Geographies doi: 10.3390/geographies4020014
Authors: Zhiqiu Xie S M Asik Ullah Chika Takatori
In Japan, rural areas are grappling with population decline and aging, leading to a shortage of labor for farmland maintenance. This has resulted in the abandonment of farmland or its conversion for solar photovoltaic (PV) use. However, this unplanned conversion raises concerns about agricultural productivity decline, landscape degradation, biodiversity loss, water resource maintenance, and disaster prevention. This study focuses on the Kushida watershed, examining (1) accurate farmland classification using remote sensing data, (2) the geographical distribution of farmland converted to PV systems from 2016 to 2021 and concentrated along the river, especially on north-facing slopes, (3) the highest conversion rates in wheat fields, followed by legume fields, tea fields, and paddy fields, and (4) no clear correlation between farmland conversions and changes in the number of farmers, but associations with farmland geography and solar radiation levels. These findings contribute to a nuanced understanding of sustainable rural development in Japan, emphasizing the importance of considering geographical factors in the conversion of farmland to PV.
]]>Geographies doi: 10.3390/geographies4020013
Authors: Miriam Marzen
Wind erosivity has an intermittent character due to complicated interactions between air streams, surface characteristics, and sediment particles. To experimentally investigate the effect of a sudden and local gust on sediment entrainment, a simple setup was installed in a mobile wind tunnel. One, three, and five consecutive gusts were applied and compared with standard test conditions with steady wind. The applied wind was characterized by total test duration (s), duration of gust (s), mean velocity, peak velocity (m s−1), gust factor, and transport capacity based on sediment-specific threshold velocity. The eroded material was collected by sediment containers. The results suggest that 1. the application of gusts inside the mobile wind tunnel setup is feasible but related to uncertainty concerning the applied wind conditions, and 2. the horizontal transport rate increased with the number of applied gusts. While the highest rates were measured during five gusts on sand, the relative effect of gusts was most accentuated in the comparison of one gust to no gust on loam. The findings highlight how temporally and spatially limited gust impact causes extreme particle entrainment. These particles may subsequently either start erosion or enter vertical dust transport.
]]>Geographies doi: 10.3390/geographies4010012
Authors: Vassilis P. Arapoglou Stavros Nikiforos Spyrellis
Recent treatment of accommodation and arrival infrastructures for asylum seekers and refugees has fuelled international research on refugee reception policies in urban environments and on the consequences of related initiatives of the European Union and international organizations such as the UNHCR. Using Athens as a case study, this article provides empirical evidence to revive the theoretical treatment of the importance of arrival and accommodation infrastructures in urban areas in transition. We collected and compiled data from four sources: the 2011 population census, the 2018 ESTIA accommodation program and the UNHCR Site Management Support (SMS) Reports of Temporary Accommodation Sites and Reception and Identification Centres (RICs), and a primary survey of services for asylum seekers and refugees. After the geocoding of data, we calculate indices for key dimensions of the segregation of accommodated asylum seekers and foreign nationals. We discuss the findings, seeking to highlight how the location and the composition of accommodation infrastructures has been influenced by a wider process of urban change and adaptations to global forces, leading not only to the transformation of inner-city zones but also suburban and peri-urban areas.
]]>Geographies doi: 10.3390/geographies4010011
Authors: Hussam Hag Husein Rupert Bäumler Bernhard Lucke Wahib Sahwan
This study investigates the distribution, morphology, and properties of these soils, focusing on areas such as littoral plains, high hilly areas, and rift depression valleys. Black soils occur in the eastern Mediterranean with a limited distribution, and some of them meet the requirements for black soils according to the INBS (International Network of Black Soils), while others do not. Black soils can be categorized into three types based on their genesis and evolution: calcareous black soils (mainly raw rocky rendzina), hydromorphic black soils, and black soil on basalt. While black soils were found in various bioclimatic stages and parent materials, their presence was notably limited in certain areas, contrary to prior indications. A soil morphology analysis revealed distinct color variations and depths, influenced by the accumulation of organic matter for hydromorphic and calcareous black soils and basaltic parent material for black soils on basalt. A particle size analysis indicated texture variations from clay to loam, with no clear indication of illuviation. A chemical analysis showed alkaline pH levels, except in basalt-derived soils, which exhibited a slight acidity. Hydromorphic black soil is the most important in terms of expansion and agricultural use and is only found in limestone marl deposits and lakes in depressions emerging from Dead Sea rifts under conditions of saturation or poor drainage. These soils have a thick, dark moly horizon and a high organic matter content.
]]>Geographies doi: 10.3390/geographies4010010
Authors: Ruggero Ermini Carmen Fattore Amir Aubed Zoubi
Urban transformations change land use, permeability, and morphology of the areas involved in the evolution process; this, consequently, modifies the impact produced by the precipitation phenomena and increases the risk of flooding or uncontrolled runoff in different areas.The proposed watershed hydrologic approach enables us to consider the morphology of the territory together with the transformations implemented by human activities, and this allows us to evaluate the effects of each area on neighboring areas, emphasizes the hydrological roles of upper, intermediate, and lower parts, and reveals urban and non-urban connections. This elucidates hydromorphic complexities in urban transformations and assesses climate change adaptability. The suggested methodology has been implemented in the urban district of “Sasso Caveoso” within the city of Matera. This application facilitates a quantitative synthesis of the contextual response, allowing for an analysis across various scenarios and offering decision-support tools of practical utility.
]]>Geographies doi: 10.3390/geographies4010009
Authors: Jessica R. Mosher Jim E. Banta Rhonda Spencer-Hwang Colleen C. Naughton Krystin F. Kadonsky Thomas Hile Ryan G. Sinclair
Research has shown that there has consistently been a lack of equity and accessibility to SARS-CoV-2 testing in underserved and disadvantaged areas in the United States. This study examines the distribution of Wastewater-Based Epidemiology (WBE) testing placement across the United States (US), particularly within the context of underserved communities, and explores an environmental equity approach to address the impact of WBE on future pandemics. The methods combined the Centers for Disease Control Social Vulnerability Index (CDC-SVI) data set at the county level in a geospatial analysis utilizing ArcGIS and multilinear regression analysis as independent variables to investigate disparities in WBE coverage in the US. The findings show that disparities exist between counties in the use of WBE nationwide. The results show that WBE is distributed inequitably on national and state levels. Considering the nationwide adoption of WBE and funding availability through the CDC National Wastewater Surveillance System, these findings underscore the importance of equitable WBE coverage for effective COVID-19 monitoring. These findings offer data to support that a focus on expanding WBE coverage to underserved communities ensures a proactive and inclusive strategy against future pandemics.
]]>Geographies doi: 10.3390/geographies4010008
Authors: Ana Clara Mourão Moura Ashiley Adelaide Rosa Paula Barros
This study proposes planning for children’s independent mobility through geoinformation technologies by listening to children. This research assumes that children’s values and expectations must be considered in city planning. A bibliographic review identified 15 indicators which make spaces safe and attractive for children to circulate and play. Thematic maps of the indicators were prepared and integrated by a multicriteria analysis by the weights of the evidence according to the hierarchical importance of each variable. The definition of the weights considered the opinions of the children and technicians. The consultation with children was carried out by mapping volunteers (VGI), a consultation on hierarchy, the geodesign of ideas for the area, and an artistic workshop. In the technical study, the query applied the Delphi method. It used the VGI—Volunteered Geographic Information—web-based platform, where children recorded places of topophilia and topophobia, while technicians mapped the presence of 15 indicators. The set of information was made available on a web-based platform called SDI—Spatial Data Infrastructure—in which there are resources for a geodesign workshop where ideas for the area were elaborated through negotiation and cocreation. The product is a transformational design for the area through urban design and the parameterization of its uses.
]]>Geographies doi: 10.3390/geographies4010007
Authors: Christina W. Lopez Evgenia Spears Tyler C. Hartwick John C. Killough Michael A. Schuett
Approximately 30% of the private land in Texas, USA is under absentee ownership. Understanding who absentee landowners are and their land management behaviors is vital for the protection of privately owned landscapes and the ecosystem services that they support, including surface water quality. By focusing on absentee landowners with properties in five watersheds in Texas, we utilized the theory of place attachment to gain insights into absentee landowners’ land management decisions and their involvement in water quality conservation programs, such as watershed protection plans (WPPs). By conducting a mail-out survey, we obtained 100 responses, which were analyzed using an exploratory factor analysis and a series of nonparametric assessments. The results revealed that, contrary to the term “absentee”, the landowners in our study demonstrated strong feelings of place attachment and heightened land stewardship. Based on these findings, we suggest that instead of considering absentee landowners as obstacles to collaborative conservation initiatives, such as WPPs, natural resource practitioners should recognize and capitalize on the emotional attachment that these landowners have to their properties, thereby fostering their involvement. By demonstrating the owner–land relationship and its behavioral outcomes among absentee landowners, this study provides a novel contribution to the existing literature on place attachment in the context of private land management and conservation.
]]>Geographies doi: 10.3390/geographies4010006
Authors: Shubham Aggarwal Kevin J. Kuehner Joe Magner
Understanding rain, ground, and surface water interactions in riparian zones is essential for hydrologic and environmental management. The novelty of this study lies in its revelation of isotopic shifts and consequent evaluation of hydrologic pathways and processes within the forested riparian zones of three distinct streams, valleys, and riparian systems in a carbonate-sandstone incipient karst landscape. We collected water samples from three southeastern Minnesota catchments: Trout Brook, Crystal Creek, and Bridge Creek. A Picarro L2130i was used to measure δ18O for oxygen, and δD for deuterium in units of ‰ (per mil). We estimated the global meteoric line for the study sites, built upon aquifer age dating, and explored aquifer transit time for the study sites using a simple seasonal amplitude model. The results showed small amplitudes for 2020 and 2021, suggesting that bedrock aquifer water was the primary source water with a mean core transit time greater than 10 years. All three catchments were different but had similar bedrock valley types and riparian sediment. The primary driving factor was the seasonal precipitation input mixing with existing water. In a normal to wetter year, the isotopic data showed larger amplitude shifts between seasons with trendlines that adjusted depending on the temperature of the new water additions. The proposed approach is valuable in revealing complex hydrologic processes and pathways and can contribute extensively to the planning and management of karst riparian systems.
]]>Geographies doi: 10.3390/geographies4010005
Authors: Qiaosong Wang
We present a near real-time solution for 3D reconstruction from aerial images captured by consumer UAVs. Our core idea is to simplify the multi-view stereo problem into a series of two-view stereo matching problems. Our method applies to UAVs equipped with only one camera and does not require special stereo-capturing setups. We found that the neighboring two video frames taken by UAVs flying at a mid-to-high cruising altitude can be approximated as left and right views from a virtual stereo camera. By leveraging GPU-accelerated real-time stereo estimation, efficient PnP correspondence solving algorithms, and an extended Kalman filter, our system simultaneously predicts scene geometry and camera position/orientation from the virtual stereo cameras. Also, this method allows for the user selection of varying baseline lengths, which provides more flexibility given the trade-off between camera resolution, effective measuring distance, flight altitude, and mapping accuracy. Our method outputs dense point clouds at a constant speed of 25 frames per second and is validated on a variety of real-world datasets with satisfactory results.
]]>Geographies doi: 10.3390/geographies4010004
Authors: Miljenko Lapaine
In the literature on map projections, we regularly encounter the name standard parallel or standard parallels. However, it is obvious that a unique definition of a standard parallel is not universally accepted. To fully clarify the meaning of standard parallels, the author proposes the notion of equidistantly mapped parallels, which has not been common in the literature so far. Equidistantly mapped parallels can be in the direction of the parallel or in the direction of the meridian. Here, it is shown that every standard parallel is also an equidistantly mapped parallel, but that the reverse need not be true. If the parallel is mapped equidistantly in the direction of the parallel, then its length in the projection plane is equal to the length of that parallel on the sphere. The opposite does not have to be true, i.e., if the length of the image of the parallel in the projection plane is equal to the length of the parallel on the sphere, this does not mean that the parallel was mapped equidistantly. In addition to standard and equidistant parallels, the concept of parallels of true length also appears in the theory of map projections. They should also be distinguished from standard and equidistant parallels.
]]>Geographies doi: 10.3390/geographies4010003
Authors: Sebastien Fleuret
Backpackers are an unusual category of travellers. Their unique mobility patterns, spatial practices, and the areas they travel through expose them to health situations that remain largely unexplored to date. This article conducts a narrative literature review (across six different databases in English and French) in this domain and highlights key contributions. The results show that backpackers frequently experience health problems during their trips. They are described as being more at risk than other tourists and more inclined to adopt harmful behaviours. However, the majority of related studies lack contextualisation, which is an advantage of geographical analysis. Moreover, given the limited volume of the existing literature, this review serves as an invitation to geographers to delve deeper into this intriguing field.
]]>Geographies doi: 10.3390/geographies4010002
Authors: Michael Walther Ulrich Kamp Nyam-Osor Nandintsetseg Avirmed Dashtseren Khurelbaatar Temujin
The over 2200 lakes of Mongolia are generally poorly studied, particularly the glacial lakes. This overview study presents a classification of the glacial lakes based on tectonic-geological and geomorphological dynamics. Selected representative lakes are described using results from fieldwork and satellite image analysis, including bathymetry, paleoshorelines, and recent lake-level fluctuations between 1987 and 2020. Generally, lake levels dropped from the early Holocene until recently, with the onset of the climate change-driven glacier recession that has resulted in lake-level rises and area expansion in almost all moraine-dammed, tongue-basin, and ice-contact lakes. In contrast, endorheic lakes have mainly been shrinking for the past forty years because of an increase in air temperature and evaporation rates and the effects of an intensifying water use within the catchment for irrigation, mining, and hydroelectric energy production in the form of dams. The creation of a lake monitoring system based on an in-depth inventory is recommended.
]]>Geographies doi: 10.3390/geographies4010001
Authors: Apostolos G. Papadopoulos Pavlos Baltas
Depopulation is caused by low fertility rates and out-migration, and it applies to countries, regions and smaller areas. Rural depopulation is defined as a sharp population decline that falls well below an adequate population size and indicates that an area has lost its demographic reproductive capacity. This paper discusses the socioeconomic and territorial aspects of rural depopulation, attempting to do justice to the spatial dimensions of the phenomenon. Greece exhibits all the symptoms of demographic transition, leading to labour shortages, declining economic productivity, and increasing demands on the health and welfare system. The study on rural depopulation in Greece focuses on the changes and dynamics observed at the municipal and regional levels. A typology has been developed to identify rural communities in Greece. The main source of demographic data for our study is the Greek censuses (1991, 2001, 2011, and 2021). Demographic and socioeconomic trends in Greece are interlinked and show different regional and local dynamics. Rural depopulation is closely related to the study of (international and internal) migration, even though the latter does not provide a permanent solution to depopulation. An empirical analysis has shown that there is a need to revitalise rural areas through socioeconomic improvements, infrastructure investments, and policies that directly impact rural communities.
