ISPRS International Journal of Geo-Information

Open AccessArticle

Synergy of Road Network Planning Indices on Central Retail District Pedestrian Evacuation Efficiency

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ISPRS Int. J. Geo-Inf. 2023, 12(6), 239; https://doi.org/10.3390/ijgi12060239 (registering DOI) - 09 Jun 2023

Abstract

Pedestrian evacuation is an important measure to ensure disaster safety in central retail districts, the efficiency of which is affected by the synergy of road network planning indices. This paper established the typical forms of central retail district (CRD) road networks in terms [...] Read more.

Pedestrian evacuation is an important measure to ensure disaster safety in central retail districts, the efficiency of which is affected by the synergy of road network planning indices. This paper established the typical forms of central retail district (CRD) road networks in terms of block form, network structure and road grade, taking China as an example. The experiment was designed using the orthogonal design of experiment (ODOE) method and quantified the evacuation time under different road network planning indices levels through the Anylogic simulation platform. Using range and variance analysis methods, the synergy of network density, network connectivity, road type and road width on pedestrian evacuation efficiency were studied from the perspectives of significance, importance and optimal level. The results showed that the type of CRD will affect the importance of network planning indices, and that the network connectivity is insignificant (P 0.477/0.581) in synergy; networks with wide pedestrian primary roads (30.1~40.0 m), medium secondary roads (3.1~5.0 m/side) and high density (11.0~13.0 km/km²) have the highest evacuation efficiency. From the perspective of evacuees, this paper put forward urban design implications on CRD road networks to improve their capacity for disaster prevention and reduction. Full article

(This article belongs to the Special Issue Human-Induced Disaster and Conflict Analysis, Prediction, and Prevention by Geospatial Analytics and Information Systems)

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Open AccessArticle

Archaeological Predictive Modeling Using Machine Learning and Statistical Methods for Japan and China

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Yuan Wang

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Xiaodan Shi

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Takashi Oguchi

ISPRS Int. J. Geo-Inf. 2023, 12(6), 238; https://doi.org/10.3390/ijgi12060238 - 07 Jun 2023

Abstract

Archaeological predictive modeling (APM) is an essential method for quantitatively assessing the probability of archaeological sites present in a region. It is a necessary tool for archaeological research and cultural heritage management. In particular, the predictive modeling process could help us understand the [...] Read more.

Archaeological predictive modeling (APM) is an essential method for quantitatively assessing the probability of archaeological sites present in a region. It is a necessary tool for archaeological research and cultural heritage management. In particular, the predictive modeling process could help us understand the relationship between past human civilizations and the natural environment; moreover, a better understanding of the mechanisms of the human–land relationship can provide new ideas for sustainable development. This study aims to investigate the impact of topographic and hydrological factors on archaeological sites in the Japanese archipelago and Shaanxi Province, China and proposes a hybrid integration approach for APM. This approach employed a conditional attention mechanism (AM) using deep learning and a frequency ratio (FR) model, in addition to a separate FR model and the widely-used machine learning MaxEnt method. The models’ outcomes were cross-checked using the four-fold cross-validation method, and the models’ performances were compared using the area under the receiver operating characteristic curve (AUC) and Kvamme’s Gain. The results showed that in both study areas, the AM_FR model exhibited the most satisfactory performances. Full article

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Open AccessArticle

The Use of ICTs to Support Social Participation in the Planning, Design and Maintenance of Public Spaces in Latin America

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Sergio Alvarado Vazquez

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Ana Mafalda Madureira

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Frank O. Ostermann

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Karin Pfeffer

ISPRS Int. J. Geo-Inf. 2023, 12(6), 237; https://doi.org/10.3390/ijgi12060237 - 07 Jun 2023

Abstract

Recent research indicates that information and communication technologies (ICTs) can support social participation in the planning, design and maintenance of public spaces (PDMPS), specifically to create comprehensive knowledge among different stakeholders. However, critics point out that the use of ICTs by planners and [...] Read more.

