The effective deployment of medical emergency equipment, such as automated external defibrillator (AED), is essential to myocardial infarction (MI) patients. However, there are shortcomings in current studies that simultaneously consider the risk of MI and the availability of medical resources when siting the AEDs. In this study, an AED site recommendation framework was proposed to address the lack of consideration for both the MI risk and medical resources when siting the AEDs. It conducts the AED sitting under different scenarios considering the spatial distribution of MI risk and healthcare accessibility in Chinese cities. First, an automated machine learning framework data is proposed to estimate the MI risk at the community scale based on multi‐source spatio‐temporal. Second, the accessibility of medical resources was calculated by an improved Gaussian two‐step moving search algorithm. Finally, the AED siting in multiple scenarios is conducted based on the coverage model. The performance of the AED siting model was evaluated at Wuhan city. The results show that MI risk is impacted by both socioeconomic and cultural characteristics (municipal utilities, streetscape environment, educational and commercial facilities). There is a strong spatial heterogeneity in the distribution of both MI risk and medical resources in Wuhan, and an unreasonable match between the two was detected in some regions. Medical resources need to be strengthened in some high‐risk areas, such as rural areas and tourist attractions. In addition, 1015 AED candidate sites were identified by the location set covering problem model, with a 15‐min accessibility rate of 96.5%. Given the limited resources, mobile AEDs which have about 15‐min service range can be deployed based on the maximum covering location problem model to meet the demand in central urban areas efficiently. This study can contribute to more rational selection of AED sites and the prevention of myocardial infarction among residents, particularly when supported by policies that promote balanced regional development of pre‐hospital medical emergency networks.
{"title":"Automated external defibrillator location selection considering myocardial infarction risk and medical resources","authors":"Yao Yao, Ledi Shao, Hanyu Yin, Changwu Xu, Zihao Guo, Honghuang Chen, Junyi Cheng, Xiaotong Zhang, Jiteng Xie, Chenqi Feng, Qingfeng Guan, Peng Luo","doi":"10.1111/tgis.13223","DOIUrl":"https://doi.org/10.1111/tgis.13223","url":null,"abstract":"The effective deployment of medical emergency equipment, such as automated external defibrillator (AED), is essential to myocardial infarction (MI) patients. However, there are shortcomings in current studies that simultaneously consider the risk of MI and the availability of medical resources when siting the AEDs. In this study, an AED site recommendation framework was proposed to address the lack of consideration for both the MI risk and medical resources when siting the AEDs. It conducts the AED sitting under different scenarios considering the spatial distribution of MI risk and healthcare accessibility in Chinese cities. First, an automated machine learning framework data is proposed to estimate the MI risk at the community scale based on multi‐source spatio‐temporal. Second, the accessibility of medical resources was calculated by an improved Gaussian two‐step moving search algorithm. Finally, the AED siting in multiple scenarios is conducted based on the coverage model. The performance of the AED siting model was evaluated at Wuhan city. The results show that MI risk is impacted by both socioeconomic and cultural characteristics (municipal utilities, streetscape environment, educational and commercial facilities). There is a strong spatial heterogeneity in the distribution of both MI risk and medical resources in Wuhan, and an unreasonable match between the two was detected in some regions. Medical resources need to be strengthened in some high‐risk areas, such as rural areas and tourist attractions. In addition, 1015 AED candidate sites were identified by the location set covering problem model, with a 15‐min accessibility rate of 96.5%. Given the limited resources, mobile AEDs which have about 15‐min service range can be deployed based on the maximum covering location problem model to meet the demand in central urban areas efficiently. This study can contribute to more rational selection of AED sites and the prevention of myocardial infarction among residents, particularly when supported by policies that promote balanced regional development of pre‐hospital medical emergency networks.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"9 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical and cadastral data management practices for underground facilities are insufficient to represent underground assets' Rights, Restrictions, and Responsibilities (RRRs) and their relationships with the cadastre. For this reason, developing a 3D integrated data (underground and above‐ground) model may be an approach to an effective land management system. This research aims to develop a creative data model by integrating Turkish National Geographic Information System (TUCBS‐AY in Turkish) with international standards (Land Administration Domain Model (LADM) and CityGML) as a holistic approach. The requirements determined for underground facilities using TUCBS‐AY were used. Since the data produced in Turkey were modeled according to the CityGML 2.0 version, the CityGML 2.0 UtilityNetwork version was used in the study to be compatible with the existing Turkish cadastral system. While some classes in the model are generalized, they are expanded using LADM's classes for legal rights and part information. In addition, the CityGML classes have been expanded within the model so that parcels, buildings, and independent sections are represented separately, thus providing the opportunity to represent the underground utilities associated with them, their RRRs, and ownership situations. Requirements for the proposed model were determined based on Turkey's cadastral system and underground data. The main purpose is to manage the legal and physical relations of underground and surface objects at the city scale, compatible with the current Turkish cadastral system, with a holistic approach. The proposed integrated conceptual data model shows how legal rights and ownership of underground structures can be logically represented with a 3D data model.
