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Hazards, Disasters and Land Science toward Asian and Global SDGs...
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Hazards, Disasters and Land Science toward Asian and Global SDGs for Land Systems: Approaches from Remotely Sensed Geospatial Data Analyses

A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 22558

Special Issue Editors

Dr. Ram Avtar

E-Mail Website
Guest Editor
Graduate School of Environmental Science, Hokkaido University, Sapporo, Japan
Interests: UAV; earth observation and forestry
Special Issues, Collections and Topics in MDPI journals
Dr. Yunus P. Ali

E-Mail Website
Guest Editor
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China
Interests: GIS; remote sensing; geomorphology; geoscience; geography
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Teiji Watanabe

E-Mail Website
Guest Editor
Group of Environmental Geography, Section of Integrated Environmental Science, Faculty of Environmental Earth Science, Hokkaido University W-5, N-10, Sapporo 060-0810, Japan
Interests: mountain geoecology; landscape changes in high mountain areas; geodiversity; sustainable use and management in mountain protected areas/national parks; trail erosion in mountain areas
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Land is an epicenter for several natural and anthropogenic activities on the planet. Human-induced changes have consequences for the global environmental standards. The changes in agricultural patterns, shrinking forests resources, and expanding industrial townships have become a regular feature of the 21st century. These changes have taken an unprecedented route, threatening the sustainability of ecosystems, evidenced by the growing frequency of extreme weather events such as floods, droughts, cyclones, and landslides. The concepts of climate change adaptation and mitigation, and building community resilience under the template of sustainable development are inevitable options now. The role of geospatial data has been widely discussed to develop effective approaches to understand and monitor environmental transformations. The geospatial data, apart from establishing a baseline, also help with future projections and policy formulations. The recent advances in the field of space technology with hypersensitive data on time and location scales offer immense opportunities to explore land processes and their relationship with the increasing environmental challenges. This Special Issue will gather papers by interested experts worldwide and selected papers from the 3rd Global Land Programme (GLP) 2021 Asia Conference, which will be held in Sapporo, Japan on 14–17 September, 2021. The conference focuses on hazards, disasters, and Land Science for SDGs in the Asian and global contexts.

Papers selected for this Special Issue are subjected to a rigorous peer review procedure with the aim of rapid and wide dissemination of research results, developments, and applications in the environment.

Dr. Ram Avtar
Dr. Yunus P. Ali
Prof. Dr. Teiji Watanabe
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Opportunities and challenges of land use/cover mapping in the new remote sensing era
  • Geospatial data for terrestrial ecosystem monitoring
  • Rethinking and rejuvenating urban spaces along sustainability practices in Asia and other parts of the world
  • Environmental monitoring using cloud-based processing of remote sensing datasets
  • Connectivity and feedback of land systems across multiple temporal and spatial scales
  • Monitoring and evaluation of climate- and geo-related risk management

Published Papers (5 papers)