]]>Geographies doi: 10.3390/geographies3040044
Authors: Raj Bridgelall Ryan Jones Denver Tolliver
The inefficiency of transporting goods contributes to reduced economic growth and environmental sustainability in a country. Autonomous trucks (ATs) are emerging as a solution, but the imbalance in the weight moved and ton-miles produced by long-haul and short-haul trucking creates a challenge in targeting initial deployments. This study offers a unique solution by presenting a robust method that combines data mining and geographic information systems (GISs) to identify the optimal routes for ATs based on a top-down approach to maximize business benefits. Demonstrated in a U.S. case study, this method revealed that despite accounting for only 16% of the weight moved, long-haul trucking produced 56% of the ton-miles, implying a high potential for ATs in this segment. The method identified eight key freight zones in five U.S. states that accounted for 27% of the long-haul weight and suggested optimal routes for initial AT deployment. Interstate 45 emerged as a pivotal route in the shortest paths among these freight zones. This suggests that stakeholders should seek to prioritize funding for infrastructure upgrades and maintenance along that route and the other routes identified. The findings will potentially benefit a broad range of stakeholders. Companies can strategically focus resources to achieve maximum market share, regulators can streamline policymaking to facilitate AT adoption while ensuring public safety, and transportation agencies can better plan infrastructure upgrades and maintenance. Users globally can apply the methodological framework as a reliable tool for decision-making about where to initially deploy ATs.
]]>Geographies doi: 10.3390/geographies3040043
Authors: Vassilios Krassanakis Andriani Skopeliti Merve Keskin Paweł Cybulski
Geovisualization (or Geographic Visualization) represents an interdisciplinary scientific field spanning cartography, geographic information science (GIScience) and technology, computer science and human–computer interaction (HCI), psychology, and cognitive science [...]
]]>Geographies doi: 10.3390/geographies3040042
Authors: Yusik Choi Alberto Giordano
In this article we explore the text of the over 16,000 historical markers erected in the state since 1936, using GIS and corpus linguistics to determine the where, how, what, and when of how Texas memorializes its racial and ethnic groups. Unsurprisingly, our results indicate that the story of Texas is implicitly a narrative of white people. More interestingly, the term “African (Americans)” begins to be commemorated especially after the 1990s, but only in stories of community, religion, school, and children, as Texas historical markers do not to dwell on narratives of slavery, the civil rights movement, and lynchings. “Indians” and “Mexicans” in the 1930s and 1960s exemplify the most egregious case of derogatory semantics we found in the markers. As concerns racial and ethnic groups, in general they tend to be memorialized where they were historically present, whether or not such groups are still there. The analysis also reveals the increasing concentration of the markers in urban areas.
]]>Geographies doi: 10.3390/geographies3040041
Authors: Petr Iakovlevitch Ekel Sandro Laudares Adriano José de Barros Douglas Alexandre Gomes Vieira Carlos Augusto Paiva da Silva Martins Matheus Pereira Libório
Web Geographic Information Systems (WebGISs) were widely used to monitor COVID-19 cases and deaths during the pandemic. Furthermore, geotechnologies were also very useful in education, public management, tourism, and other areas. Although there are WebGISs with a high level of sophistication, most are simple, consisting of geovisualizers of cases, deaths, and vaccinations. This study develops a WebGIS that offers information about age, comorbidities, and tests, which can be analyzed from specific points such as hospitals, main access roads, regions, or neighborhoods. Although it is not a highly sophisticated solution, the WebGIS developed in this study is especially useful for municipal governments in developing countries like Brazil that do not have patient health data in geographic databases. The WebGIS developed in this study offers public managers essential information for developing effective public policies to combat the COVID-19 pandemic and other epidemiological phenomena such as dengue and malaria.
]]>Geographies doi: 10.3390/geographies3040040
Authors: Irina Stanciu Dumitru Ioane
The Moesian Platform represents a major tectonic unit of the foreland of the Carpathians and Balkans, spanning across the southern part of Romania and the northern part of Bulgaria. Although the Moesian Platform is considered to be a stable tectonic unit, it has played a significant role in the geological history of the region, influencing the development of the surrounding Carpathian and Balkan mountain ranges, making it an area of interest for studying tectonic history, geological structures, and landscape evolution. In the southern part of the Moesian Platform in Romania, delineated to the north and to the east by the steep slopes of the Argeş River valley and to the south by the steep slopes of the Danube River valley, an elevated and W–E promontory-looking geomorphological feature identified by the local inhabitants as “hill” is distinct from the neighbouring flat relief of the Romanian plain. This study is the result of a comprehensive investigation into the geomorphological features and neotectonic structures within this region. An intriguing outcrop displaying a filled fault, cutting and displacing the Quaternary sedimentary formations of the recently named Argeş Promontory, shed light on recent tectonic activities that have influenced the landscape. By integrating field observations, geological, and tectonic data, as well as satellite geodetic data, our results contribute to a better understanding of the study area’s regional geodynamics, emphasizing the significant role of tectonic activity in shaping the present-day landscape.
]]>Geographies doi: 10.3390/geographies3040039
Authors: Ronnie Donaldson Tina Odinakachi Iirmdu Musfiqah Majiet Pauline Van der Spuy
Township tourism has become more varied, offering a wider range of products, experiences and services. In this paper, we examine residents and stakeholders’ opinions on township tourism in Langa, Cape Town, South Africa; an area characterised by crime, unemployment, housing backlogs and poverty. Using a qualitative approach, this paper reports on empirical evidence conducted with key tourism stakeholders to understand some of their perceptions regarding township tourism development in Langa. Concerns about safety, poor infrastructure and a lack of interaction between tourists and the local community are raised by Langa residents and community leaders. Their dissatisfaction with tour guides and tour routes serves as a reminder of the need for more inclusive practices. While business owners are aware of the potential of tourism in promoting cross-cultural dialogue, deepening understanding and creating priceless experiences, they are constrained by perceptions of crime, a lack of tourist exposure to local establishments and the exclusion from decision-making processes. Despite these difficulties that township tourism faces, it is crucial to promote ethical tourism practices that put emphasis on genuine encounters and local community empowerment.
]]>Geographies doi: 10.3390/geographies3040038
Authors: Ailton Alves de Carvalho Marcelo José Gama da Silva Fabiane Rabelo da Costa Batista Jucilene Silva Araújo Abelardo Antônio de Assunção Montenegro Thieres George Freire da Silva Thayná Alice Brito Almeida Marcos Vinícius da Silva Joelma Dias Iara Tamires Rodrigues Cavalcante Jhon Lennon Bezerra da Silva
The detection and monitoring of changes in land use and land cover play a crucial role in understanding land degradation and are fundamental to preserving agroecosystems. Their association with hydrological information allows essential responses to changes in hydrological patterns to be identified, contributing to water security in watersheds. Therefore, this study aimed to assess spatio-temporal dynamics and physico-hydrological trends in rainfall, runoff and land use in the Paraíba watershed. The study was conducted in the Paraíba watershed, using land use data and information from pluviometric and fluviometric stations with temporal series of more than 30 years. The Mann-Kendall statistical test was adopted to verify trends. Results indicate annual reduction trends for both native forest area and water bodies in the Paraíba watershed. On the other hand, the area designated for agriculture showed a significant increase. The correlation analysis between water bodies and forests (R² = 0.63) highlights a strong association between the decrease in forest area and the reduction in water availability, influencing the decrease in annual flow. These results serve as a warning to expand water resource management for the region, aiming to preserve and to enhance sustainable use. Therefore, the implementation of conservation measures, monitoring procedures, and adequate management is required to face the challenges imposed by climate change and land use and occupation, ensuring the water availability for the future.
]]>Geographies doi: 10.3390/geographies3040037
Authors: Hartwig H. Hochmair Gerhard Navratil Haosheng Huang
The motivation to organize this Special Issue originated from the observation of rapid changes taking place in the domain of geographical information science and systems over the past few decades [...]
]]>Geographies doi: 10.3390/geographies3040036
Authors: Efthymia Sarantakou
This paper aims to outline a framework for reviewing the issues faced by tourism destination planning in the 21st century. This paper documents the use of tourism destination typologies as a framework for policy analysis and as a basis for decision making. The main research hypothesis of this study is that typologies based on, or primarily focused on, geographical dimensions have historically been the appropriate framework for strategic planning. This study proposes the use of a basic geographical typology, according to which destinations are categorized into urban, island, coastal, and mountainous. This paper refers to the evolution, key features, and challenges faced by each type of destination. Through a review of international best practices, this study maps out the fundamental objectives, developmental patterns, and strategies for each geographical type of destination, offering valuable insights for future research. Emphasis is given to contemporary trends in tourism planning in the first few decades of the 21st century.
]]>Geographies doi: 10.3390/geographies3040035
Authors: Nadja Gomes Machado Névio Lotufo Neto Juliana Barbosa da Silva Lotufo Luiz Octavio Fabrício dos Santos Marcelo Sacardi Biudes
Dengue is a serious infectious disease worldwide and a climate-sensitive disease. Thus, our goals were to (i) evaluate the relationship between dengue incidence and meteorological variables (rainfall and air temperature); (ii) identify the spatiotemporal pattern of dengue incidence in the municipalities of Mato Grosso from 2001 to 2020; and (iii) verify the spatial dependence of dengue incidence in the dry and wet seasons. We used dengue data from 2001 to 2020, monthly rainfall estimates from GPM, and daily air temperature estimates from ERA-5. The municipalities of the Mato Grosso state are included in 16 healthcare territories. The seasonal rainfall pattern indicates that the peak of the dengue endemic occurred in the wet season. However, drier and/or warmer places had a lower incidence of dengue in the dry season. Furthermore, a lagged effect of meteorological variables on dengue incidence has been identified, ranging from 0 to 7 months. Hotspot areas were identified which might have the potential for an intense spreading of dengue in Mato Grosso. They were mainly concentrated in the healthcare territory of Teles Pires (ID 14) in the dry season, while they were concentrated in the healthcare territories of Garças Araguaia (ID 5), Oeste (ID 11), and Teles Pires (ID 14) in the wet season. In addition, they are located in the Am climate and in the Amazon Forest and Brazilian savanna biomes, which have higher dengue incidence values. These results help to highlight which municipalities decision-makers must intervene in the public health system to prevent and control future epidemics.
]]>Geographies doi: 10.3390/geographies3040034
Authors: Adelar Fochezatto Eduardo Rodrigues Sanguinet Patricia Batistela Rodrigo Valdes
During the COVID-19 pandemic, regions were affected by a combination of economic crises: weak demand and constrained supply. Several studies have sought to analyse the heterogeneous effects of supply and demand shocks on the labour market, economic growth, and the environment. This study has a different focus, estimating both direct and indirect effects of demand and supply shocks adopted during the pandemic in Brazil and Chile. Afterwards, the paper compares the degree of regional absorption (leakage) of income resulting from each of these shocks, applying an interregional input–output model for each country. The results of this study show that income absorption by the poorest regions is relatively greater in the case of a supply shock. It can be said, therefore, that this type of shock improves the retention of income generated in the poorest regions, favouring the development of these localities and the reduction in regional inequalities. The main reason for this result is that supply policies have restricted essential sectors to a lesser extent, and these sectors are generally less concentrated in large urban centres in both Brazil and Chile. In other words, much of the interregional leakage is driven by the demand for non-essential products, mainly in the richest urban economy centres. Finally, the geographical dimension of regional inequalities leads to the economic benefit of prosperous areas in the country when shocks occur in vulnerable regions, highlighting the centre–periphery pattern in both countries.
]]>Geographies doi: 10.3390/geographies3040033
Authors: Gamal El Afandi Hossam Ismael
More than half of the global population lives in urban areas, which can cause the phenomenon known as Urban Heat Island (UHI). UHI is a phenomenon where urban areas experience higher temperatures compared to their rural surroundings. The occurrence of UHI in large cities is primarily due to urbanization and increased vehicular emissions. Factors such as wind speed and direction, solar flux, and the thermodynamic properties of surface materials determine the intensity of UHI. It can cause thermal air circulation, leading to high concentrations of urban air pollutants such as fine particulate matter (PM2.5). These pollutants can remain suspended in the air and cause asthma and allergies. It is essential to understand the characteristics of UHI intensity and its effect on air quality. This study aims to analyze the spatiotemporal variations of UHI and their correlation with PM2.5 concentration in three Alabama cities, namely Birmingham, Montgomery, and Mobile, during the summer seasons of 2002, 2012, and 2022. The study also compares UHI in these cities with nearby rural areas to determine the effect of urbanization by calculating the Normalized Difference Building Index (NDBI). To achieve these objectives, the Land Surface Temperature (LST), UHI intensity, and NDBI Datasets were analyzed. The results showed that PM2.5 concentrations in the cities have been decreasing annually since 2002, leading to an improvement in air quality. There was a negative linear correlation between UHI intensity and PM2.5 concentration. However, LST remained consistently high throughout the study period. The correlation between UHI intensity and NDBI was positive. The findings of this study can help us better understand the dynamics and driving mechanisms of the urban heat environment. Furthermore, they can assist urban metropolitan planners in developing more efficient mitigation strategies that reduce the negative impacts of UHI and PM2.5 concentrations on the environment.
]]>Geographies doi: 10.3390/geographies3030032
Authors: Adolfo Quesada-Román Manuel Peralta-Reyes
This study conducts a bibliometric analysis of 735 research papers on geomorphological mapping published in English between 2000 and 2021 using the Web of Science database. The analysis focuses on key metrics such as annual publication rates, journal distribution, common keywords, and frequently cited papers. The results demonstrate sustained investment in geomorphological mapping research over the past two decades, driven by advancements in data analysis, GIS technologies, and cross-institutional and cross-country collaboration. While European universities and research centers lead the field, researchers from Latin America and Asia are also making noteworthy contributions. However, research concentration remains largely in Europe, particularly at low altitudes. The study highlights the vital importance of investment in geomorphological mapping research and the benefits of collaboration to advance understanding and knowledge production. It also emphasizes the need for greater geographic and cultural diversity among researchers to ensure a more comprehensive and inclusive approach to research in this field.
]]>Geographies doi: 10.3390/geographies3030031
Authors: Innocensia Owuor Hartwig H. Hochmair
Social media platforms are valuable data sources in the study of public reactions to events such as natural disasters and epidemics. This research assesses for selected countries around the globe the time lag between daily reports of COVID-19 cases and GDELT (Global Database of Events, Language, and Tone) and Twitter (X) COVID-19 mentions between February 2020 and April 2021 using time series analysis. Results show that GDELT articles and tweets preceded COVID-19 infections in Australia, Brazil, France, Greece, India, Italy, the U.S., Canada, Germany, and the U.K., while for Poland and the Philippines, tweets preceded and GDELT articles lagged behind COVID-19 disease incidences, respectively. This shows that the application of social media and news data for surveillance and management of pandemics needs to be assessed on a case-by-case basis for different countries. It also points towards the applicability of time series data analysis for only a limited number of countries due to strict data requirements (e.g., stationarity). A deviation from generally observed lag patterns in a country, i.e., periods with low COVID-19 infections but unusually high numbers of COVID-19-related GDELT articles or tweets, signals an anomaly. We use the seasonal hybrid extreme Studentized deviate test to detect such anomalies. This is followed by text analysis of news headlines from NewsBank and Google on the date of these anomalies to determine the probable event causing an anomaly, which includes elections, holidays, and protests.
]]>Geographies doi: 10.3390/geographies3030030
Authors: Bruna M. Netto Kita D. Macario Ayrton Assumpção Maikel Diaz Stewart J. Fallon Xiaomei Xu Ingrid Chanca Carla Carvalho
Foraminifera are widely used in paleoclimatic and paleoceanographic studies, providing information about past ocean conditions. However, in order to use these tracers, it is essential to obtain an accurate chronology. Radiocarbon has proven to be a powerful tool in developing robust chronologies. Sample sizes of a few milligrams of carbonate material are needed for precise radiocarbon determination using accelerator mass spectrometry (AMS). In the specific case of paleoceanographic and paleoenvironmental studies, Foraminifera microfossils are the most important indicator of oceanic conditions. However, for establishing the chronology of deposition, sample availability is often limited. In AMS facilities using solid ion sources, such as the Radiocarbon Laboratory of the Universidade Federal Fluminense (LAC-UFF), in Brazil, CO2 samples need to be converted to graphite after physical and chemical pre-treatment to remove contamination. Reducing the sample sizes increases the relative contribution of contamination and can favor increased background levels. In this work, we tested different amounts of 14C-free carbonate samples as a means to evaluate the pattern of contamination. For the sealed tube Zn/TiH2 graphitization method, we tested prebaking the graphitization tubes and compared storage procedures. As a result, the background for regular-sized samples was decreased, and accurate measurement of carbonate samples containing ca. 0.5 mg C could be performed. Prebaked graphitization tubes can safely be stored in desiccator cabinets for up to 4 weeks. Foraminifera samples with mass as low as 1 mg (ca. 0.1 mg C) can now be measured at the LAC-UFF AMS facility, provided that C contamination can be estimated and corrected. The developments presented in this work allowed for the study of species-specific Foraminifera and other small-sized carbonate samples.