{"title":"A holistic approach proposal for 3D underground land management (3D ULA) in Turkey: The case of utility network","authors":"Hicret Gürsoy Sürmeneli, Jing Sun, Mehmet Alkan","doi":"10.1111/tgis.13230","DOIUrl":"https://doi.org/10.1111/tgis.13230","url":null,"abstract":"Physical and cadastral data management practices for underground facilities are insufficient to represent underground assets' Rights, Restrictions, and Responsibilities (RRRs) and their relationships with the cadastre. For this reason, developing a 3D integrated data (underground and above‐ground) model may be an approach to an effective land management system. This research aims to develop a creative data model by integrating Turkish National Geographic Information System (TUCBS‐AY in Turkish) with international standards (Land Administration Domain Model (LADM) and CityGML) as a holistic approach. The requirements determined for underground facilities using TUCBS‐AY were used. Since the data produced in Turkey were modeled according to the CityGML 2.0 version, the CityGML 2.0 UtilityNetwork version was used in the study to be compatible with the existing Turkish cadastral system. While some classes in the model are generalized, they are expanded using LADM's classes for legal rights and part information. In addition, the CityGML classes have been expanded within the model so that parcels, buildings, and independent sections are represented separately, thus providing the opportunity to represent the underground utilities associated with them, their RRRs, and ownership situations. Requirements for the proposed model were determined based on Turkey's cadastral system and underground data. The main purpose is to manage the legal and physical relations of underground and surface objects at the city scale, compatible with the current Turkish cadastral system, with a holistic approach. The proposed integrated conceptual data model shows how legal rights and ownership of underground structures can be logically represented with a 3D data model.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"51 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The main goal of this article is to analyze spatial disparities in local electoral participation in Slovakia between 1994 and 2018 on a very detailed spatial structure of all (almost 3000) municipalities. To achieve this goal, methods of global and local spatial autocorrelation and spatial regression are used. Municipality‐level analysis, then, provides three main results. First, cartographic presentations provide spatial evidence of highly stable patterns of electoral participation in Slovak municipalities. In the long term, there was no substantial inter‐electoral change in the clustering of voter turnout in the different municipalities, except for an overall significant decline in the homogeneity of the clusters with low or high electoral turnout. Second, while there was some positive spatial autocorrelation of turnout between a concrete municipality and its surroundings, suggesting the existence of a contagion effect, this effect was not too strong and quickly waned with growing distance. Third, as especially the local elections in 2018 suggested that local political environment has its own dynamics that are increasingly independent of municipality size, a more detailed analysis of the local political context combining both quantitative and qualitative techniques should be a priority in the future.