Recent research indicates that information and communication technologies (ICTs) can support social participation in the planning, design and maintenance of public spaces (PDMPS), specifically to create comprehensive knowledge among different stakeholders. However, critics point out that the use of ICTs by planners and decision-makers often ignores the needs of local residents. For this research, we inquired how ICTs can support social participation in PDMPS. Our case study combines a literature review and 21 semi-structured interviews with government officials, non-governmental organisations, academics and architecture/urban planning consultancy companies in Mexico to understand how different stakeholders use ICTs to improve the quality of public spaces. We developed an approach that facilitates the analysis of ICT aspects related to hardware and software supporting social participation in PDMPS. The findings show that Mexico has a base of digital tools requiring technical capacities and spatial literacy at various stages of PDMPS, and ICTs are seen as an opportunity to engage with residents. However, in practice, our interviewees mentioned that ICTs are rarely implemented to support participatory processes due to high costs, a lack of political support and the insufficient technical expertise of technical staff to engage with residents using ICTs. The paper closes with recommendations and suggestions for future research on how ICTs can better support participatory processes in PDMPS. Full article

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Open AccessArticle

Assessing the Status of National Spatial Data Infrastructure (NSDI) of Bangladesh

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Md. Mostafizur Rahman

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György Szabó

ISPRS Int. J. Geo-Inf. 2023, 12(6), 236; https://doi.org/10.3390/ijgi12060236 - 07 Jun 2023

Abstract

National spatial data infrastructure (NSDI) is an essential framework for managing and sharing geospatial data across different sectors and organizations. In Bangladesh, the development of NSDI is still in its early stages, and there are several challenges that need to be addressed to [...] Read more.

National spatial data infrastructure (NSDI) is an essential framework for managing and sharing geospatial data across different sectors and organizations. In Bangladesh, the development of NSDI is still in its early stages, and there are several challenges that need to be addressed to ensure its effective implementation. This paper provides a comprehensive assessment of the status of NSDI implementation in Bangladesh using Eelderink’s fourteen key variables. The paper examines the current state of NSDI implementation in Bangladesh, identifies strengths and weaknesses, and suggests recommendations for improvement. The findings suggest that while some progress has been made in establishing NSDI in Bangladesh, there are still significant challenges, such as limited funding; weak coordination among stakeholders; and a lack of skilled manpower, awareness, and capacity among users. To address these challenges, in this paper, we recommend several measures to improve the NSDI framework in Bangladesh. These include increasing funding support for NSDI development and maintenance, improving coordination among stakeholders through the establishment of a national coordinating body, enhancing awareness and capacity-building programs for NSDI users, and promoting the use of open data standards to improve data quality and interoperability. It is hoped that these recommendations will be taken into consideration by policymakers and other stakeholders to further enhance the development of NSDI in Bangladesh. Full article

Open AccessArticle

Reducing Redundancy in Maps without Lowering Accuracy: A Geometric Feature Fusion Approach for Simultaneous Localization and Mapping

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ISPRS Int. J. Geo-Inf. 2023, 12(6), 235; https://doi.org/10.3390/ijgi12060235 - 07 Jun 2023

Abstract

Geometric map features, such as line segments and planes, are receiving increasing attention due to their advantages in simultaneous localization and mapping applications. However, large structures in different environments are very likely to appear repeatedly in several consecutive time steps, resulting in redundant [...] Read more.

Geometric map features, such as line segments and planes, are receiving increasing attention due to their advantages in simultaneous localization and mapping applications. However, large structures in different environments are very likely to appear repeatedly in several consecutive time steps, resulting in redundant features in the final map. These redundant features should be properly fused, in order to avoid ambiguity and reduce the computation load. In this paper, three criteria are proposed to evaluate the closeness between any two features extracted at two different times, in terms of their included angle, feature circle overlapping and relative distance. These criteria determine whether any two features should be fused in the mapping process. Using the three criteria, all features in the global map are categorized into different clusters with distinct labels, and a fused feature is then generated for each cluster by means of least squares fitting. Two competing methods are employed for comparative verification. The comparison results indicate that using the commonly used KITTI dataset and the commercial software PreScan, the proposed feature fusion method outperforms the competing methods in terms of conciseness and accuracy. Full article

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Open AccessArticle

To What Extent Can Satellite Cities and New Towns Serve as a Steering Instrument for Polycentric Urban Expansion during Massive Population Growth?—A Comparative Analysis of Tokyo and Shanghai

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ISPRS Int. J. Geo-Inf. 2023, 12(6), 234; https://doi.org/10.3390/ijgi12060234 - 06 Jun 2023

Abstract

In response to the call of the New Urban Agenda—Habitat III for a reinvigoration of long-term and integrated planning towards sustainable urban development, this paper presents an empirical comparative study of planning practices based on the “satellite city” and “new town” concepts in [...] Read more.