]]>Geographies doi: 10.3390/geographies3030029
Authors: Fernando Orduna-Cabrera Marcial Sandoval-Gastelum Ian McCallum Linda See Steffen Fritz Santosh Karanam Tobias Sturn Valeria Javalera-Rincon Felix F. Gonzalez-Navarro
The creation of crop type maps from satellite data has proven challenging and is often impeded by a lack of accurate in situ data. Street-level imagery represents a new potential source of in situ data that may aid crop type mapping, but it requires automated algorithms to recognize the features of interest. This paper aims to demonstrate a method for crop type (i.e., maize, wheat and others) recognition from street-level imagery based on a convolutional neural network using a bottom-up approach. We trained the model with a highly accurate dataset of crowdsourced labelled street-level imagery using the Picture Pile application. The classification results achieved an AUC of 0.87 for wheat, 0.85 for maize and 0.73 for others. Given that wheat and maize are two of the most common food crops grown globally, combined with an ever-increasing amount of available street-level imagery, this approach could help address the need for improved global crop type monitoring. Challenges remain in addressing the noise aspect of street-level imagery (i.e., buildings, hedgerows, automobiles, etc.) and uncertainties due to differences in the time of day and location. Such an approach could also be applied to developing other in situ data sets from street-level imagery, e.g., for land use mapping or socioeconomic indicators.
]]>Geographies doi: 10.3390/geographies3030028
Authors: Daniel A. Griffith
An enumeration of spatial autocorrelation’s (SA’s) polyvalent forms occurred nearly three decades ago. Attempts to conceive and disseminate a clearer explanation of it employ metaphors seeking to better relate SA to a student’s or spatial scientist’s personal knowledge databank. However, not one of these uses the jigsaw puzzle metaphor appearing in this paper, which exploits an analogy between concrete visual content organization and abstract map patterns of attributes. It not only makes SA easier to understand, which furnishes a useful pedagogic tool for teaching novices and others about it, but also discloses that many georeferenced data should contain a positive–negative SA mixture. Empirical examples corroborate this mixture’s existence, as well as the tendency for marked positive SA to characterize remotely sensed and moderate (net) positive SA to characterize socio-economic/demographic, georeferenced data.
]]>Geographies doi: 10.3390/geographies3030027
Authors: Lilian Alessa James Valentine Sean Moon Chris McComb Sierra Hicks Vladimir Romanovsky Ming Xiao Andrew Kliskey
There has been a growth in the number of composite indicator tools used to assess community risk, vulnerability, and resilience, to assist study and policy planning. However, existing research shows that these composite indicators vary extensively in method, selected variables, aggregation methods, and sample size. The result is a plethora of qualitative and quantitative composite indices to choose from. Despite each providing valuable location-based information about specific communities and their qualities, the results of studies, each using disparate methods, cannot easily be integrated for use in decision making, given the different index attributes and study locations. Like many regions in the world, the Arctic is experiencing increased variability in temperatures as a direct consequence of a changing planetary climate. Cascading effects of changes in permafrost are poorly characterized, thus limiting response at multiple scales. We offer that by considering the spatial interaction between the effects of permafrost, infrastructure, and diverse patterns of community characteristics, existing research using different composite indices and frameworks can be augmented. We used a system-science and place-based knowledge approach that accounts for sub-system and cascade impacts through a proximity model of spatial interaction. An estimated ‘permafrost vulnerability surface’ was calculated across Alaska using two existing indices: relevant infrastructure and permafrost extent. The value of this surface in 186 communities and 30 military facilities was extracted and ordered to match the numerical rankings of the Denali Commission in their assessment of permafrost threat, allowing accurate comparison between the permafrost threat ranks and the PVI rankings. The methods behind the PVI provide a tool that can incorporate multiple risk, resilience, and vulnerability indices to aid adaptation planning, especially where large-scale studies with good geographic sample distribution using the same criteria and methods do not exist.
]]>Geographies doi: 10.3390/geographies3030026
Authors: Nikolaos Gourgouletis Marianna Gkavrou Evangelos Baltas
Reference evapotranspiration (ETo) estimation is essential for water resources management. The present research compares four different ETo estimators based on reanalysis data (ERA5-Land) and in situ observations from three different cultivation sites in Greece. ETo based on FAO56-Penman–Monteith (FAO-PM) is compared to ETo calculated from the empirical methods of Copais, Valiantzas and Hargreaves-Samani using both reanalysis and in situ data. The daily and monthly biases of each method are calculated against the FAO56-PM method. ERA5-Land data are also compared to ground-truth observations. Additionally, a sensitivity analysis is conducted on each site for different cultivation periods. The present research finds that the use of ERA5-Land data underestimates ground-truth-based ETo by 35%, approximately, when using the FAO56-PM method. Additionally, the use of other methodologies also shows underestimation of ETo when calculated with ERA5-Land data. On the contrary, the use of the Valiantzas and Copais methodologies with in situ observations shows overestimation of ETo when compared to FAO56-PM, in the ranges of 32–62% and 24–56%, respectively. The sensitivity analysis concludes that solar radiation and relative humidity are the most sensitive variables of the Copais and Valiantzas methodologies. Overall, the Hargreaves-Samani methodology was found to be the most efficient tool for ETo estimation. Finally, the evaluation of the ERA5-Land data showed that only air temperature inputs can be utilized with high levels of confidence.
]]>Geographies doi: 10.3390/geographies3030025
Authors: Andrew G. O. Malone
Climate change is altering the conditions to which communities have adapted. The Köppen–Geiger classification system can provide a compact metric to identify regions with notable changes in climatic conditions. Shifting Köppen–Geiger climate zones will be especially impactful in regions with large populations. This study uses high-resolution datasets on Köppen–Geiger climate zones and populations to quantify the number of people affected by shifting climate zones (i.e., population exposure to shifting climate zones). By the end of this century, 9–15% of the Earth’s land surface is projected to shift its climate zone. These shifts could affect 1.3–1.6 billion people (14–21% of the global population). Many of the affected people live in areas that were classified as temperate in the historical period. These areas are projected to be classified as tropical or arid in the future. This study presents a new metric for exposure to climate change: the number of people living in areas whose climate zone classification is projected to shift. It also identifies populations that may face climatic conditions in the future that deviate from those to which they have adapted.
]]>Geographies doi: 10.3390/geographies3030024
Authors: Dean Kyne
Colonia communities, which host forgotten Americans, lack essential services such as portable water, adequate wastewater and solid waste disposal, adequate drainage, and adequate paved roads. The aim of this study is to investigate five key aspects of the colonias in the Rio Grande Valley (RGV), which include the total count of colonias in the valley, their susceptibility to public health hazards, flooding occurrences, the transformations that have occurred over the past two decades, and community resilience. This research utilizes two datasets, namely the Colonia Database from the Texas Secretary of State and the community resiliency estimates from the Census Bureau. Geographical information systems (GIS) methods are employed to analyze the spatial and temporal distribution of colonia communities. The principal results reveal that colonia communities host 14% of the RGV’s total 1.37 million population. About half of the total colonia population resides in Hidalgo County, followed by Starr, Cameron, and Willacy counties. About 87% of the total colonia communities exist in census tracts characterized by low or very low community resiliency. Furthermore, 26% of the total colonia communities experiencing flooding after rainfall are in tracts with low or very low community resiliency. This study provides the major conclusion that while there have been slight improvements in the colonias’ susceptibility to public health risks within the past two decades, there still remains significant developmental work. Without tackling these challenges, achieving meaningful progress in community resilience becomes a daunting task. Applying an environmental justice lens to the issues faced by colonia communities helps shed light on the systemic inequalities and injustices they experience.
]]>Geographies doi: 10.3390/geographies3030023
Authors: Augustine-Moses Gaavwase Gbagir Kylli Ek Alfred Colpaert
This paper analyzes the performance of the open-source OpenDroneMap image processing software (ODM) across multiple platforms. We tested desktop and laptop computers as well as high-performance cloud computing and supercomputers. Multiple machine configurations (CPU cores and memory) were used. We used eBee S.O.D.A. drone image datasets from Namibia and northern Finland. For testing, we used the OpenDroneMap command line tool with default settings and the fast orthophoto option, which produced a good quality orthomosaic. We also used the “rerun-all option” to ensure that all jobs started from the same point. Our results show that ODM processing time is dependent upon the number of images, a high number of which can lead to high memory demands, with low memory leading to an excessively long processing time. Adding additional CPU cores is beneficial to ODM up to a certain limit. A 20-core machine seems optimal for a dataset of about 1000 images, although 10 cores will result only in slightly longer processing times. We did not find any indication of improvement when processing larger datasets using 40-core machines. For 1000 images, 64 GB memory seems to be sufficient, but for larger datasets of about 8000 images, higher memory of up to 256 GB is required for efficient processing. ODM can use GPU acceleration, at least in some processing stages, reducing processing time. In comparison to commercial software, ODM seems to be slower, but the created orthomosaics are of equal quality.
]]>Geographies doi: 10.3390/geographies3030022
Authors: Omran E. Frihy Jean-Daniel Stanley
The most extensive coverage of surficial sediment samples collected to date on Egypt’s Nile Delta coast and shelf is needed to better define sediment dispersal patterns across this setting’s rapidly eroding margin. Changes in time are now induced by River Nile sediment cutoff by dams, sea level rise, marked shelf subsidence, and regional climate changes, which have altered the amounts and components of sediments; these require replacement, along with the implementation of more effective coastal protection measures. Multiple computer-generated offshore maps depict the distributions and proportions of sand, silt, and mud; the mean grain size and standard deviation (sorting); heavy mineral concentrations; and carbonate content. Heavy mineral lobes at the coast and offshore identify former Nile branch sites. Channel lobes extending seaward resulted from their progradational phase and from the delta’s altered sedimentation from the early to late Holocene. The progressive deposition and erosion of these fossil fluvial lobes, and of two active Nile channels, selectively removed their quartz and less dense minerals, thus concentrating heavy minerals on the coast and inner shelf. The prolonged dispersal of original sediment effluence from relict and recent Nile tributaries induced variable depositional patterns on the present shelf. These coastal depocenters, along with extensive sand, silt, and mud from shelf sediments, were reworked further seaward and dispersed by bottom currents, thus masking most previous onshore-to-offshore transport patterns. The major surficial features document long-term responses to the diverse dispersal that influenced the shoreline to the outer shelf deposits from the Pleistocene to the present.
]]>Geographies doi: 10.3390/geographies3020021
Authors: Georgios Lampropoulos George Panagiotopoulos Christina Giannakoula Alexandros Kokkalas
This paper presents the development procedure and significance of a web mapping application designed for disseminating, exploring, and analyzing Kaupert’s 19th-century Maps of Attica, Greece. The application facilitates historical and geographical study by providing access to high-resolution map images and overlaying multiple vector layers of geospatial data. The paper outlines the methods used to create the application, which includes the process of interpreting, digitizing, and organizing the original mapped data, georeferencing the historical cartographic sheets, and developing the web-based mapping application. The results of this work include a comprehensive and interactive digital reference tool for studying the ancient topography of Attica, as well as a framework for future research. Overall, this work highlights the potential of digital technologies to transform the way we approach and study historical maps and other cultural artifacts.
]]>Geographies doi: 10.3390/geographies3020020
Authors: Cheila Avalon Cullen Rafea Al Suhili
Jamaica, as a Small Island Developing State (SIDS), is highly vulnerable to weather extremes. As precipitation persistence is a critical factor in determining the susceptibility of an area to risks, this work assesses the spatial and temporal variations of rainfall persistence in Jamaica from 1981 to 2020, using satellite-based information. The Hurst exponent (H) and the serial correlation coefficient (SCC) are used to evaluate the long-term persistence of precipitation and the Persistence Threshold (PT) concept is introduced to provide a description of rainfall characteristics over short periods, specifically, the number of consecutive days with precipitation above or below a set threshold value. The PT method is a novel concept that expands upon the Consecutive Dry Days (CDD) and Consecutive Wet Days (CWD) methods that only consider a threshold of 1 mm. Results show notable temporal and spatial variations in persistence over the decades, with an overall increasing trend in high precipitation persistence and a decreasing trend in low precipitation persistence. Geographically, the northern mountainous area of Jamaica received the most persistent rainfall over the study period with an observed increase in extreme rainfall events. The excess rainfall of the 2001–2010 decade is remarkable in this study, coinciding with the global unprecedented climate extremes during this time. We conclude that the data used in this study is viable for understanding and modeling rainfall trends in SIDS like Jamaica, and the derived PT method is a useful tool for short-term rainfall trends, but it is just one step toward determining flood or drought risk. Further research will focus on developing drought and flood indices.
]]>Geographies doi: 10.3390/geographies3020019
Authors: Grayson R. Morgan Alexander Fulham T. Grant Farmer
As the world’s urban population increases to the predicted 70% of the total population, urban infrastructure and built-up land will continue to grow as well. This growth will continue to have an impact on the urban heat island effect in all of the world’s cities. The urban tree canopy has been found to be one of the few factors that can lessen the effects of the urban heat island effect. This study seeks to accomplish two objectives: first, we examine the use of a commonly used machine learning classifier (e.g., Support Vector Machine) for identifying the urban tree canopy using no-cost high resolution NAIP imagery. Second, we seek to use Land Surface Temperature (LST) maps derived from no-cost Landsat thermal imagery to identify correlations between canopy loss and temperature hot spot increases over a 14-year period in Columbia, SC, USA. We found the SVM imagery classifier was highly accurate in classifying both the 2005 imagery (94.3% OA) and the 2019 imagery (94.25% OA) into canopy and other classes. We found the color infrared image available in the 2019 NAIP imagery better for identifying canopy than the true color images available in 2005 (97.8% vs. 90.2%). Visual analysis based on the canopy maps and LST maps showed temperatures rose near areas where tree canopy was lost, and urban development continued. Future studies will seek to improve classification methods by including other classes, other ancillary data sets (e.g., LiDAR), new classification methods (e.g., deep learning), and analytical methods for change detection analysis.
]]>Geographies doi: 10.3390/geographies3020018
Authors: Robert B. Srygley Jacob I. Dixon Patrick D. Lorch
Microhabitats can provide thermal niches that affect geographic range shifts of species as the climate changes and provide refuges for pest and beneficial insect populations in agricultural regions. The spatial distribution of microhabitats is influenced by topography that can influence local extinction and recolonization by animal populations. Scaling local temperature-dependent processes to a regional scale of population expansion, and contraction requires the validation of biophysical models of near surface temperatures. We measured temperature at 2.5 cm above and below ground at 25 sites in each of the two regions: southern and northern Utah, USA. Using NichMapR version 3.2.0, we modeled the temperature at these same sites with local slopes and aspects for four years for the former and eight years for the latter region. Empirical and modeled air temperatures differed by 7.4 °C, on average, and soil temperatures differed less (4.4 °C, on average). Site-specific additions of hill shading at 25 m distance or soil parameters did not improve the agreement of the empirical and modeled temperatures. A hybrid model for air temperature that incorporated soil temperature at 0 cm depth when snow depth exceeded 3 cm resulted in an average improvement of 8% that was as great as 31%. Understanding biological processes at the regional scale and in projected future climates will continue to require biophysical modeling. To achieve the widest applications possible, biophysical models such as NichMapR need to be validated with empirical data from as wide a variety of altitudes, latitudes, soil types, and topographies wherein organisms currently inhabit and where their ranges might expand to in the future.