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Research

16 pages, 3098 KiB  
Article
Vegetation Dynamics Due to Urbanization in the Coastal Cities along the Maritime Silk Road
by Min Yan, Shunxiang Fan, Li Zhang, Riffat Mahmood, Bowei Chen and Yuqi Dong
Land 2022, 11(2), 164; https://doi.org/10.3390/land11020164 - 20 Jan 2022
Cited by 8 | Viewed by 2841
Abstract
Substantial research indicates the effects of urbanization on vegetation cover; however, a view of this scenario from a regional scale is absent. Nowadays, coastal cities have become the new engine for the development of countries in coastal areas. To capture the effects of [...] Read more.
Substantial research indicates the effects of urbanization on vegetation cover; however, a view of this scenario from a regional scale is absent. Nowadays, coastal cities have become the new engine for the development of countries in coastal areas. To capture the effects of rapid urbanization on vegetation dynamics, 35 coastal cities along the Maritime Silk Road (MSR) were selected to study the related research using quantitative tools. We calculated spatiotemporal trends of vegetation dynamics along an urban development intensity (UDI) gradient using the MODIS-enhanced vegetation index (EVI) during the period of 2000–2015. We found a significant reduction (p < 0.05) in the EVI in the core area against that in the rural area (ΔEVI) of 14 cities and an insignificant change in vegetation in the peri-urban areas or urban outskirts. EVI decreased significantly along the UDI gradients in 12 coastal cities with a linear pattern and in seven coastal cities with a concave pattern; only Bangkok exhibited a convex pattern. The nonlinear pattern between the EVI and UDI reflected the fact that vegetation dynamics were affected by complicated factors, including climate change and human interventions, over a long period of time. In conclusion, our work provided a scientific reference for the sustainable development of coastal cities along the MSR; further work is necessary to explore the mechanic details of the positive and negative influences of urban factors and related policies on vegetation conditions. Full article
(This article belongs to the Special Issue Hazards, Disasters and Land Science toward Asian and Global SDGs for Land Systems: Approaches from Remotely Sensed Geospatial Data Analyses)
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18 pages, 25312 KiB  
Article
Application of Risk Analysis in the Screening of Flood Disaster Hot Spots and Adaptation Strategies
by Er-Chiang Huang, Pei-Wen Li, Shao-Wei Wu and Chao-Yuan Lin
Land 2022, 11(1), 36; https://doi.org/10.3390/land11010036 - 26 Dec 2021
Viewed by 2789
Abstract
In recent years, Taiwan has established a sound flood control foundation in terms of river management. Due to climate change and land development, surface runoff has increased. In addition, the functions of flood control engineering facilities have their limits. Surface runoff cannot be [...] Read more.
In recent years, Taiwan has established a sound flood control foundation in terms of river management. Due to climate change and land development, surface runoff has increased. In addition, the functions of flood control engineering facilities have their limits. Surface runoff cannot be fully absorbed by rivers, and frequent floods still occur in some areas. According to the characteristics of water flowing along the terrain to low-lying land, the terrain features can be used to find out the hot areas prone to flooding and the appropriate location of flood storage space for improving flooding. On the basis of the natural terrain environment, the disaster risk framework is used to manage environmental complexity, and to carry out research on flood warning and governance decision-making systems, so that human beings can coexist with the uncertainty of flood risk. In this study, the Zhuoshuixi Basin was used as the sample area, the SCS-CN method was used to analyze the excess runoff, and the risk concept was used to establish a flood evaluation model. In addition, through the changes in land use, the SCS-CN method estimates the difference of potential maximum retention, quantifies the variation of excess rainfall in each watershed division, and uses the digital elevation model to calculate the depression site to analyze the relationship between the difference of potential maximum retention and the depression space of the watershed. The results show that the adaptation strategy for high-risk flooded areas should be strengthened, and areas with large water storage space and a small potential maximum retention difference can be the best location for offsite compensation. Full article
(This article belongs to the Special Issue Hazards, Disasters and Land Science toward Asian and Global SDGs for Land Systems: Approaches from Remotely Sensed Geospatial Data Analyses)
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20 pages, 7109 KiB  
Article
Impact of Industrial Pollution of Cadmium on Traditional Crop Planting Areas and Land Management: A Case Study in Northwest China
by Yu Song, Wenlong Li, Yating Xue, Huakun Zhou, Wenying Wang and Chenli Liu
Land 2021, 10(12), 1364; https://doi.org/10.3390/land10121364 - 10 Dec 2021
Cited by 2 | Viewed by 2183
Abstract
Cadmium in soils not only reduces crop yield and quality but also threatens the safety of human health and wildlife due to bioaccumulation. Baiyin City, a typical industrial region located in northwest China, was evaluated to examine the spatial distribution of cadmium. We [...] Read more.