In response to the call of the New Urban Agenda—Habitat III for a reinvigoration of long-term and integrated planning towards sustainable urban development, this paper presents an empirical comparative study of planning practices based on the “satellite city” and “new town” concepts in Tokyo and Shanghai to examine from a long-term perspective how well they have guided polycentric urban development at a time of massive population growth. We aim to deliver evidence-based contributions to boost the knowledge transfer between the Global North and the Global South. The paper adopts a multi-dimensional framework for the comparative analysis, including a review of long-term urban development policies and an inspection of the population distribution and extent of built-up areas using time-specific categorizations to map the spatiotemporal changes based on GHSL data. The comparative analysis shows that urban plans in Tokyo and Shanghai based on satellite cities and new towns as steering instruments for polycentric urban growth management have not lived up to the original aspirations. In fact, the intended steering of population distribution has essentially failed, despite the practical steps undertaken. Full article

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Open AccessArticle

Spatiotemporal Patterns Evolution of Residential Areas and Transportation Facilities Based on Multi-Source Data: A Case Study of Xi’an, China

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Xinyi Lai

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Chao Gao

ISPRS Int. J. Geo-Inf. 2023, 12(6), 233; https://doi.org/10.3390/ijgi12060233 - 06 Jun 2023

Abstract

The spatiotemporal patterns of residential and supporting service facilities are critical to effective urban planning. However, with growing urban sprawl and congestion, the spatial distribution patterns and evolutionary characteristics of these areas show significant uncertainty. This research was conducted for six phases from [...] Read more.

The spatiotemporal patterns of residential and supporting service facilities are critical to effective urban planning. However, with growing urban sprawl and congestion, the spatial distribution patterns and evolutionary characteristics of these areas show significant uncertainty. This research was conducted for six phases from 2012 to 2022, incorporating datasets of point of interest (POI) data for residential areas and transportation facilities (RATFs) and OpenStreetMap (OSM) data. Using exploratory spatial data analysis (ESDA) and standard deviation ellipse, we investigated the spatiotemporal patterns and directional characteristics of RATFs in Xi’an, as well as their evolution and underlying causes. The analysis demonstrated that: (1) The spatial distribution of RATFs in Xi’an exhibits non-uniform and gradually evolving patterns, with significant spatial agglomeration characteristics over the past decade. Residential areas (RAs) exhibit a spatial autocorrelation that is high in the middle and low in the surrounding areas, while transportation facilities (TFs) exhibit spatial patterns that are high in the southern and low in the northern areas. (2) Overall, the number of RATFs has continued to increase, and they exhibit significant spatial autocorrelation. Specifically, the trend of RAs concentrating in the central city has become increasingly prominent, while TFs have expanded from the center to the north. (3) Furthermore, from the perspective of supply–demand matching, this study proposes targeted adjustment strategies for the distribution of RATFs. It provides significant references for the optimization of service facilities and provides new ideas and practical experience for urban spatial analysis methods based on multi-source data. Full article

(This article belongs to the Special Issue Urban Geospatial Analytics Based on Crowdsourced Data)

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Open AccessArticle

An Earth Observation Framework in Service of the Sendai Framework for Disaster Risk Reduction 2015–2030

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ISPRS Int. J. Geo-Inf. 2023, 12(6), 232; https://doi.org/10.3390/ijgi12060232 - 06 Jun 2023

Abstract

The Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) proposed seven targets comprising 38 quantified indicators and various sub-indicators to monitor the progress of disaster risk and loss reduction efforts. However, challenges persist regarding the availability of disaster-related data and the required resources [...] Read more.

The Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) proposed seven targets comprising 38 quantified indicators and various sub-indicators to monitor the progress of disaster risk and loss reduction efforts. However, challenges persist regarding the availability of disaster-related data and the required resources to address data gaps. A promising way to address this issue is the utilization of Earth observation (EO). In this study, we proposed an EO-based disaster evaluation framework in service of the SFDRR and applied it to the context of tropical cyclones (TCs). We first investigated the potential of EO in supporting the SFDRR indicators, and we then decoupled those EO-supported indicators into essential variables (EVs) based on regional disaster system theory (RDST) and the TC disaster chain. We established a mapping relationship between the measurement requirements of EVs and the capabilities of EO on Google Earth Engine (GEE). An end-to-end framework that utilizes EO to evaluate the SFDRR indicators was finally established. The results showed that the SFDRR contains 75 indicators, among which 18.7% and 20.0% of those indicators can be directly and indirectly supported by EO, respectively, indicating the significant role of EO for the SFDRR. We provided four EV classes with nine EVs derived from the EO-supported indicators in the proposed framework, along with available EO data and methods. Our proposed framework demonstrates that EO has an important contribution to supporting the implementation of the SFDRR, and that it provides effective evaluation solutions. Full article

(This article belongs to the Topic Advances in Earth Observation and Geosciences)

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Open AccessArticle

Automatic Generation of 3D Indoor Navigation Networks from Building Information Modeling Data Using Image Thinning

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Weisong Zhang

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Yukang Wang

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Xiaoping Zhou

ISPRS Int. J. Geo-Inf. 2023, 12(6), 231; https://doi.org/10.3390/ijgi12060231 - 05 Jun 2023

Abstract

Navigation networks are a common form of indoor map that provide the basis for a wide range of indoor location-based services, intelligent tasks for indoor robots, and three-dimensional (3D) geographic information systems. The majority of current indoor navigation networks are manually modeled, resulting [...] Read more.

Navigation networks are a common form of indoor map that provide the basis for a wide range of indoor location-based services, intelligent tasks for indoor robots, and three-dimensional (3D) geographic information systems. The majority of current indoor navigation networks are manually modeled, resulting in a laborious and fallible process. Building Information Modeling (BIM) captures design information, allowing for the automated generation of indoor maps. Most existing BIM-based navigation systems for floor-level wayfinding rely on well-defined spatial semantics, and do not adapt well to buildings with irregular 3D shapes, which can make cross-floor path generation difficult. This research introduces an innovative approach to generating 3D indoor navigation networks automatically from BIM data using image thinning, which is referred to as GINIT. Firstly, GINIT extracts grid-based maps for floors from BIM data using only two types of semantics, i.e., slabs and doors. Secondly, GINIT captures cross-floor paths from building components by projecting 3D forms onto a 2D image, thinning the 2D image to capture the 2D projection path, and crossing over the 2D routes with 3D routes to restore the 3D path. Finally, to demonstrate the effectiveness of GINIT, experiments were conducted on three real-world multi-floor buildings, evaluating its performance across eight types of cross-layer architectural component. GINIT overcomes the dependency of space definitions in current BIM-based navigation network generation schemes by introducing image thinning. Due to the adaptability of navigation image thinning to any binary image, GINIT is capable of generating navigation networks from building components with diverse 3D shapes. Moreover, the current studies on indoor navigation network extraction mainly use geometry theory, while this study is the first to generate 3D indoor navigation networks automatically using image thinning theory. The results of this study will offer a unique perspective and foster the exploration of imaging theory applications of BIM. Full article

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Open AccessArticle

Cartographic Design and Processing of Originally Printed Historical Maps for Their Presentation on the Web

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Petra Justová

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Jiří Cajthaml

ISPRS Int. J. Geo-Inf. 2023, 12(6), 230; https://doi.org/10.3390/ijgi12060230 - 02 Jun 2023

Abstract

On the example of our project on the creation of the historical web atlas on Czech history, we introduce the process of adapting originally printed historical maps for their presentation in the web environment, which overcomes the shortcomings of standard approaches in similar [...] Read more.