]]>Geographies doi: 10.3390/geographies3020017
Authors: Natalia Blana Ioannis Kavadas Lysandros Tsoulos
Automation in map production has created the need for modeling the map composition process. Generalization is the most critical process in map composition, with considerable impact on the quality of features portrayed on the maps. Modeling of the generalization process has been an area of research for several years in the international cartographic community. Constraint-based generalization modeling prevailed, and it is evolving to an agent model or to other optimization models. The generalization model presented in this paper is based on constraint-based modeling. It introduces the standardization of the semantic and cartographic generalization process together with an evaluation mechanism for the assessment of the quality of the resulting cartographic data considering simultaneously the preservation of the shape of the portrayed linear and area features. For cartographers, quality management is a key factor in creating an evidence-based, reliable product. To achieve this objective, cartographers, drawing on international experience, should implement a quality policy and adopt a quality management system (QMS) as an integral part of the map production process, starting with the quality assessment of the input data and finishing with the evaluation of the final product.
]]>Geographies doi: 10.3390/geographies3020016
Authors: Fuyu Xu Kate Beard
Examining the similarity of event environments or surroundings—more precisely, settings—provides additional insight in analyzing event sequences, as it provides information about the context and potential common factors that may have influenced them. This article proposes a new similarity measure for event setting sequences, which involve the space and time in which events occur. While similarity measures for spatiotemporal event sequences have been studied, the settings and setting sequences have not yet been studied. While modeling event setting sequences, we consider spatial and temporal scales to define the bounds of the setting and incorporate dynamic variables alongside static variables. Using a matrix-based representation and an extended Jaccard index, we developed new similarity measures that allow for the use of all variable data types. We successfully used these similarity measures coupled with other multivariate statistical analysis approaches in a case study involving setting sequences and pollution event sequences associated with the same monitoring stations, which validate the hypothesis that more similar spatial-temporal settings or setting sequences may generate more similar events or event sequences. In conclusion, the developed similarity measures have wide application beyond the case study to other disciplinary contexts and geographical settings. They offer researchers a powerful tool for understanding different factors and their dynamics corresponding to occurrences of spatiotemporal event sequences.
]]>Geographies doi: 10.3390/geographies3020015
Authors: Nathaniel R. Geyer Eugene J. Lengerich
In 2018, the Penn State Cancer Institute developed LionVu, a web mapping tool to educate and inform community health professionals about the cancer burden in Pennsylvania and its catchment area of 28 counties in central Pennsylvania. LionVu, redesigned in 2023, uses several open-source JavaScript libraries (i.e., Leaflet, jQuery, Chroma, Geostats, DataTables, and ApexChart) to allow public health researchers the ability to map, download, and chart 21 publicly available datasets for clinical, educational, and epidemiological audiences. County and census tract data used in choropleth maps were all downloaded from the sources website and linked to Pennsylvania and catchment area county and census tract geographies, using a QGIS plugin and Leaflet JavaScript. Two LionVu demonstrations are presented, and 10 other public health related web-GIS applications are reviewed. LionVu fills a role in the public health community by allowing clinical, educational, and epidemiological audiences the ability to visualize and utilize health data at various levels of aggregation and geographical scales (i.e., county, or census tracts). Also, LionVu is a novel application that can translate and can be used, for mapping and graphing purposes. A dialog to demonstrate the potential value of web-based GIS to a wider audience, in the public health research community, is needed.
]]>Geographies doi: 10.3390/geographies3020014
Authors: C. Emdad Haque Parnali Dhar-Chowdhury Shakhawat Hossain David Walker
In recent years, many urban areas in low and middle income countries have experienced major dengue epidemics, and the city of Dhaka, the capital city of Bangladesh, is one of them. Understanding models based on land cover and land use in urban areas in relation to vector abundance and possible disease transmission can be a major epidemiological tool in identifying disease incidence and prevalence. Demographic and human behavioral factors can also play a role in determining microenvironments for entomological distribution—which is a major risk factor for epidemicity. Data collected from a cross-sectional entomological survey in the city of Dhaka during the monsoon season of 2012 and two serological surveys—one pre-monsoon and another post-monsoon in 2012—were analyzed in this study. A total of 898 households and 1003 containers with water were inspected, and 1380 Ae. aegypti pupae and 4174 larvae were counted in these containers. All Stegomyia indices were found to be the highest in the central business and residential mixed zone. The odds ratios of risk factors for seroprevalence, including sex, age, self-reported febrile illness during the previous six months, and travel during the last six months, were calculated; age distribution was found to be a highly significant risk factor (p = value < 0.0001). The study offers clear patterns of dengue viral transmission, disease dynamics, and their association with critical spatial dimensions.
]]>Geographies doi: 10.3390/geographies3020013
Authors: Zixuan Tan Jinnian Wang Zhenyu Yu Yiyun Luo
Monitoring CO2 concentrations is believed to be an effective measure for assisting in the control of greenhouse gas emissions. Satellite measurements compensate for the sparse and uneven spatial distribution of ground observation stations, allowing for the collection of a wide range of CO2 concentration data. However, satellite monitoring’s spatial coverage remains limited. This study fills the knowledge gaps of column-averaged dry-air mole fraction of CO2 (XCO2) products retrieved from the Greenhouse Gases Observing Satellite (GOSAT) and Orbiting Carbon Observatory Satellite (OCO-2) based on the normalized output of atmospheric chemical models, WRF-Chem, in Southern China during 2010–2019. Hefei (HF)/Total Carbon Column Observing Network (TCCON), Lulin (LLN)/World Data Centre for Greenhouse Gases (WDCGG) station observations were used to validate the results of void filling with an acceptable accuracy for spatiotemporal analysis (R = 0.96, R2 = 0.92, RMSE = 2.44 ppm). Compared to the IDW (inverse distance weighting) and Kriging (ordinary Kriging) interpolation methods, this method has a higher validation accuracy. In addition, spatiotemporal distributions of CO2, as well as the sensitivity of CO2 concentration to the urban built-up areas and urban green space areas in China’s major southern cities during 2010–2019, are discussed. The approximate annual average concentrations have gradually increased from 388.56 to 414.72 ppm, with an annual growth rate of 6.73%, and the seasonal cycle presents a maximum in spring and a minimum in summer or autumn from 2010 to 2019. CO2 concentrations have a strong positive correlation with the impervious area to city area ratio, while anomaly values of the impervious area to urban green area ratio occurred in individual cities. The experimental findings demonstrate the viability of the study hypothesis that combines remote sensing data with the WRF-Chem model to produce a local area dataset with high spatial resolution and an extracted urban unit from statistical data.
]]>Geographies doi: 10.3390/geographies3020012
Authors: Christina W. Lopez Madeline T. Wade Jason P. Julian
A social–ecological system is a highly connected organization of biophysical and social actors that interact across multiple scales, share resources, and adapt to the actors’ changes. The ways in which humans and nature interact have traditionally been characterized and influenced by competing intrinsic and utilitarian values. However, recently, relational values and relational models have been used to unpack the myriad of values society assigns to nature and create general typologies of nature–human relationships. Here, we investigate the spectrum of environmental values that exist in the San Marcos River (SMR)—a social–ecological system (SES) in which a spring-fed river flows through an urban environment in central Texas (USA) including a university campus that attracts regional and international tourists. Recognizing that scholars have struggled to identify a nuanced understanding of environmental values and how these values shape nature–human relationships in SES, we use the SMR case study to capture the nature–human relational models that exist among social and user groups of the blue space. Analyzing different groups of visitors and stakeholders of the SMR (n = 3145), this study serves as a pilot to apply relational models using a variety of metrics to build a framework for understanding models of nature–human relationships, beyond ecosystem services and dualistic valuations. In our sample, most respondents were classified under the stewardship model (59%). The utilization model (34%) was the second most common, followed by wardship (6%). We found that patterns of place identity emerged to support the development of relational models beyond utilization. Despite the differences among perceptions, values, and some variation in relational models, one commonality was the innate, ubiquitous preference to protect natural habitat, water quality, and the river’s aquifer water source. Our study contributes to the growing literature around relational values and is a pathway to integrate ecosystem services, environmental values, and human–environment interactions into a more holistic approach to environmental valuation.
]]>Geographies doi: 10.3390/geographies3010011
Authors: Vladyslav Zakharovskyi Károly Németh
Hydrology is one of the most influential elements of geodiversity, where geology and geomorphology stand as the main values of abiotic nature. Hydrological erosion created by river systems destructing rock formations (eluvial process) from streams’ sources and then transporting and redepositing (alluvial process) the rock debris into the main river channels, make it an ongoing transformation element of the abiotic environment along channel networks. Hence, this manuscript demonstrates the influence of hydrological elements on geosite recognition, specifically for qualitative–quantitative assessment of geodiversity, which is based on a combination of geological and geomorphological values. In this concept, a stream system will be treated as an additional element. The basement area of the Manawatu Region has been utilized as the territory for the research of hydrological assessment. The region is in the southern part of the North Island of New Zealand and has relatively low geological and geomorphological values and diversity. The Strahler order parameter will be demonstrated as a hydrological element for geodiversity assessment. This parameter has been chosen as one of the most common and acceptable within geographical information system (GIS) environments. The result of this assessment compares the influences of Strahler order on qualitative–quantitative assessment of geodiversity and provides its drawbacks. Additionally, the places with high values will be considered for more accurate field observation to be nominated as potential geosites with an opportunity for geoeducational and geotouristic significance.
]]>Geographies doi: 10.3390/geographies3010010
Authors: Ikramul Hasan Weibo Liu Chao Xu
Inundation dynamics coupled with seasonal information is critical to study the wetland environment. Analyses based on remotely sensed data are the most effective means to monitor and investigate wetland inundation dynamics. For the first time, this study deployed an automated thresholding method to quantify and compare the annual inundation characteristics in dry and wet seasons in the Everglades, using Landsat imagery in Google Earth Engine (GEE). This research presents the long-term time series maps from 2002 to 2021, with a comprehensive spatiotemporal depiction of inundation. In this paper, we bridged the research gap of space-time analysis for multi-season inundation dynamics, which is urgently needed for the Everglades wetland. Within a GIS-based framework, we integrated statistical models, such as Mann–Kendall and Sen’s Slope tests, to track the evolutionary trend of seasonal inundation dynamics. The spatiotemporal analyses highlight the significant differences in wet and dry seasons through time and space. The stationary or permanent inundation is more likely to be distributed along the coastal regions (Gulf of Mexico and Florida Bay) of the Everglades, presenting a warning regarding their vulnerability to sea level rise.
]]>Geographies doi: 10.3390/geographies3010009
Authors: David S. Jones
Ethnogeology offers a longitudinal history of the formation of landscapes though the lens of First Nations Peoples. Significantly, it offers an insight into landscape change and geographical formation as consequence of geological events, climate shift (change), and consequential human resilience and adaptation strategies. This article considers a cultural landscape near Ballaarat (Ballarat) in Australia and its geological omnipresence in the eyes of the First Nations’ Wadawurrung People. The features, two extinct volcanoes—Bonan Youang (Mt Buninyong) and Terrinalum (Mt Elephant)—and a connection tract, offer high cultural values to the Wadawurrung People in addition to serving as key contemporary mental and orientation landmarks arising from their roles in the locality’s pastoral, goldmining, and suburbanisation colonisation phases.
]]>Geographies doi: 10.3390/geographies3010008
Authors: Sisi Han In-Hun Chung Yuhan Jiang Benjamin Uwakweh
This paper aims to explore and evaluate aerial imagery and deep learning technology in pavement condition evaluation. A convolutional neural network (CNN) model, named PCIer, was designed to process aerial images and produce pavement condition index (PCI) estimations, which are classified into four scales of Good (PCI ≥ 70), Fair (50 ≤ PCI < 70), Poor (25 ≤ PCI < 50), and Very Poor (PCI < 25). In the experiment, the PCI datasets were retrieved from the published pavement condition report by the City of Sacramento, CA. Following the retrieved datasets, the authors also collected the corresponding aerial image datasets containing 100 images for each PCI grade from Google Earth. An 80% proportion of datasets were used for PCIer model training, and the remaining were used for testing. Comparisons showed using a 128-channel heatmap layer in the proposed PCIer model and saving the PCIer model with the best validation accuracy would yield the best performance, with a testing accuracy of 0.97, and a weighted average precision, recall, and F1-score of 0.98, 0.97, and 0.97, respectively. Moreover, future research recommendations are provided in the discussion for improving the effectiveness of pavement evaluation via aerial imagery and deep learning.
]]>Geographies doi: 10.3390/geographies3010007
Authors: Geographies Editorial Office Geographies Editorial Office
High-quality academic publishing is built on rigorous peer review [...]
]]>Geographies doi: 10.3390/geographies3010006
Authors: Mohammad Al-Shaar Pierre-Charles Gérard Ghaleb Faour Walid Al-Shaar Jocelyne Adjizian-Gérard
Rockfall hazard gains popularity nowadays among researchers in different scientific fields, decision-makers and urban planners. The assessment of rockfall hazard requires detection, mapping and estimating the maximum travel distance that rock boulders may reach, commonly known as “rockfall runout”. This latter can change significantly under the effects of different triggering factors such as soil conditions, chemical, physical and geological rock properties. However, comparing and analyzing these different effects represents, to the best of our knowledge, one of the newest scientific challenges that need to be addressed. This paper presents a complete methodologic approach aiming to assess the rockfall hazard through runout estimation in three different conditions: (i) gravity, (ii) earthquakes, and (iii) the presence of moisture along the slope. The “Mtein” Village and its surrounding areas in the Mount Lebanon region were chosen as the study area because there have been numerous historic rockfalls and various-sized rocks, such as cobbles and boulders, scattered throughout the area. Thus, three-dimensional simulations were conducted using the Rockyfor3D software and aerial photos for the year 1999 to assess the rockfall runout, the energy curves, and the number of deposited rocks. The results reveal that earthquakes have the highest triggering effect on rockfall and that moisture has a damping effect on RFs by decreasing the kinetic energy. The study shows the importance of taking into consideration the influence of triggering factors as well as rock density on rockfall runout and hazard.
]]>Geographies doi: 10.3390/geographies3010005
Authors: Giuseppe Mancino Antonio Falciano Rodolfo Console Maria Lucia Trivigno
The present research aims at verifying whether there are significant differences between Land Use/Land Cover (LULC) classifications performed using Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data—abbreviated as L8 and S2. To comprehend the degree of accuracy between these classifications, both L8 and S2 scenes covering the study area located in the Basilicata region (Italy) and acquired within a couple of days in August 2017 were considered. Both images were geometrically and atmospherically corrected and then resampled at 30 m. To identify the ground truth for training and validation, a LULC map and a forest map realized by the Basilicata region were used as references. Then, each point was verified through photo-interpretation using the orthophoto AGEA 2017 (spatial resolution of 20 cm) as a ground truth image and, only in doubtful cases, a direct GPS field survey. MLC and SVM supervised classifications were applied to both types of images and an error matrix was computed using the same reference points (ground truth) to evaluate the classification accuracy of different LULC classes. The contribution of S2′s red-edge bands in improving classifications was also verified. Definitively, ML classifications show better performance than SVM, and Landsat data provide higher accuracy than Sentinel-2.