Cadmium in soils not only reduces crop yield and quality but also threatens the safety of human health and wildlife due to bioaccumulation. Baiyin City, a typical industrial region located in northwest China, was evaluated to examine the spatial distribution of cadmium. We simulated soil cadmium concentrations in the laboratory, based on levels found at local sampling sites, to examine how both Medicago sativa and Zea mays plants accumulate cadmium. The experimental results revealed that cadmium in all soil samples exceeded China’s national standard levels for general farmland; in addition, cadmium accumulation in all tissues of M. sativa and Z. mays exceeded the national fodder standards. Therefore, M. sativa and Z. mays from the study area should not be used for fodder. However, about 36% of the planting area of M. sativa and Z. mays can be used for phytoextraction because of cadmium accumulation. For soil pollution management, we suggest dividing the study area into three different regions, including a non-planting region, a phytoremediation region, and a planting region. Our soil management model can effectively help local people to avoid food safety risks and to realize sustainable development of soil utilization in contaminated areas. Full article
(This article belongs to the Special Issue Hazards, Disasters and Land Science toward Asian and Global SDGs for Land Systems: Approaches from Remotely Sensed Geospatial Data Analyses)
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15 pages, 3567 KiB  
Article
Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform
by Aryo Adhi Condro, Yudi Setiawan, Lilik Budi Prasetyo, Rahmat Pramulya and Lasriama Siahaan
Land 2020, 9(10), 377; https://doi.org/10.3390/land9100377 - 08 Oct 2020
Cited by 14 | Viewed by 5833
Abstract
Indonesia has the most favorable climates for agriculture because of its location in the tropical climatic zones. The country has several commodities to support economics growth that are driven by key export commodities—e.g., oil palm, rubber, paddy, cacao, and coffee. Thus, identifying the [...] Read more.
Indonesia has the most favorable climates for agriculture because of its location in the tropical climatic zones. The country has several commodities to support economics growth that are driven by key export commodities—e.g., oil palm, rubber, paddy, cacao, and coffee. Thus, identifying the main commodities in Indonesia using spatially-explicit tools is essential to understand the precise productivity derived from the agricultural sectors. Many previous studies have used predictions developed using binary maps of general crop cover. Here, we present national commodity maps for Indonesia based on remote sensing data using Google Earth Engine. We evaluated a machine learning algorithm—i.e., Random Forest to parameterize how the area in commodity varied in Indonesia. We used various predictors to estimate the productivity of various commodities based on multispectral satellite imageries (36 predictors) at 30-meters spatial resolution. The national commodity map has a relatively high accuracy, with an overall accuracy of about 95% and Kappa coefficient of about 0.90. The results suggest that the oil palm plantation was the highest commodity product that occupied the largest land of Indonesia. However, this study also showed that the land area in rubber, rice paddies, and cacao commodities was underestimated due to its lack of training samples. Improvement in training data collection for each commodity should be done to increase the accuracy of the commodity maps. The commodity data can be viewed online (website can be found in the end of conclusions). This data can further provide significant information related to the agricultural sectors to investigate food provisioning, particularly in Indonesia. Full article
(This article belongs to the Special Issue Hazards, Disasters and Land Science toward Asian and Global SDGs for Land Systems: Approaches from Remotely Sensed Geospatial Data Analyses)
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26 pages, 12427 KiB  
Article
Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data
by Emmanouil Psomiadis, Andreas Papazachariou, Konstantinos X. Soulis, Despoina-Simoni Alexiou and Ioannis Charalampopoulos
Land 2020, 9(5), 133; https://doi.org/10.3390/land9050133 - 28 Apr 2020
Cited by 41 | Viewed by 7767
Abstract
The western part of Crete Island has undergone serious landslide events in the past. The intense rainfalls that took place in the September 2018 to February 2019 period provoked extensive landslide events at the northern part of Chania prefecture, along the motorway A90. [...] Read more.
The western part of Crete Island has undergone serious landslide events in the past. The intense rainfalls that took place in the September 2018 to February 2019 period provoked extensive landslide events at the northern part of Chania prefecture, along the motorway A90. Geospatial analysis methods and earth observation data were utilized to investigate the impact of the various physical and anthropogenic factors on landslides and to evaluate landslide susceptibility. The landslide inventory map was created based on literature, aerial photo analysis, satellite images, and field surveys. A very high-resolution Digital Elevation Model (DEM) and land cover map was produced from a dense point cloud and Earth Observation data (Landsat 8), accordingly. Sentinel-2 data were used for the detection of the recent landslide events and offered suitable information for two of them. Eight triggering factors were selected and manipulated in a GIS-based environment. A semi-quantitative method of Analytical Hierarchy Process (AHP) and Weighted Linear Combination (WLC) was applied to evaluate the landslide susceptibility index (LSI) both for Chania prefecture and the motorway A90 in Chania. The validation of the two LSI maps provided accurate results and, in addition, several susceptible points with high landslide hazards along the motorway A90 were detected. Full article
(This article belongs to the Special Issue Hazards, Disasters and Land Science toward Asian and Global SDGs for Land Systems: Approaches from Remotely Sensed Geospatial Data Analyses)
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