On the example of our project on the creation of the historical web atlas on Czech history, we introduce the process of adapting originally printed historical maps for their presentation in the web environment, which overcomes the shortcomings of standard approaches in similar projects based on printed predecessors published only as zoomable scanned analogues or default GIS maps. To simplify the originally complex map and to increase the information potential of the maps, we propose seven different types of additional map functionality according to the specific characteristics of the original map content. In addition, we present a set of rules, principles, recommendations, and methods for the cartographic design and processing of originally printed historical maps that should be considered when they are prepared for presentation on the web, including the description of the specific visualisation processes for the proposed types of map functionality. The proposed complex methodology can be applied to similar projects focused on the conversion of originally printed maps to the web and may contribute to improving the quality of the visualisation and presentation of historical maps on the web in general. Full article

(This article belongs to the Special Issue Cartography and Geomedia)

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Open AccessArticle

Research on Spatial Patterns and Mechanisms of Live Streaming Commerce in China Based on Geolocation Data

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ISPRS Int. J. Geo-Inf. 2023, 12(6), 229; https://doi.org/10.3390/ijgi12060229 - 02 Jun 2023

Abstract

Live streaming commerce (LSC) effectively combines the traditional real economy and e-commerce. Based on more than half a million unique GIS data values on LSC activities sourced via Taobao (Alibaba), we traced the spatial distribution of different players along the supply chain and [...] Read more.

Live streaming commerce (LSC) effectively combines the traditional real economy and e-commerce. Based on more than half a million unique GIS data values on LSC activities sourced via Taobao (Alibaba), we traced the spatial distribution of different players along the supply chain and further highlighted the intermediary role of streamers in developing the inter-regional industry. This study guides industrial planning in a diversified regional context, especially in economically peripheral regions. Our results show the following outcomes: (1) in contrast to dispersed suppliers, streamers and consumers are highly clustered. This trend proves that streamers are rooted in a specific urban context while playing the role of an intermediary in inter-regional supply chains, effectively extending geographic interactivity between suppliers and (potential) customers. (2) LSC primarily promotes regional light industry, especially in economically peripheral and rural areas, and provides opportunities for rapid development in cities with skilled handicraft providers. (3) China’s LSC streams have a pyramid structure, and the top group is highly clustered in metropolitan regions, such as the Yangtze River Delta (YRD) and the Pearl River Delta (PRD). This clustering makes it easier for streamers to work with large, well-known brands. The bottom group is mainly in charge of expanding the supply chain within the region and relies more on the local industrial base. It is diversified due to the different types of businesses or products. Ultimately, we draw attention to adaptive spatial planning and resource allocation in the context of the economic and geographic reforms brought by this growing industry, and discuss the policy implications based on the relationships between the supply of and demand for live streamers from a broader regional perspective. Full article

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Open AccessArticle

The Spatial Effect of Accessibility to Public Service Facilities on Housing Prices: Highlighting the Housing Equity

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ISPRS Int. J. Geo-Inf. 2023, 12(6), 228; https://doi.org/10.3390/ijgi12060228 - 01 Jun 2023

Abstract

Understanding how public service accessibility is related to housing prices is crucial to housing equity, yet the heterogeneous capitalisation effect remains unknown. This study aims to investigate the spatial effect of public service accessibility on housing prices in rapidly urbanising regions. Here, we [...] Read more.

Understanding how public service accessibility is related to housing prices is crucial to housing equity, yet the heterogeneous capitalisation effect remains unknown. This study aims to investigate the spatial effect of public service accessibility on housing prices in rapidly urbanising regions. Here, we propose a novel methodological framework that integrates the hedonic price model, geographical detector model and the spatial association detector model to understand housing equity issues. The rapidly rising housing prices, vastly transformed urban planning and heterogeneous land use patterns make the urban centre of Wuhan a typical case study. High-value units of public service accessibility are concentrated in built-up areas, while low-value units are located at the urban fringe. The results indicate that larger public services have more significant clustering effects than smaller ones. Recreational, medical, educational and financial facilities all have capitalisation effects on housing prices. Both the geographical detector model and the spatial association detector model could identify the drivers of housing prices, but the explanatory power of the latter is greater and could enhance the validity and reliability of the findings. We further find that the explanatory power of the driving factors on housing prices obtained from the spatial association detector model is greater than that of the geographical detector model. Based on the spatial association detector model, the main drivers of public service facilities are accessibility to restaurants and bars and accessibility to ATMs. In addition, there are bivariate or nonlinear enhancement effects between each pair of driving factors. This approach provides significant insights for urban environmental development planning and local real estate planning. Full article

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Open AccessArticle

A Machine Learning Approach for Classifying Road Accident Hotspots

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Brunna de Sousa Pereira Amorim

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Anderson Almeida Firmino

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Cláudio de Souza Baptista

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Geraldo Braz Júnior

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Anselmo Cardoso de Paiva

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Francisco Edeverton de Almeida Júnior

ISPRS Int. J. Geo-Inf. 2023, 12(6), 227; https://doi.org/10.3390/ijgi12060227 - 31 May 2023

Abstract

Road accidents are a worldwide problem, affecting millions of people annually. One way to reduce such accidents is to predict risk areas and alert drivers. Advanced research has been carried out on identifying accident-influencing factors and potential highway risk areas to mitigate the [...] Read more.