]]>Geographies doi: 10.3390/geographies3010004
Authors: Habitamu Alesew Ayele Alemu O. Aga Liuelsegad Belayneh Tilahun Wankie Wanjala
Information on land use and land cover modification and their related problems for the streamflow and sediment yield are crucial for spatial planners and stakeholders to devise suitable catchment resources management plans and strategies. This research sought to assess the changes in land use and land cover (LULC) effects on the streamflow and sediment yield of the Koga watershed. Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI data were used to create the land use and land cover maps. The LULC type identification analysis was performed by using ERDAS Imagine 2015. After the supervised classification, the land use and land cover maps for three distinct years (1991, 2008, and 2018) were generated, and the accuracy of the maps was reviewed. The LULC change analysis results were pointed out, as there was an appreciable LULC change in the study watershed. Agricultural land increased by 14.21% over the research period, whereas grassland decreased by 22.91%. The other LULC classes (built-up area, forest area, water body, and wetland) increased by 0.39%, 6.36%, 4.30%, and 0.46%, respectively. Contrarily, bushland decreased by 2.80%. Human activities were decisive in the significant land use alterations within the catchment. The flow rate of the river basin increased over the rainy season in the years 1991–2008 and declined in the drier months. The watershed’s sediment yield increased from 1991 to 2008 as a result of the extension of its agricultural area. Thus, the findings of this investigation demonstrated that the flow and sediment yield characteristics are changed because of the modifications within the LULC in the catchment. Some downstream and upstream parts of the area are exposed to comparatively high erosion, and the maximum amount of sediment is generated during the rainy season.
]]>Geographies doi: 10.3390/geographies3010003
Authors: Philip C. Hutton Elena A. Mikhailova Lili Lin Zhenbang Hao Hamdi A. Zurqani Christopher J. Post Mark A. Schlautman George B. Shepherd
Many climate change “solution” plans include net-zero goals, which involve balancing the anthropogenic greenhouse gas emissions (GHG) with their removal. Achieving net-zero goals is particularly problematic for soils because they are often excluded from GHG inventories and reduction plans. For example, Maryland’s Climate Solutions Now Act (Senate Bill 528) put forward the goal of lowering emissions of GHG to 60% under 2006 quantities by 2031 and with a target of net-zero emissions by 2045. To achieve these goals, the state of Maryland (MD) needs to quantify GHG emissions from various sources contributing to the state’s total emissions footprint (EF). Soils are currently excluded from MD’s GHG assessments, which raises a question about how the soil impacts the net-zero goal. This study examines the challenges in meeting net-zero goals using an example of carbon dioxide (CO2) as one of the GHG types (net-zero CO2 emissions). The current study quantified the “realized” social costs of CO2 (SC-CO2) emissions for MD from new land developments in the period from 2001 to 2016 which caused a complete loss of 2.2 × 109 kg of total soil carbon (TSC) resulting in $383.8M (where M = million, USD = US dollars). All MD’s counties experienced land developments with various emissions and SC-CO2 monetary values. Most of the developments, TSC losses, and SC-CO2 occurred near the existing urban areas of Annapolis and Baltimore City. These emissions need to be accounted for in MD’s GHG emissions reduction plans to achieve a net-zero target. Soils of MD are limited in recarbonization capacity because 64% of the state area is occupied by highly leached Ultisols. Soil recarbonization potential is further reduced by urbanization with Prince George’s, Montgomery, and Frederick counties experiencing the highest increases in developed areas. In addition, projected sea-level rises will impact 17 of MD’s 23 counties. These losses will generate additional social costs because of migration, costs of relocation, and damages to infrastructure. The state of MD has a high proportion of private land ownership (92.4%) and low proportion of public lands, which will limit opportunities for relocation within the state. Net-zero targets are important but meeting these targets without specific and integrative approaches depending on the source and type of emissions may result in failure. These approaches should also focus on the social costs of emissions, which raises the need for a new concept of integrating net-zero emissions and social costs.
]]>Geographies doi: 10.3390/geographies3010002
Authors: Fausto O. Sarmiento Nobuko Inaba Yoshihiko Iida Masahito Yoshida
The interdependence of biological and cultural diversity is exemplified by the new conservation paradigm of biocultural heritage. We seek to clarify obsolescent notions of nature, whereby cultural construction and identity markers of mountain communities need to reflect localized, situated, and nuanced understanding about mountainscapes as they are developed, maintained, managed, and contested in spatiality and historicity. Using the nexus of socioecological theory, we question whether a convergent approach could bridge montological knowledge systems of either different equatorial and temperate latitudes, western and eastern longitudes, hills and snow-capped mountain altitudes, or hegemonic and indigenous historicity. Using extensive literature research, intensive reflection, field observation, and critical discourse analysis, we grapple with the Nagoya Protocol of the Convention of Biological Diversity (COP 10, 2010) to elucidate the benefit sharing and linkages of biocultural diversity in tropical and temperate mountain frameworks. The result is a trend of consilience for effective conservation of mountain socioecological systems that reaffirms the transdisciplinary transgression of local knowledge and scientific input to implement the effective strategy of biocultural heritage conservation after the UN Decade of Biological Diversity. By emphasizing regeneration of derelict mountain landscapes, invigorated by empowered local communities, promoted by the Aspen Declaration, the UN Decade of Ecological Restoration, and the UN International Year of Mountain Sustainable Development, montological work on sustainable, regenerative development for 2030 can be expected.
]]>Geographies doi: 10.3390/geographies3010001
Authors: Paulo Ricardo Rufino Björn Gücker Monireh Faramarzi Iola Gonçalves Boëchat Francielle da Silva Cardozo Paula Resende Santos Gustavo Domingos Zanin Guilherme Mataveli Gabriel Pereira
The Amazon basin, the world’s largest river basin, is a key global climate regulator. Due to the lack of an extensive network of gauging stations, this basin remains poorly monitored, hindering the management of its water resources. Due to the vast extension of the Amazon basin, hydrological modeling is the only viable approach to monitor its current status. Here, we used the Soil and Water Assessment Tool (SWAT), a process-based and time-continuous eco-hydrological model, to simulate streamflow and hydrologic water balance in an Amazonian watershed where only a few gauging stations (the Jari River Basin) are available. SWAT inputs consisted of reanalysis data based on orbital remote sensing. The calibration and validation of the SWAT model indicated a good agreement according to Nash-Sutcliffe (NS, 0.85 and 0.89), Standard Deviation Ratio (RSR, 0.39 and 0.33), and Percent Bias (PBIAS, −9.5 and −0.6) values. Overall, the model satisfactorily simulated water flow and balance characteristics, such as evapotranspiration, surface runoff, and groundwater. The SWAT model is suitable for tropical river basin management and scenario simulations of environmental changes.
]]>Geographies doi: 10.3390/geographies2040046
Authors: Jobaed Ragib Zaman C. Emdad Haque David Walker
While there is a large body of literature focusing on global-level flood hazard management, including preparedness, response, and recovery, there is a lack of research examining the patterns and dynamics of community-level flood management with a focus on local engagement and institutional mechanism. The present research explores how local communities mobilize themselves, both individually and institutionally, to respond to emerging flood-related situations and recover from their impacts. A case study approach was applied to investigate two towns in the Red River Valley of Manitoba, Canada: St. Adolphe and Ste. Agathe. Data collection consisted of in-depth interviews and oral histories provided by local residents, in addition to analysis of secondary official records and documents. The findings revealed that local community-level flood preparedness, response, and recovery in the Province of Manitoba are primarily designed, governed, managed, and evaluated by the provincial government authorities using a top-down approach. The non-participatory nature of this approach makes community members reluctant to engage with precautionary and response measures, which in turn results in undesired losses and damages. It is recommended that the Government of Manitoba develop and implement a collaborative and participatory community-level flood management approach that draws upon the accumulated experiential knowledge of local stakeholders and institutions.
]]>Geographies doi: 10.3390/geographies2040045
Authors: Abhilash Singh M. Niranjannaik Shashi Kumar Kumar Gaurav
We evaluate the penetration depth of synthetic aperture radar (SAR) signals into the ground surface at different frequencies. We applied dielectric models (Dobson empirical, Hallikainen, and Dobson semi-empirical) on the ground surface composed of different soil types (sandy, loamy, and clayey). These models result in different penetration depths for the same set of sensors and soil properties. The Dobson semi-empirical model is more sensitive to the soil properties, followed by the Hallikainen and Dobson empirical models. We used the Dobson semi-empirical model to study the penetration depth of the upcoming NASA-ISRO synthetic aperture radar (NISAR) mission operated at the L-band (1.25 GHz) and the S-band (3.22 GHz) into the ground. We observed that depending upon the soil types, the penetration depth of the SAR signals ranges between 0 to 10 cm for the S-band and 0 to 25 cm for the L-band.
]]>Geographies doi: 10.3390/geographies2040044
Authors: Osvaldo Luiz Leal de Moraes
This article analyses a near-centennial time series of daily precipitation in the Metropolitan Region of São Paulo, Brazil, in order to quantify the detectable increase in intensity and/or frequency of extreme events. This area is the most populated in the southern hemisphere, and heavy or extreme precipitation events, mainly those related with hydro-meteorological disasters, have important effects on its society. Indexes derived from daily precipitation data through a simple methodological approach are able to quantify changes at decadal and annual time scales. The analysis was carried out for five thresholds, i.e., daily precipitation higher than 50, 60, 70, 80, and 90 mm. The indexes exhibited statistically trends in both precipitation intensity and frequency for all thresholds, indicating significant changes in daily extreme events in the study period.
]]>Geographies doi: 10.3390/geographies2040043
Authors: S. Abdul Rahaman S. Aruchamy
Nilgiri tea is a vital perennial beverage variety and is in high demand in global markets due to its quality and medicinal value. In recent years, the cultivation of tea plantations has decreased due to the extreme climate and prolonged practice of tea cultivation in the same area, decreasing its taste and quality. In this scenario, land suitability analysis is the best approach to evaluate the bio-physiochemical and ecological parameters of tea plantations. The present study aims to identify and delineate appropriate land best suited for the cultivation of tea within the Kallar watershed using the geographic information system (GIS) and multi-criteria evaluation (MCE) techniques. This study utilises various suitability criteria, such as soil (texture, hydrogen ion concentration, electrical conductivity, depth, base saturation, and drainability), climate (rainfall and temperature), topography (relief and slope), land use, and the normalised difference vegetation index (NDVI), to evaluate the suitability of the land for growing tea plantations based on the Food and Agricultural Organization (FAO) guidelines for rainfed agriculture. The resultant layers were classified into five suitability classes, including high (S1), moderate (S2), and marginal (S3) classes, which occupied 16.7%, 7.08%, and 16.3% of the land, whereas the currently and permanently not suitable (N1 and N2) classes covered about 18.52% and 29.06% of the total geographic area. This study provides sufficient insights to decision-makers and farmers to support them in making more practical and scientific decisions regarding the cultivation of tea plantations that will result in the increased production of quality tea, and prevent and protect human life from harmful diseases.
]]>Geographies doi: 10.3390/geographies2040042
Authors: Gurwinder Singh Sartajvir Singh Ganesh Sethi Vishakha Sood
Continuous observation and management of agriculture are essential to estimate crop yield and crop failure. Remote sensing is cost-effective, as well as being an efficient solution to monitor agriculture on a larger scale. With high-resolution satellite datasets, the monitoring and mapping of agricultural land are easier and more effective. Nowadays, the applicability of deep learning is continuously increasing in numerous scientific domains due to the availability of high-end computing facilities. In this study, deep learning (U-Net) has been implemented in the mapping of different agricultural land use types over a part of Punjab, India, using the Sentinel-2 data. As a comparative analysis, a well-known machine learning random forest (RF) has been tested. To assess the agricultural land, the major winter season crop types, i.e., wheat, berseem, mustard, and other vegetation have been considered. In the experimental outcomes, the U-Net deep learning and RF classifiers achieved 97.8% (kappa value: 0.9691) and 96.2% (Kappa value: 0.9469), respectively. Since little information exists on the vegetation cultivated by smallholders in the region, this study is particularly helpful in the assessment of the mustard (Brassica nigra), and berseem (Trifolium alexandrinum) acreage in the region. Deep learning on remote sensing data allows the object-level detection of the earth’s surface imagery.
]]>Geographies doi: 10.3390/geographies2040041
Authors: Elena A. Mikhailova Lili Lin Zhenbang Hao Hamdi A. Zurqani Christopher J. Post Mark A. Schlautman Gregory C. Post George B. Shepherd
Conflicts of interest (COI) are an integral part of human society, including their influence on greenhouse gas (GHG) emissions and climate change. Individuals or entities often have multiple interests ranging from financial benefits to reducing climate change-related risks, where choosing one interest may negatively impact other interests and societal welfare. These types of COI require specific management strategies. This study examines COI from land-use decisions as an intersection of different perspectives on land use (e.g., land conservation versus land development), which can have various consequences regarding GHG emissions. This study uses the state of New Jersey (NJ) in the United States of America (USA) as a case study to demonstrate COI related to soil-based GHG emissions from land conversions between 2001 and 2016 which caused $722.2M (where M = million = 106) worth of “realized” social costs of carbon dioxide (SC-CO2) emissions. These emissions are currently not accounted for in NJ’s total carbon footprint (CF), which can negatively impact the state’s ability to reach its carbon reduction goals. The state of NJ Statutes Annotated 26:2C-37 (2007): Global Warming Response Act (GWRA) (updated in 2019) set a statewide goal of reducing GHG emissions to 80 percent below 2006 levels by 2050. Remote sensing and soil data analysis allow temporal and quantitative assessment of the contribution of land cover conversions to NJ’s CF by soil carbon type, soil type, land cover type, and administrative units (state, counties), which helps document past, and estimate future related GHG emissions using a land cover change scenario to calculate the amount of GHG emissions if an area of land was to be developed. Decisions related to future land conversions involve potential COI within and outside state administrative structures, which could be managed by a conflict-of-interest policy. The site and time-specific disclosures of GHG emissions from land conversions can help governments manage these COI to mitigate climate change impacts and costs by assigning financial responsibility for specific CF contributions. Projected sea-level rise will impact 16 out of 21 NJ’s counties and it will likely reach coastal areas with densely populated urban areas throughout NJ. Low proportion of available public land limits opportunities for relocation. Increased climate-change-related damages in NJ and elsewhere will increase the number of climate litigation cases to alleviate costs associated with climate change. This litigation will further highlight the importance and intensity of different COI.
]]>Geographies doi: 10.3390/geographies2040040
Authors: Jasper Knight
Sand grains are ubiquitous in the Earth’s system, and are found in different environmental settings globally, but sand itself as a physical object has multiple conflicting meanings with respect to both its agglomeration into landforms such as sand dunes and beaches, and how sand and its dynamics have cultural significance and meaning. This study takes a transdisciplinary approach towards examining the multiple meanings of sand, focusing on sand as a spatiotemporal pheneomenon that exists in different contexts within the Earth system. The nature and spatiotemporalities of sand are framed in this study through the concepts of presence, absence and transience, which are key interpretive approaches that lie at the interface of how the physical and phenomenological worlds interact with each other. This is a new and innovative approach to understanding people–environment relationships. These concepts are then discussed using the examples of the dynamics of and values ascribed to desert dune and sandy beach landscapes, drawn from locations globally. These examples show that the dynamic geomorphic changes taking place in sand landscapes (sandscapes) by erosion and deposition (determining the presence and absence of sand in such landscapes) pose challenges for the ways in which people make sense of, locate, interact with and value these landscapes. This uncertainty that arises from constant change (the transience of sandscapes) highlights the multiple meanings that sandscapes can hold, and this represents the comforting yet also unsettling nature of sand, as a vivid symbol of human–Earth relationships.