Road accidents are a worldwide problem, affecting millions of people annually. One way to reduce such accidents is to predict risk areas and alert drivers. Advanced research has been carried out on identifying accident-influencing factors and potential highway risk areas to mitigate the number of road accidents. Machine learning techniques have been used to build prediction models using a supervised classification based on a labeled dataset. In this work, we experimented with many machine learning algorithms to discover the best classifier for the Brazilian federal road hotspots associated with severe or nonsevere accident risk using several features. We tested with SVM, random forest, and a multi-layer perceptron neural network. The dataset contains a ten-year road accident report by the Brazilian Federal Highway Police. The feature set includes spatial footprint, weekday and time when the accident happened, road type, route, orientation, weather conditions, and accident type. The results were promising, and the neural network model provided the best results, achieving an accuracy of 83%, a precision of 84%, a recall of 83%, and an F1-score of 82%. Full article

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Open AccessArticle

Controlling Traffic Congestion in Urbanised City: A Framework Using Agent-Based Modelling and Simulation Approach

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Raihanah Adawiyah Shaharuddin

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Md Yushalify Misro

ISPRS Int. J. Geo-Inf. 2023, 12(6), 226; https://doi.org/10.3390/ijgi12060226 - 31 May 2023

Abstract

Urbanised city transportation simulation needs a wide range of factors to reflect the influence of certain real-life events accurately. The vehicle composition and the timing of the traffic light signal scheduling play an important role in controlling the traffic flow and facilitate road [...] Read more.

Urbanised city transportation simulation needs a wide range of factors to reflect the influence of certain real-life events accurately. The vehicle composition and the timing of the traffic light signal scheduling play an important role in controlling the traffic flow and facilitate road users, particularly in densely populated urban cities. Since road capacity in urban cities changes throughout the day, an optimal traffic light signal duration might be different. Hence, in this paper, the effect of vehicle composition and traffic light phases on traffic flow during peak and off-peak hours in Georgetown, Penang, one of the highly populated cities in Malaysia, is investigated. Through Agent-Based Modelling (ABM), this complex system is simulated by integrating the driver’s behaviour into the model using the GIS and Agent-Based Modelling Architecture (GAMA) simulation platform. The result of predicted traffic flow varies significantly depending on the vehicle composition while the duration of the traffic signal timing has little impact on traffic flow during peak hours. However, during off-peak hour, it is suggested that 20 s duration of green light provides the highest flow compared to 30 s and 40 s duration of green light. This concludes that the planning for traffic light phasing should consider multiple factors since the vehicle composition and traffic light timing for an effective traffic flow varies according to the volume of road users. Full article

(This article belongs to the Special Issue Harnessing the Geospatial Data Revolution for Promoting Sustainable Transport Systems)

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Open AccessArticle

Exploring Crowd Travel Demands Based on the Characteristics of Spatiotemporal Interaction between Urban Functional Zones

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ISPRS Int. J. Geo-Inf. 2023, 12(6), 225; https://doi.org/10.3390/ijgi12060225 - 30 May 2023

Abstract

As a hot research topic in urban geography, spatiotemporal interaction analysis has been used to detect the hotspot mobility patterns of crowds and urban structures based on the origin-destination (OD) flow data, which provide useful information for urban planning and traffic management applications. [...] Read more.

As a hot research topic in urban geography, spatiotemporal interaction analysis has been used to detect the hotspot mobility patterns of crowds and urban structures based on the origin-destination (OD) flow data, which provide useful information for urban planning and traffic management applications. However, existing methods mainly focus on the detection of explicit spatial interaction patterns (such as spatial flow clusters) in OD flow data, with less attention to the discovery of underlying crowd travel demands. Therefore, this paper proposes a framework to discover the crowd travel demands by associating the dynamic spatiotemporal interaction patterns and the contextual semantic features of the geographical environment. With urban functional zones (UFZs) as the basic units of human mobility in urban spaces, this paper gives a case study in Wuhan, China, to detect and interpret the human mobility patterns based on the characteristics of spatiotemporal interaction between UFZs. Firstly, we build the spatiotemporal interaction matrix based on the OD flows of different UFZs and analyze the characteristics of the interaction matrix. Then, hotspot poles, defined as the local areas where people gather significantly, are extracted using the Gi-statistic-based spatial hotspot detection algorithm. Next, we develop a frequent interaction pattern mining method to detect the frequent interaction patterns of the hotspot poles. Finally, based on the detected frequent interaction patterns, we discover the travel demands of crowds with semantic features of corresponding urban functional zones. The characteristics of crowd travel distance and travel time are further discussed. Experiments with floating car data, road networks, and POIs in Wuhan were conducted, and results show that the underlying travel demands can be better discovered and interpreted by the proposed framework and methods in this paper. This study helps to understand the characteristics of human movement and can provide support for applications such as urban planning and facility optimization. Full article

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Open AccessArticle

Building Façade Color Distribution, Color Harmony and Diversity in Relation to Street Functions: Using Street View Images and Deep Learning

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ISPRS Int. J. Geo-Inf. 2023, 12(6), 224; https://doi.org/10.3390/ijgi12060224 - 30 May 2023

Abstract

Building façade colors play an important role in influencing urban imageability, attraction and citizens’ experience. However, the relations between street functions and the building façade color distribution, color harmony and color diversity have not been thoroughly examined. We obtained the dominant colors of [...] Read more.

Building façade colors play an important role in influencing urban imageability, attraction and citizens’ experience. However, the relations between street functions and the building façade color distribution, color harmony and color diversity have not been thoroughly examined. We obtained the dominant colors of building façades in Changning District, Shanghai, utilizing Baidu street view images, image semantic segmentation technology and the K-means algorithm. The variations in building façades’ dominant colors, color harmony and diversity across different types of functional streets were examined through logistic regression and ANOVA analyses. The results indicate that, compared to industrial streets, red hues are more common in science education streets, residential streets and mixed functional streets. Business streets are more likely to have hues of green, red and red–purple. Residential streets’ saturation is overall higher than that of industrial streets. In business streets, the medium–high value occurs less frequently than other streets. Moreover, we found that the street building façade colors in industrial streets were more harmonious and less diversified than that in other functional streets. This study has implications for urban color planning practices. Color harmony and color diversity should be well considered in future planning. The role of street functions should also be addressed in building façade color planning, to improve existing planning frameworks as well as related strategies. Full article

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Open AccessArticle

The Spatial Association between Residents’ Leisure Activities and Tourism Activities Using Colocation Pattern Measures: A Case Study of Nanjing, China

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ISPRS Int. J. Geo-Inf. 2023, 12(6), 223; https://doi.org/10.3390/ijgi12060223 - 29 May 2023

Abstract

With the increasing trend of residents and tourists sharing urban spaces, the boundary between leisure spaces and tourism spaces is gradually being blurred. However, few studies have quantified the spatiotemporal correlation patterns of residents’ leisure activities and tourists’ activities. To fill this gap, [...] Read more.

With the increasing trend of residents and tourists sharing urban spaces, the boundary between leisure spaces and tourism spaces is gradually being blurred. However, few studies have quantified the spatiotemporal correlation patterns of residents’ leisure activities and tourists’ activities. To fill this gap, this paper takes Nanjing as an example to study the temporal and spatial correlation between residents’ leisure activities and tourists’ activities based on mobile phone signal data. First, through kernel density analysis, it is found that there is a spatial overlap between residents’ leisure activities and tourists’ activities. Then, the spatial and temporal correlation patterns of residents’ leisure activities and tourists’ activities are analyzed through the colocation quotient. According to our findings, (1) residents’ leisure activities and tourists’ activities are not spatially correlated, indicating that they are relatively independent in space both during the week and on weekends. (2) On weekday afternoons, the spatial correlation between residents’ and tourists’ leisure activities is strongest. On weekends, the night is when residents’ leisure activities and tourists’ activities are most closely related. (3) The correlation area is mainly distributed in areas near famous scenic spots, as well as public spaces such as parks and squares. Based on the above analysis, this paper aims to study the resident-tourist interaction in the spatial context to provide directions for improving the attractiveness of cities, urban transportation, services, and marketing strategies. Full article