]]>Geographies doi: 10.3390/geographies2040039
Authors: Luis Valderrama-Landeros Francisco Flores-Verdugo Francisco Flores-de-Santiago
Tropical sandy beaches provide essential ecosystem services and support many local economies. In recent times, however, there has been a massive infrastructure expansion in popular tourist destinations worldwide. To investigate the shoreline variability at a popular tourist destination in Mexico, we used the novel semi-automatic CoastSat program (1980 to 2020) and the climate dataset ERA5 (wave energy and direction). We also measured the beach cross-shore distance and the foredune height with topographic surveys. The results indicate that the section of real estate seafront infrastructure in the study site presents a considerable shoreline erosion due to the fragmentation between the foredune ridge and the beach berm, based on the in situ transects. Moreover, foredune corridors with cross-shore distances of up to 70 to 90 m and dune heights of 8 m, can be seen in the short unobstructed passages between buildings. In the south section we found the coastline in a much more stable condition because this area has not had coastal infrastructures, as of yet. For the most part, the remote sensing analysis indicates constant erosion since 1990 in the real estate section (mainly seafront hotels) and an overall accretion pattern at the unobstructed beach-dune locations. This study demonstrates the catastrophic consequences of beach fragmentation due to unplanned real estate developments, by combining in situ surveys and a freely available big-data approach (CoastSat).
]]>Geographies doi: 10.3390/geographies2040038
Authors: Pedro Rogerio Giongo Ana Paula Aparecida de Oliveira Assis Marcos Vinícius da Silva Abelardo Antônio de Assunção Montenegro José Henrique da Silva Taveira Adriana Rodolfo da Costa Patrícia Costa Silva Angelina Maria Marcomini Giongo Héliton Pandorfi Alessandro José Marques Santos Clarice Backes Maria Beatriz Ferreira Jhon Lennon Bezerra da Silva
The Brazilian Cerrado biome provides relevant ecosystem services for Brazil and South America, being strategic for the planning and management of water resources as well as for agribusiness. The objective was to evaluate the water quality along the course of the Córrego da Formiga in a virgin portion of the Brazilian Cerrado, the relationship of land use with physical-chemical and biological parameters of the water, and the inflow of the tributary. Five water collection points were defined (between the source and mouth) and observed on a quarterly scale in 2015, water samples were collected and analyzed for physical-chemical and biological parameters in the laboratory, and flow measurements were performed at the same point and day of water collection. To identify and quantify land use and land cover (LULC) in the watershed, an image from the Landsat8-OLI satellite was obtained, and other geomorphological data from hypsometry (Topodata-INPE) were obtained to generate the slope, basin delimitation, and contribution area for each water collection point. The LULC percentages for each area of contribution to the water collection points were correlated with the physical-chemical and biological parameters of the water and submitted to multivariate analysis (PLS-DA) for analysis and grouping among the five analyzed points. Changes in water-quality patterns were more pronounced concerning the time when the first and last sampling was performed (rainy period) and may be influenced by the increase in the volume of water in these periods. The stream flow is highly variable over time and between points, with the lowest recorded flow being 0.1 L s−1 (P1) and the highest being 947.80 L s−1 (P5). Córrego da Formiga has class III water quality (CONAMA resolution 357), which characterizes small restrictions on the use of water for multiple uses. The soil cover with native vegetation is just over 12%, while the predominance was of the classes of sugar cane (62.42%) and pasture (19.33%). The PLS-DA analysis allowed separating the water analysis points between P1, P2, P3, and P5, while P4 was superimposed on others. It was also possible to verify that the parameters that weighed the most for this separation of water quality were pH, alkalinity_T, alkalinity_h, calcium, and hardness, all with a tendency to increase concentration from the source (P1) to the mouth (P5). As for water quality, it was also possible to verify that points P2 and P5 presented better water-quality conditions.
]]>Geographies doi: 10.3390/geographies2040037
Authors: Vladyslav Zakharovskyi Károly Németh
In qualitative–quantitative assessment of geodiversity, geomorphology describes landscape forms suggesting specific locations as geosites. However, all digital elevation models (DEM) contain information only about altitude and coordinate systems, which are not enough data for inclusion assessments. To overcome this, researchers may transform altitude parameters into a range of different models such as slope, aspect, plan, and profile curvature. More complex models such as Geomorphon or Topographic Position Index (TPI) may be used to build visualizations of landscapes. All these models are rarely used together, but rather separately for specific purposes—for example, aspect may be used in soil science and agriculture, while slope is considered useful for geology and topography. Therefore, a qualitative–quantitative assessment of geodiversity has been developed to recognize possible geosite locations and simplify their search through field observation and further description. The Coromandel Peninsula have been chosen as an area of study due to landscape diversity formed by Miocene–Pleistocene volcanism which evolved on a basement of Jurassic Greywacke and has become surrounded and partially covered by Quaternary sediments. Hence, this research provides a comparison of six different models for geomorphological assessment. Models are based on DEM with surface irregularities in locations with distinct elevation differences, which can be considered geosites. These models have been separated according to their parameters of representations: numerical value and types of landscape. Numerical value (starting at 0, applied to the area of study) models are based on slope, ruggedness, roughness, and total curvature. Meanwhile, Geomorphon and TPI are landscape parameters, which define different types of relief ranging from stream valleys and hills to mountain ranges. However, using landscape parameters requires additional evaluation, unlike numerical value models. In conclusion, we describe six models used to calculate a range of values which can be used for geodiversity assessment, and to highlight potential geodiversity hotspots. Subsequently, all models are compared with each other to identify differences between them. Finally, we outline the advantages and shortcomings of the models for performing qualitative–quantitative assessments.
]]>Geographies doi: 10.3390/geographies2040036
Authors: Jhon Lennon Bezerra da Silva Daiana Caroline Refati Ricardo da Cunha Correia Lima Ailton Alves de Carvalho Maria Beatriz Ferreira Héliton Pandorfi Marcos Vinícius da Silva
Thematic maps of land cover and use can assist in the environmental monitoring of semiarid regions, mainly due to the advent of climate change, such as drought, and pressures from anthropic activities, such as the advance of urban areas. The use of geotechnologies is key for its effectiveness and low operating cost. The objective was to evaluate and understand the spatiotemporal dynamics of the loss and gain of land cover and use in a region of the Brazilian semiarid region, and identify annual trends from changing conditions over 36 years (1985 to 2020), using cloud remote sensing techniques in Google Earth Engine (GEE). Thematic maps of land cover and land use from MapBiomas Brazil were used, evaluated by Mann–Kendall trend analysis. The Normalized Difference Vegetation Index (NDVI) was also determined from the digital processing of about 800 orbital images (1985 to 2020) from the Landsat series of satellites. The trend analysis for land cover and use detected, over time, the loss of forest areas and water bodies, followed by the advance of exposed soil areas and urban infrastructure. The modification of native vegetation directly influences water availability, and agricultural activities increase the pressure on water resources, mainly in periods of severe drought. The NDVI detected that the period from 2013 to 2020 was most affected by climatic variability conditions, with extremely low average values. Thematic maps of land cover and use and biophysical indices are essential indicators to mitigate environmental impacts in the Brazilian semiarid region.
]]>Geographies doi: 10.3390/geographies2040035
Authors: Yu Wang Wenhui Wang Peng Li Xin Qi Wenbiao Hu
Thyroid cancer (TC) is the fastest growing cancer in China and has lots of influencing factors which can be intervened to reduce its incidence. In this article, we aimed to identify the risk factors of TC. The regional TC data in 2016 were obtained from the China Cancer Registry Annual Report published by the National Cancer Center (NCC). Univariate correlation analysis and generalized linear Poisson regression analysis were used to determine risk factors for morbidity of TC from the provincial and prefecture levels. High urbanization rate (UR) (RR = 1.109, 95%CI: 1.084, 1.135), high GDP per capita (PGDP) (RR = 1.013, 95%CI: 1.007, 1.018), high aquatic products (RR = 1.047, 95%CI: 1.020, 1.075) and dry and fresh fruit consumption (RR = 1.024, 95%CI: 1.007, 1.040) can increase TC incidence. Therefore, high PGDP, high UR, high aquatic products and dry and fresh fruit consumption were all risk factors for TC incidence. Our results may be helpful for providing analytical ideas and methodological references for the regionalized prevention and control of TC in a targeted manner.
]]>Geographies doi: 10.3390/geographies2040034
Authors: Dibyanti Danniswari Tsuyoshi Honjo Katsunori Furuya
Land surface temperature (LST) is heavily influenced by urban morphology. Building height is an important parameter of urban morphology that affects LST. Existing studies show contradicting results where building height can have a positive or negative relationship with LST. More studies are necessary to examine the impact of building height. However, high accuracy building height data are difficult to obtain on a global scale and are not available in many places in the world. Using the Digital Building Height Model (DBHM) calculated by subtracting the SRTM from AW3D30, this study analyzes the relationship between building height and Landsat LST in two cities: Tokyo and Jakarta. The relationship is observed during both cities’ warm seasons (April to October) and Tokyo’s cool seasons (November to February). The results show that building height and LST are negatively correlated. In the morning, areas with high-rise buildings tend to have lower LST than areas with low-rise buildings. This phenomenon is revealed to be stronger during the warm season. The LST difference between low-rise and mixed-height building areas is more significant than between mixed-height and high-rise building areas.
]]>Geographies doi: 10.3390/geographies2030033
Authors: Jiping Cao Hartwig H. Hochmair Fisal Basheeh
Social media data have been widely used to gain insight into human mobility and activity patterns. Despite their abundance, social media data come with various data biases, such as user selection bias. In addition, a change in the Twitter app functionality may further affect the type of information shared through tweets and hence influence conclusions drawn from the analysis of such data. This study analyzes the effect of three Twitter app policy changes in 2015, 2017, and 2019 on the tweeting behavior of users, using part of London as the study area. The policy changes reviewed relate to a function allowing to attach exact coordinates to tweets by default (2015), the maximum allowable length of tweet posts (2017), and the limitation of sharing exact coordinates to the Twitter photo app (2019). The change in spatial aspects of users’ tweeting behavior caused by changes in user policy and Twitter app functionality, respectively, is quantified through measurement and comparison of six aspects of tweeting behavior between one month before and one month after the respective policy changes, which are: proportion of tweets with exact coordinates, tweet length, the number of placename mentions in tweet text and hashtags per tweet, the proportion of tweets with images among tweets with exact coordinates, and radius of gyration of tweeting locations. The results show, among others, that policy changes in 2015 and 2019 led users to post a smaller proportion of tweets with exact coordinates and that doubling the limit of allowable characters as part of the 2017 policy change increased the number of place names mentioned in tweets. The findings suggest that policy changes lead to a change in user contribution behavior and, in consequence, in the spatial information that can be extracted from tweets. The systematic change in user contribution behavior associated with policy changes should be specifically taken into consideration if jointly analyzing tweets from periods before and after such a policy change.
]]>Geographies doi: 10.3390/geographies2030032
Authors: Milad Fakhari Jasmin Raymond Richard Martel Stephen J. Dugdale Normand Bergeron
In summer, salmonids can experience thermal stress during extreme weather conditions. This may affect their growth and even threaten their survival. Cool water zones in rivers constitute thermal refuges, allowing fish to be more comfortable to grow and survive in extreme events. Therefore, identifying and understanding the spatiotemporal variability of discrete thermal refuges and larger scale cooling zones in rivers is of fundamental interest. This study analyzes thermal refuges as well as cooling zones in two salmonid rivers in a subarctic climate by use of thermal infrared (TIR) imagery. The two studied rivers are the Koroc and Berard Rivers, in Nunavik, Quebec, Canada. On the 17 km studied section of the Berard River, four thermal refuges and five cooling zones were detected, covering 46% of the surveyed section of the river. On the 41 km section studied for the Koroc River, 67 thermal refuges and five cooling zones were identified which represent 32% of the studied section of the river. 89% of identified thermal refuges and about 60% of cooling zones are groundwater-controlled. Continuity of permafrost and shape of the river valley were found to be the main parameters controlling the distribution of refuges and cooling zones. These data provide important insights into planning and conservation measures for the salmonid population of subarctic Nunavik rivers.
]]>Geographies doi: 10.3390/geographies2030031
Authors: Elissavet Feloni Andreas Anayiotos Evangelos Baltas
Urban flooding can cause significant infrastructure and property damage to cities, loss of human life, disruption of human activities, and other problems and negative consequences on people and the local government administration. The objective of this research work is to investigate the relation between urban flood occurrence and potentially flood-triggering factors. The analysis is performed in the western part of Athens Basin (Attica, Greece), where over the past decades several flood events caused human losses and damages to properties and infrastructure. Flood impact is measured by the number of citizen calls for help to the emergency line of the fire service, while potentially influencing factors are several geomorphological characteristics of the area and hydrometeorological indices regarding storms, which were determined with the aid of GIS techniques. The analysis is based on the investigation on binary logistic regression and generalized linear regression models that are used to build relationships between the potentially flood-influencing factors and the flood occurrence/impact for three events that were selected for reasons of comparison. The entire analysis highlights the variations attributed to the consideration of different factors, events, as well as to the different cell size of the grid used in the analysis. Results indicate that, the binary logistic regression model performed for flood occurrence achieves higher predictability, compared to the ability of the model used to describe flood impact.
]]>Geographies doi: 10.3390/geographies2030030
Authors: Faith M. Hartley Aaron E. Maxwell Rick E. Landenberger Zachary J. Bortolot
This study investigates the mapping of forest community types for the entire state of West Virginia, United States, using Global Land Analysis and Discovery (GLAD) Phenology Metrics, Analysis Ready Data (ARD) derived from Landsat time series data, and digital terrain variables derived from a digital terrain model (DTM). Both classifications and probabilistic predictions were made using random forest (RF) machine learning (ML) and training data derived from ground plots provided by the West Virginia Natural Heritage Program (WVNHP). The primary goal of this study was to explore the use of globally consistent ARD for operational forest type mapping over a large spatial extent. Mean overall accuracy calculated from 50 model replicates for differentiating seven forest community types using only variables selected from the 188 GLAD Phenology Metrics used in the study resulted in an overall accuracy (OA) of 54.3% (map-level image classification efficacy (MICE) = 0.433). Accuracy increased to a mean OA of 64.8% (MICE = 0.496) when the Oak/Hickory and Oak/Pine classes were combined into an Oak Dominant class. Once selected terrain variables were added to the model, the mean OA for differentiating the seven forest types increased to 65.3% (MICE = 0.570), while the accuracy for differentiating six classes increased to 76.2% (MICE = 0.660). Our results highlight the benefits of combining spectral data and terrain variables and also the enhancement of the product’s usefulness when probabilistic predictions are provided alongside a hard classification. The GLAD Phenology Metrics did not provide an accuracy comparable to those obtained using harmonic regression coefficients; however, they generally outperformed models trained using only summer or fall seasonal medians and performed comparably to those trained using spring medians. We suggest further exploration of the GLAD Phenology Metrics as input for other spatial predictive mapping and modeling tasks.