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Open AccessArticle

Benchmarking Geospatial High-Value Data Openness Using GODI Plus Methodology: A Regional Level Case Study

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Karlo Kević

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Ana Kuveždić Divjak

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Frederika Welle Donker

ISPRS Int. J. Geo-Inf. 2023, 12(6), 222; https://doi.org/10.3390/ijgi12060222 - 29 May 2023

Abstract

The 2019 European Open Data Directive identifies geospatial data as data that could have a major impact on human activities (high-value data, HVD) and advocates its provision as open data (OD), i.e., without barriers to access and re-use. Although Croatia has implemented OD [...] Read more.

The 2019 European Open Data Directive identifies geospatial data as data that could have a major impact on human activities (high-value data, HVD) and advocates its provision as open data (OD), i.e., without barriers to access and re-use. Although Croatia has implemented OD policies to support the provision of open data, many geospatial data are still not available, or if available, their level of openness ranks Croatia lower than Slovenia and Serbia on some ranking lists. Benchmarking tools have proven to be a powerful tool in identifying barriers in OD. This paper, therefore, benchmarks the level of openness and provision of geospatial HVD in Croatia, Slovenia and Serbia, using the extended and modified Global Open Data Index methodology (GODI Plus). It is expected that this will provide an answer to the status of OD policies and government engagement in OD in Croatia and identify good OD practices among the three countries analyzed. Furthermore, the results will be a baseline benchmark for future HVD analyses. The results reveal low data openness for Croatia and Serbia, high data openness for Slovenia, and a low level of government engagement in all three proposed countries. Full article

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Open AccessArticle

Identification of Risk Areas of Dengue Transmission in Culiacan, Mexico

by

Susana Román-Pérez

,

Raúl Aguirre-Gómez

,

Juan Eugenio Hernández-Ávila

,

Luisa Basilia Íñiguez-Rojas

,

René Santos-Luna

and

Fabián Correa-Morales

ISPRS Int. J. Geo-Inf. 2023, 12(6), 221; https://doi.org/10.3390/ijgi12060221 - 29 May 2023

Abstract

Dengue is a public health problem in more than 100 countries around the world and in virtually the entire region of the Americas, including Mexico. Mosquitoes of the genus Aedes aegypti transmit dengue; its reproduction requires certain geographical, epidemiological, demographic and socioeconomic conditions. [...] Read more.

Dengue is a public health problem in more than 100 countries around the world and in virtually the entire region of the Americas, including Mexico. Mosquitoes of the genus Aedes aegypti transmit dengue; its reproduction requires certain geographical, epidemiological, demographic and socioeconomic conditions. Detailed information on socioeconomic, epidemiological and entomological data is available, but detailed meteorological information is not. The objective of this study was to identify the areas of risk of dengue transmission for each month of the year based on environmental, social, entomological and epidemiological information from 2010 to 2020, in Culiacan, Mexico. LST, NDVI and NDMI were calculated from Landsat 8 satellite images with remote sensing techniques. Additional variables were human population density and overcrowding; mosquito egg density from positive ovitraps; and probable cases of dengue. A descriptive analysis of the study variables and a multiple linear regression analysis were performed to determine the significant variables. In addition, a multicriteria spatial analysis was applied through the AHP technique to identify areas at risk of dengue transmission. The results revealed that the variables NDVI, NDMI and overcrowding were not significant; however, the LST, population density, egg density per positive ovitrap and probable cases were. The highest population in the transmission risk areas was in November, and the highest transmission area was identified in October. In conclusion, it was possible to identify which of the study variables were significant; in addition, monthly maps of risk areas of dengue transmission for Culiacan were obtained. Each geographical area had its own characteristics that influenced, in one way or another, the incidence of dengue, highlighting that the strategies for control of dengue must be specific to each region. Full article

(This article belongs to the Topic Applications of Spatial Science and Technology in Health Research)

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ISPRS International Journal of Geo-Information

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