]]>Geographies doi: 10.3390/geographies2030029
Authors: Vladyslav Zakharovskyi Károly Németh
Spatial scale in modeling is one of the most important aspects of any kind of assessment. This study utilized previously studied assessments of geodiversity through a qualitative–quantitative methodology for geosite recognition. Our methodology was developed based on geodiversity as a complex description of all elements of abiotic nature and processes, influencing it. Based on this definition, geodiversity can be divided into main elements: geology and geomorphology, creating a core of abiotic nature; and additional elements including hydrology, climate, and human influences. We include this description of geodiversity here to emphasize the data which were used in the assessment. The methodology was based on an evaluation system, subject to improvements informed by previous research, and map-based models showing the area of spreading of calculated elements. Except for additional changes in the assessment, this article primarily addresses the problem of scale, by comparing two different methods of scale in the research: grid and non-grid. Grid types of assessment are considered a widely useable method, requiring definitions of areas of research with a potential variety of polygons, and calculating elements inside the cell and applying values to each cell. In contrast, non-grid assessment utilizes the natural borders of all elements (e.g., map view pattern of geological formations), and including them in calculations. The union of layers from different elements creates shapes which highlight regions with the highest values. Hence, the goal of this article is to demonstrate differences between grid and non-grid assessments of geodiversity in Western Samoa. In our results, we compare the methods and emphasize specific tasks most suitable for each method.
]]>Geographies doi: 10.3390/geographies2030028
Authors: C. Emdad Haque Khandakar Hasan Mahmud David Walker
In the field of flood management, risk and loss estimation is a prerequisite to undertake precautionary measures. Among several available tools, the HAZUS model is one of the most effective ones that can assist in the analysis of different dimensions of natural hazards, such as earthquakes, hurricanes, floods, and tsunamis. The flood hazard analysis portion of the model characterizes the spatial variation of flood regimes for a given study area. This research attempts to illustrate how the geoinformatics tool HAZUS can help in estimating overall risk and potential loss and damage due to floods and how this knowledge can guide the decision-making process and enhance community resilience. Examining a case study in the Rural Municipality of St. Andrews in Manitoba, Canada, this study found that both the ‘Quick Look’ and ‘Enhanced Quick Look’ analyses provided robust results. However, for the RM of St. Andrews, which is characterized by differing levels of exposure on the floodplain, and where many new housing starts occur in high-risk flood zones, ‘Enhanced Quick Look’ with spatially explicit building stock is recommended. The case study of the RM of St. Andrews demonstrates that the HAZUS model can predict loss and damage with increasing magnitude of flooding depth. It is thus recognized that the risk and loss estimation tools can be effective means for future flood loss and damage reduction.
]]>Geographies doi: 10.3390/geographies2030027
Authors: Daniel Beene Su Zhang Christopher D. Lippitt Susan M. Bogus
Pan-sharpening is a pixel-level image fusion process whereby a lower-spatial-resolution multispectral image is merged with a higher-spatial-resolution panchromatic one. One of the drawbacks of this process is that it may introduce spectral or radiometric distortion. The degree to which distortion is introduced is dependent on the imaging sensor, the pan-sharpening algorithm employed, and the context of the scene analyzed. Studies that evaluate the quality of pan-sharpening algorithms often fail to account for changes in geographic context and are agnostic to any specific applications of an end user. This research proposes an evaluation framework to assess the effects of six widely used pan-sharpening algorithms on normalized difference vegetation index (NDVI) calculation in five contextually diverse geographic locations. Output image quality is assessed by comparing the empirical cumulative density function of NDVI values that are calculated by using pre-sharpened and sharpened imagery. The premise is that an effective algorithm will generate a sharpened multispectral image with a cumulative NDVI distribution that is similar to the pre-sharpened image. Research results revealed that, generally, the Gram–Schmidt algorithm introduces a significant degree of spectral distortion regardless of sensor and spatial context. In addition, higher-spatial-resolution imagery is more susceptible to spectral distortions upon pan-sharpening. Furthermore, variability in cumulative density of spectral information in fused images justifies the application of an analytical framework to assist users in selecting the most effective methods for their intended application.
]]>Geographies doi: 10.3390/geographies2030026
Authors: John M. Humphreys
Eastern equine encephalitis virus (EEEv) is an arthropod-borne virus and the causative agent of neurologic disease in humans, horses, poultry, and wildlife. Although EEEv is known to be transmitted in cycles involving avian hosts and ornithophilic mosquitoes, there is ongoing debate about the role avian-host phylodiversity plays in diluting or amplifying virus prevalence across geographic space and through time. This study leveraged seventeen years of non-human EEEv detections to quantify possible EEEv dilution and amplification effects in response to avian-host phylodiversity. In assessing EEEv and avian-host diversity relationships, comparisons were performed to illustrate how modeling decisions aimed at capturing spatial patterns, temporal trends, and space–time interactions impacted results and the interpretations drawn from those results. Principal findings indicated that increased avian phylodiversity promotes EEEv dilution across geographic space, but this dilution effect is scale-dependent and masked by amplification effects that occur through time. Findings further demonstrated that the decisions made when modeling complex spatiotemporal dynamics can readily contribute to contrasting statistical outcomes and results misinterpretation, even when arithmetic and mathematics are strictly correct.
]]>Geographies doi: 10.3390/geographies2030025
Authors: René Ulloa-Espíndola Elisa Lalama-Noboa Jenny Cuyo-Cuyo
Natural or anthropogenic urban vegetation is an important resource for urban planning, risk assessment, and sustainable development of a city. Quito is a megadiverse city due to its location and topography, but the socioeconomic diversity generates more contrasting conditions of certain behaviors and habits related to urban infrastructure. The contrasts of vegetation and green spaces in the different sectors of Quito also reflect the diversity of the city. This study examines the effects of socioeconomic conditions on the loss or increase of urban vegetation. The exploratory regression method (spatial) and logit model (non-spatial) were used to explain the socioeconomic effects on urban vegetation density at the level of urban parishes. On the one hand, the Normalized Difference Vegetation Index (NDVI) was calculated as the dependent variable based on the 2021 sentinel images. On the other hand, the independent variables were structured based on the socioeconomic level, the land valuation areas of Quito (AIVAS), and the quality of life index. This article contributes to establishing baseline information that helps structure the conditions, strategies, and investments to design and implement plans and programs for urban drainage, ecosystem benefits, and sustainable development in the city of Quito.
]]>Geographies doi: 10.3390/geographies2030024
Authors: Kenji Wada Günter Wallner Steven Vos
With the rapid growth of information technology and geographic information science, many map-based visualization applications for decision-making have been proposed. These applications are used in various contexts. Our study provides empirical evidence of how domain experts utilize map-based data visualization for generating insights into vitality with respect to health-related concepts. We conducted a study to understand domain experts’ knowledge, approach, and experience. Nine domain experts participated in the study, with three experts each from the fields of government, business, and research. The study followed a mixed-methods approach involving an online survey, open-ended tasks, and semi-structured interviews. For this purpose, a map-based data visualization application containing various vitality-related datasets was developed for the open-ended tasks. Our study confirms the importance of maps in this domain but also shows that vitality is strongly geographical. Furthermore, we found that map-based visualizations require multiple data sources and dimensions to enhance the utilization of them in the context of vitality. Therefore, our study suggests the necessity of a combination of multiple datasets as ‘vitality themes’ to efficiently communicate this particular subject to experts. As such, our results provide guidelines for designing map-based data visualizations that support the decision-making process across various domain experts in the field of vitality.
]]>Geographies doi: 10.3390/geographies2030023
Authors: Paolo Magliulo Sofia Sessa Angelo Cusano Marika Beatrice Alberto Giannini Filippo Russo
As highlighted by the EU Water Framework Directive from 2000, the hydromorphology of a stream, besides water quality and biological aspects, is one of the main elements to be evaluated to correctly assess its ecological state. Notwithstanding this, there are no such studies in peninsular Southern Italy. This study provides a contribution to filling this gap by assessing the morphological quality of one of the major rivers of this area, i.e., the Calore River, by using the IDRAIM method. The latter presents the advantage of taking into account the specific Italian context in terms of channel adjustments and human pressures, together with pre-existing geomorphological approaches developed in other countries. The method is based on data obtained by means of GIS analysis, remote sensing, and field survey. The analysis provided encouraging results, highlighting the good morphological quality of the Calore River. To maintain such quality, accurate monitoring of the human activities and/or careful planning of structures that could negatively affect the river’s morphological quality is unquestionably needed. The Calore River morphological quality seems to be controlled by artificiality rather than by the channel changes experienced since the 1950s. The results will be fundamental for already planned studies dealing with flood hazard and risk assessment.
]]>Geographies doi: 10.3390/geographies2020022
Authors: Michele Gatto Salvatore Misiano Lorella Montrasio
Most of the methods for landslide susceptibility assessment are based on mathematical relationships established between factors responsible for the triggering of the phenomenon, named the conditioning factors. These are usually derived from geographic data commonly handled through Geographical Information System (GIS) technology. According to the adopted methodology, after an initial phase conducted on the GIS platform, data need to be transferred to specific software, e.g., MATLAB, for analysis and elaboration. GIS-based risk management platforms are thus sometimes hybrid, requiring relatively complex adaptive procedures before exchanging data among different environments. This paper describes how MATLAB can be used to derive the most common landslide conditioning factors, by managing the geographic data in their typical formats: raster, vector or point data. Specifically, it is discussed how to build matrices of parameters, needed to assess susceptibility, by using grid cell mapping units, and mapping them bypassing GIS. An application of these preliminary operations to a study area affected by shallow landslides in the past is shown; results show how geodata can be managed as easily as in GIS, as well as being displayed in a fashionable way too. Moreover, it is discussed how raster resolution affects the processing time. The paper sets the future development of MATLAB as a fully implemented platform for landslide susceptibility, based on any available methods.
]]>Geographies doi: 10.3390/geographies2020021
Authors: Benjamin T. Fraser Christine L. Bunyon Sarah Reny Isabelle Sophia Lopez Russell G. Congalton
Unmanned Aerial Systems (UAS, UAV, or drones) have become an effective tool for applications in natural resources since the start of the 21st century. With their associated hardware and software technologies, UAS sensor data have provided high resolution and high accuracy results in a range of disciplines. Despite these achievements, only minimal progress has been made in (1) establishing standard operating practices and (2) communicating both the limitations and necessary next steps for future research. In this review of literature published between 2016 and 2022, UAS applications in forestry, freshwater ecosystems, grasslands and shrublands, and agriculture were synthesized to discuss the status and trends in UAS sensor data collection and processing. Two distinct conclusions were summarized from the over 120 UAS applications reviewed for this research. First, while each discipline exhibited similarities among their data collection and processing methods, best practices were not referenced in most instances. Second, there is still a considerable variability in the UAS sensor data methods described in UAS applications in natural resources, with fewer than half of the publications including an incomplete level of detail to replicate the study. If UAS are to increasingly provide data for important or complex challenges, they must be effectively utilized.
]]>Geographies doi: 10.3390/geographies2020020
Authors: Elena A. Mikhailova Lili Lin Zhenbang Hao Hamdi A. Zurqani Christopher J. Post Mark A. Schlautman Gregory C. Post
Greenhouse gas (GHG) emissions from landcover conversions contribute to the total carbon (C) footprint (CF), which is the sum of GHG emissions from various sources and events expressed as carbon dioxide (CO2) equivalent. Soil-based emissions from land conversions are often excluded from the total CF, which can lead to underreporting the CF. This study uses the state of Connecticut (CT) as a case study to demonstrate the importance of soil-based emissions from land cover conversions to the state’s CF. The state of CT Public Act 08-98 (2008): Global Warming Solutions Act (GWSA) set a statutory requirement to cut GHG emissions 10 percent below 1990 levels by 2020 and 80 percent below 2001 levels by 2050 without considering soil-based emissions from land conversions. This omission results in underestimates of past and current emissions related to CT’s CF. In addition, not accounting for soil-based emissions from land conversions may increase the future size of CT’s CF. Remote sensing and soil data analysis provide an opportunity for rapid, quantitative, and temporal assessment of the contribution of land cover conversions to CT’s CF by soil type, land cover type, and administrative units (counties). Results are reported for soil organic carbon (SOC), soil inorganic carbon (SIC), and total soil carbon (TSC) based on C contents and monetary values of social costs of carbon. The state of CT experienced soil-based emissions from land cover conversions from 2001 to 2016 with $388.1M (where $ = USD, M = million = 106) worth of “realized” social costs of carbon dioxide (SC-CO2) emissions which should be accounted for in CT’s total CF. The current methodology could be used to optimize future land conversions to minimize the amount of soil GHG emissions by considering the soil C resources in different development scenarios. With an extensive, densely populated coastal area, CT will be directly affected by rising sea levels and other climate change impacts. Future research can focus on owner-specific CF contributions to address the responsibility for costs of GHG emissions as well as limiting the CF impact of land conversions.
]]>Geographies doi: 10.3390/geographies2020019
Authors: Miljenko Lapaine Nedjeljko Frančula
Many books, textbooks and papers have been published in which the classification of map projections is based on auxiliary (developable) surfaces and projections are divided into conic, cylindrical and azimuthal projections. We argue that such a classification of map projections is unacceptable and give many reasons for that. Many authors wrote in more detail about the classification of map projections, and our intention is to give a new refined and rectified insight into the classification of map projections. Our approach can be included in map projection publications of general and thematic cartography. Doing this, misconceptions and unnecessary insistence on conceptuality instead of reality will be avoided.
]]>Geographies doi: 10.3390/geographies2020018
Authors: Natalia Blana Lysandros Tsoulos
This article elaborates on map-quality evaluation and assessment as a result of the generalization of geospatial data through the development of a methodology, which incorporates a quality data model including constraints. These constraints are used to guide the generalization process and they operate as requirements in quality controls applied for the quality evaluation and assessment of the resulting cartographic data. The quality model stores the required map specifications compiled as constraints, and provides quality measures along with new techniques for the evaluation and assessment of cartographic data quality. This secures the map composition process in each and every step and for all features involved, at any map scale. The methodology developed results in the creation of a scale-dependent cartographic database that contains exclusively the features to be portrayed on the map, generalized properly according to the map scale. It will reduce cartographers’ need to review each transformation throughout the map-composition process with considerable savings in time and money and, on the other hand, it will secure the quality of the final map. The formulation of the proposed methodology amalgamates generalization theory with the authors’ research in computer-assisted cartography, taking into account the work conducted on the topic by other researchers. In this study, the quality requirements, the measures and the associated techniques together with the results of the application of the proposed methodology for area and line features are described in detail to allow others to replicate and build on the presented results.
]]>Geographies doi: 10.3390/geographies2020017
Authors: Cornelis Stal Lars De Sloover Jeffrey Verbeurgt Alain De Wulf
The digital age has brought about an explosion in the growth of data, of which data with a geographical component stands out. Proper use of geographical data comes with the need for correct coordinate reference systems (CRSs). They are considered the ultimate binder for interoperability between geospatial data actors and stakeholders. Moreover, CRSs are crucial for the visual and analytical integration of geospatial data from disparate data sources. However, CRSs might be—for numerous reasons—incorrectly assigned or even missing. The result is a time-consuming study of the map, literature, and available resources to ultimately find the alleged right CRS. This study provides a summary of prevailing resources from national mapping agencies of some European countries to address the above problem. Secondly, and most importantly, is the development of an open-source Python-based software package. This software package aims to accurately estimate the best candidate CRS, given a tuple of coordinates at a priori an approximately known location. It is controlled by geocoding the known location and intersecting the resulting coordinate with the bounding box of all CRSs in the EPSG-database. An in-depth review of CRS tools by mapping authorities reveals, in particular, limitations concerning the countries’ spatial areas, in combination with often required know-how of local CRSs. To address these shortcomings, our tool is developed to enable a more generic extraction of CRSs for any given location worldwide. Testing proved successful for 30 different maps, with a grid present on the map and the CRS of the map being included in the EPSG-database.
]]>Geographies doi: 10.3390/geographies2020016
Authors: Mingke Li Heather McGrath Emmanuel Stefanakis
Recent research has extended conventional hydrological algorithms into a hexagonal grid and noted that hydrological modeling on a hexagonal mesh grid outperformed that on a rectangular grid. Among the hydrological products, flow routing grids are the base of many other hydrological simulations, such as flow accumulation, watershed delineation, and stream networks. However, most of the previous research adopted the D6 algorithm, which is analogous to the D8 algorithm over a rectangular grid, to produce flow routing. This paper explored another four methods regarding generating flow directions in a hexagonal grid, based on four algorithms of slope aspect computation. We also developed and visualized hexagonal-grid-based hydrological operations, including flow accumulation, watershed delineation, and hydrological indices computation. Experiments were carried out across multiple grid resolutions with various terrain roughness. The results showed that flow direction can vary among different approaches, and the impact of such variation can propagate to flow accumulation, watershed delineation, and hydrological indices production, which was reflected by the cell-wise comparison and visualization. This research is practical for hydrological analysis in hexagonal, hierarchical grids, such as Discrete Global Grid Systems, and the developed operations can be used in flood modeling in the real world.
]]>Geographies doi: 10.3390/geographies2020015
Authors: Esther Shupel Ibrahim Bello Ahmed Oludunsin Tunrayo Arodudu Jibril Babayo Abubakar Bitrus Akila Dang Mahmoud Ibrahim Mahmoud Halilu Ahmad Shaba Sanusi Bello Shamaki
Desertification has become one of the most pronounced ecological disasters, affecting arid and semi-arid areas of Nigeria. This phenomenon is more pronounced in the northern region, particularly the eleven frontline states of Nigeria, sharing borders with the Niger Republic. This has been attributed to a range of natural and anthropogenic factors. Rampant felling of trees for fuelwood, unsustainable agriculture, overgrazing, coupled with unfavourable climatic conditions are among the key factors that aggravate the desertification phenomenon. This study applied geospatial analysis to explore land use/land cover changes and detect major conversions from ecologically active land covers to sand dunes. Results indicate that areas covered by sand dunes (a major indicator of desertification) have doubled over the 25 years under consideration (1990 to 2015). Even though 0.71 km2 of dunes was converted to vegetation, indicative of the success of various international, national, local and individual afforestation efforts, conversely about 10.1 km2 of vegetation were converted to sand dunes, implying around 14 times more deforestation compared to afforestation. On average, our results revealed that the sand dune in the study area is progressing at a mean annual rate of 15.2 km2 annually. The land cover conversion within the 25-year study period was from vegetated land to farmlands. Comparing the progression of a sand dune with climate records of the study area and examining the relationship between indicators of climate change and desertification suggested a mismatch between both processes, as increasing rainfall and lower temperatures observed in 1994, 2005, 2012, and 2014 did not translate into positive feedbacks for desertification in the study area. Likewise, the mean annual Normalized Difference Vegetation Index (NDVI) from 2000 to 2015 shows a deviation between vegetation peaks, mean temperatures and rainfall. On average, our results reveal that the sand dune is progressing at a mean annual rate of about 15.2 km2 in the study area. Based on this study’s land cover change, trend and conversion assessment, visual reconciliation of climate records of land cover data, statistical analysis, observations from ground-truthing, as well as previous literature, it can be inferred that desertification in Nigeria is less a function of climate change, but more a product of human activities driven by poverty, population growth and failed government policies. Further projections by this study also reveal a high probability of more farmlands being converted to sand dunes by the years 2030 and 2045 if current practices prevail.
]]>Geographies doi: 10.3390/geographies2020014
Authors: Zaheer Allam David S. Jones Phillip Roös
The Conference of Parties (COP) 26 highlighted the need for global-level deep decarbonization and provided financial instruments to aid climate mitigation in the global south, as well as compensation avenues for loss and damage. This narrative reiterated the urgency of addressing climate change, as well as aiding advances in green products and green solutions whilst shifting a portion of responsibility upon the global south. While this is much needed, we argue that the science rhetoric driving this initiative continues to be advantageous to the global north due to their capacity to control consumption gaps and to access human knowledge and resource extraction. If not addressed, this will reinforce a continuing unjust north/south narrative, highlighting neo-climate colonialism precepts.
]]>Geographies doi: 10.3390/geographies2020013
Authors: Mykhailo Lohachov Nataliya Rybnikova
The efficient modeling of population-density and urban-extent dynamics is a precondition for monitoring urban sprawl and managing the accompanying conflicts. Currently, one of the most promising approaches in this field is cellular automata—spatial models allowing one to anticipate the behavior of unit areas (e.g., evolution or degradation) in response to the influence of their neighborhood. In the present study, the possibility of modeling the population-density and urban-extent dynamics via a cellular automaton with density-specific parameters is tested. Using an adaptive genetic algorithm, three key model parameters (the evolution and degradation thresholds of a cell and its impact upon the neighbors) are optimized to ensure minimal deviation of the model predictions from actual population dynamics data for 24 Ukrainian provinces during three subsequent time windows from 2010–2019. The performance of the obtained optimized models is assessed in terms of the ability to (1) predict population-density classes and (2) discriminate between urban and rural areas. Generally, the obtained optimized models show high performance for both population-density and urban-extent dynamics (with the average Cohen’s Kappa reaching ~0.81 and ~0.91, respectively). Rare cases with poor prediction accuracy usually represent politically and economically unstable Eastern Ukrainian provinces involved in the military conflict since 2014. Statistical analysis of the obtained model parameters reveals significant differences (p < 0.001) in all of them among population-density classes, arguing for the plausibility of the selected density-specific model architecture. Upon exclusion of the above-mentioned Eastern Ukrainian provinces, all model coefficients appear rather stable (p > 0.135) through the three analyzed time windows, indicating the robustness of the model. The ability of the model to discriminate between urban and rural areas depends on the population density threshold. The best correspondence between actual and predicted urban areas emerges upon the 3000 persons/km2 population-density threshold. Further improvement of the model seems possible via extending its input beyond the population density data alone, e.g., by accounting for the existing infrastructure and/or natural boundaries—known factors stimulating or inhibiting urban sprawl.
]]>Geographies doi: 10.3390/geographies2020012
Authors: Bambang H. Trisasongko Dyah R. Panuju Amy L. Griffin David J. Paull
This article explores a potential exploitation of fully polarimetric radar data for the management of rubber plantations, specifically for predicting tree circumference as a crucial information need for sustainable plantation management. Conventional backscatter coefficients along with Eigen-based and model-based decomposition features served as the predictors in models of tree girth using ten regression approaches. The findings suggest that backscatter coefficients and Eigen-based decomposition features yielded lower accuracy than model-based decomposition features. Model-based decompositions, especially the Singh decomposition, provided the best accuracies when they were coupled with guided regularized random forests regression. This research demonstrates that L-band SAR data can provide an accurate estimation of rubber plantation tree girth, with an RMSE of about 8 cm.
]]>Geographies doi: 10.3390/geographies2020011
Authors: Caitlin Dalla Pria Fiona Cawkwell Stephen Newton Paul Holloway
Herring gulls (Larus argentatus) are declining globally, but there are populations who are taking advantage of the new foraging and nesting opportunities afforded to them by urban landscapes. Nest-site selection (NSS) in urban environs is understudied, despite its critical role in supporting planning policy, biodiversity conservation and the management of human–wildlife conflict. The aim of this study was to assess the contribution of anthropogenic habitat features to NSS in urban populations of L. argentatus at different hierarchical levels in Fingal County, Ireland. We used generalised linear models with a logit function to investigate the relationship among nest sites, building features, street furniture (i.e., streetlights and refuse bins), landscape features, and presence of conspecifics at three different hierarchical levels, including the county, town, and colony levels. L. argentatus preferentially chose buildings that were closer to streetlights and food sources at the colony level, while avoiding streetlights when considered in isolation. Conspecific attraction at the county and colony levels indicated that individuals avoided neighbouring nest sites, yet this relationship was inverted at the town level, suggesting preference. Moreover, 75% of nests were within 30 m of each other (the average road width in the study area) when measured at the county level. Various relationships with different food sources were identified, suggesting within-population variation among preferences for nest sites. There appears to be a substantial population variation among preferences for nest sites, which does appear to be driven by the cross-scale decisions involved in nest-site selection.
]]>Geographies doi: 10.3390/geographies2010010
Authors: Glen Searle Siqin Wang Michael Batty Yan Liu
This paper considers whether existing approaches for quantifying variables in cellular automata (CA) modelling adequately incorporate all the relevant factors in typical actor decisions underpinning urban development. A survey of developers and planners is used to identify factors they incorporate to allow for or proceed with development, using South East Queensland as a reference region. Three types of decision factors are identified and ranked in order of importance: those that are already modelled in CA applications; those that are not modelled but are quantifiable; and those that are not (easily) quantifiable because they are subjective in nature. Factors identified in the second category include development height/scale, open space supply, and existing infrastructure capacity. Factors identified in the third category include political intent, community opposition, and lifestyle quality. Drawing on our analysis of these factors we suggest how and to what extent survey data might be used to address the challenges of incorporating actor variables into the CA modelling of urban change. The paper represents the first attempt to review what decision factors should be included in CA modelling, and how this might be enabled.
]]>Geographies doi: 10.3390/geographies2010009
Authors: Su Zhang Christopher D. Lippitt Susan M. Bogus Tammira D. Taylor Renee Haley
The construction industry relies on construction cost indexes to prepare cost estimate benchmarks and develop cost estimates. Subsequently, government agencies, non-profit organizations, and private companies routinely publish construction cost indexes for cities. Currently, all construction cost indexes are released in a tabular format for 649 cities across the conterminous United States, which is not effective in illustrating construction cost variations at the national level. This study explored the utility of various established interpolation methods and mapping techniques to visualize construction cost indexes at the national level. Geovisualization techniques such as thematic mapping provide a visual representation of construction cost data in addition to traditional tabular formats. This study explored the utility of Thiessen polygon and inverse distance weighted (IDW) methods to create thematic maps which can be used to interactively visualize construction costs at the national level. A qualitative comparison revealed that the IDW method can produce the most intuitive, interactive, and continuous surface maps to identify dynamic and previously unrecognized patterns. These continuous surface maps allow construction practitioners and academics, real estate developers, and the public to locate the geographic proximity of high or low construction costs while cost change maps allow investors and businesses to identify patterns in changing construction costs over a certain period. This work contributes to the body of knowledge by introducing interpolated maps for visualizing any construction cost-related indexes at a large scale such as the national level.
]]>Geographies doi: 10.3390/geographies2010008
Authors: Polixeni Iliopoulou Elissavet Feloni
In this article, geovisualization is used for the presentation and interpretation of spatial analysis results concerning several house attributes. For that purpose, point data for houses in the region of Attica, Greece are analyzed. The data concern houses for sale and comprise structural characteristics, such as size, age and floor, as well as locational attributes. Geovisualization of house characteristics is performed employing spatial interpolation techniques, kriging techniques, in particular. Spatial autocorrelation in the data is examined through the calculation of the Moran’s I coefficient, while spatial clusters of houses with similar characteristics are identified using the Getis-Ord Gi* local spatial autocorrelation coefficient. Finally, a model is developed in order to predict house prices according to several structural and locational characteristics. In that respect, a classic hedonic pricing model is constructed, which is consequently developed as a geographically weighted regression (GWR) model in a GIS environment. The results of this model indicate that two characteristics, i.e., size and age, account for most of the variability in house prices in the study region. Since GWR is a local model producing different regression parameters for each observation, it is possible to obtain the spatial distribution of the regression parameters, which indicate the significance of the house characteristics for price determination in different locations in the study area.
]]>Geographies doi: 10.3390/geographies2010007
Authors: Leda Stamou
Color occupies a prominent place in the bibliography of cartography, as it is an important element in the formation of cartographic symbolization. Apart from the technical issues of its application to maps, color theory is one of the elements that connect maps with art. In this paper various cartographic trends and their origins are examined and correlated with the artistic periods in which they were developed in order to investigate and document the extent to which maps follow the artistic movements and, particularly in the art of painting, concerning the form and the content of the maps and whether color can be used as an identification element of the art trend and the corresponding period. The research spans from the end of the Middle Ages to the 21st century and is referred spatially in Western Europe, including Italy. The comparison of colors is made in both descriptive and quantitative terms through the commentary of hue, brightness, and saturation, as well as through plotting them in the color wheel, a process that allows an overview of the range and location of color sequences. Concluding, the paintings and maps that were selected and examined in detail support the effect of painting on maps, without implying that it is intentional.
]]>Geographies doi: 10.3390/geographies2010006
Authors: Daniel Kpienbaareh Evans Sumabe Batung Isaac Luginaah
Protected areas (PAs) transform over time due to natural and anthropogenic processes, resulting in the loss of biodiversity and ecosystem services. As current and projected climatic trends are poised to pressurize the sustainability of PAs, analyses of the existing perturbations are crucial for providing valuable insights that will facilitate conservation management. In this study, land cover change, landscape characteristics, and spatiotemporal patterns of the vegetation intensity in the Kasungu National Park (area = 2445.10 km2) in Malawi were assessed using Landsat data (1997, 2008 and 2018) in a Fuzzy K-Means unsupervised classification. The findings reveal that a 21.12% forest cover loss occurred from 1997 to 2018: an average annual loss of 1.09%. Transition analyses of the land cover changes revealed that forest to shrubs conversion was the main form of land cover transition, while conversions from shrubs (3.51%) and bare land (3.48%) to forest over the two decades were comparatively lower, signifying a very low rate of forest regeneration. The remaining forest cover in the park was aggregated in a small land area with dissimilar landscape characteristics. Vegetation intensity and vigor were lower mainly in the eastern part of the park in 2018. The findings have implications for conservation management in the context of climate change and the growing demand for ecosystem services in forest-dependent localities.
]]>Geographies doi: 10.3390/geographies2010005
Authors: Paddington Hodza Kurtis A. Butler
Mapping ancient roads is crucial to tell credible geospatial stories about where, how, or why different people might have travelled or transported materials within and between places in the distant past. Achieving this process is challenging and commonly accomplished by means of archaeological and GIS methods and materials. It is not uncommon for different experts employing these methods to generate inconsistent delineations of the same ancient roads, creating confusion about how to produce knowledge and decisions based on multiple geospatial perspectives. This yet to be adequately addressed problem motivates our desire to enrich existing literature on the nature and extents of these differences. We juxtapose GIS and archaeologically generated road maps for northern Etruria, a region of ancient Italy with a well-developed road network built by the Etruscans and Romans. We reveal map differences through a map comparison approach that integrates a broad set of qualitative and quantitative measures plus geospatial concepts and strategies. The differences are evident in route locations, sinuosities, lengths, and complexities of the terrains on which the routes were set as defined by subtle variations in elevation, slope, and ruggedness. They ranged from 11.2–34.4 km in road length, 0–65.7 m in road relief, 1.0–13.5% in mean road grade, 0.07–0.79 in detour indices and 0.19–3.08 for mean terrain roughness indices, all of which can be considerable depending on application. Taken together, the measures proved effective in furthering our understanding of the range of possible disagreements between ancient linear features mapped by different experts and methods and are extensible for other application areas. They point to the importance of explicitly acknowledging and maintaining all usable perspectives in geospatial databases as well as visualization and analysis processes, regardless of levels of disagreement, and especially where ground-truth informed assessments cannot be reliably performed.
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