{"title":"Geography of voter turnout in Slovak local elections (1994–2018): The effects of size and contagion on local electoral participation","authors":"Pavel Maškarinec","doi":"10.1111/tgis.13221","DOIUrl":"https://doi.org/10.1111/tgis.13221","url":null,"abstract":"The main goal of this article is to analyze spatial disparities in local electoral participation in Slovakia between 1994 and 2018 on a very detailed spatial structure of all (almost 3000) municipalities. To achieve this goal, methods of global and local spatial autocorrelation and spatial regression are used. Municipality‐level analysis, then, provides three main results. First, cartographic presentations provide spatial evidence of highly stable patterns of electoral participation in Slovak municipalities. In the long term, there was no substantial inter‐electoral change in the clustering of voter turnout in the different municipalities, except for an overall significant decline in the homogeneity of the clusters with low or high electoral turnout. Second, while there was some positive spatial autocorrelation of turnout between a concrete municipality and its surroundings, suggesting the existence of a contagion effect, this effect was not too strong and quickly waned with growing distance. Third, as especially the local elections in 2018 suggested that local political environment has its own dynamics that are increasingly independent of municipality size, a more detailed analysis of the local political context combining both quantitative and qualitative techniques should be a priority in the future.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"14 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141871395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the realm of volunteered geographic information (VGI), the existence of comparable tags, attributes, and values across diverse categories of geographic objects gives rise to major categorization challenges such as conceptual overlap and indiscernibility. Enhancing the semantic data retrieval of VGI relies on the semantic quality of descriptive content annotated for tagging geographic objects. The main focus of this study is analyzing the descriptive content of OpenStreetMap to assess the significance of semantic levels. The proposed methodology relies on fuzzy rough set calculations to determine the degrees of dependency and significance of semantic levels. Three indicators, namely, the significance of semantic levels, decreasing the heterogeneity of attributes, and replicability were defined and assessed for a subset of building‐related tags. Analyzing building‐related tags in OpenStreetMap unveiled the higher significance for simple object, similarity, purpose, and function levels. The value of decreasing the heterogeneity of attributes was calculated at 63%, and the average replicability indicator of important attributes was doubled. Based on the results, the significance of semantic levels was deemed fit to enhance semantic homogeneity and replicability.
{"title":"A fuzzy rough approach to analyze the significance of semantic levels for building tags in OpenStreetMap","authors":"Somayeh Ahmadian, Parham Pahlavani","doi":"10.1111/tgis.13222","DOIUrl":"https://doi.org/10.1111/tgis.13222","url":null,"abstract":"In the realm of volunteered geographic information (VGI), the existence of comparable tags, attributes, and values across diverse categories of geographic objects gives rise to major categorization challenges such as conceptual overlap and indiscernibility. Enhancing the semantic data retrieval of VGI relies on the semantic quality of descriptive content annotated for tagging geographic objects. The main focus of this study is analyzing the descriptive content of OpenStreetMap to assess the significance of semantic levels. The proposed methodology relies on fuzzy rough set calculations to determine the degrees of dependency and significance of semantic levels. Three indicators, namely, the significance of semantic levels, decreasing the heterogeneity of attributes, and replicability were defined and assessed for a subset of building‐related tags. Analyzing building‐related tags in OpenStreetMap unveiled the higher significance for simple object, similarity, purpose, and function levels. The value of decreasing the heterogeneity of attributes was calculated at 63%, and the average replicability indicator of important attributes was doubled. Based on the results, the significance of semantic levels was deemed fit to enhance semantic homogeneity and replicability.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"13 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141871396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peter Baumann, Bang Pham Huu, Dimitar Misev, Vlad Merticariu
A significant share of our data are timeseries. Time can occur as the single dimension, or further (such as spatial) dimensions can be present as well, leading to multidimensional data such as 3D x/y/t satellite image timeseries or 4D x/y/z/t atmospheric simulations like weather forecasts. However, no user would like to count “seconds since epoch,” rather we all prefer calendar notation. Libraries, SQL, etc. support calendar arithmetics, yet more advanced functionality is needed. Instead of demoting advanced calendar functionality to low‐level coding, it seems desirable to have semantic support for calendars at high‐level, declarative query level. We present a conceptual framework for temporal modeling which allows the expression of a wide range of temporal queries. It smoothly enhances existing calendar handling by adding two new data and query description parameters, period of validity, and granularity. While our work is embedded in spatio‐temporal geo services, it can be incorporated in a non‐breaking manner in any environment needing calendar addressing. The concepts are implemented in an Array DBMS operational on several Petabytes of Earth datacubes.
{"title":"Enhanced calendar support for temporal datacube queries","authors":"Peter Baumann, Bang Pham Huu, Dimitar Misev, Vlad Merticariu","doi":"10.1111/tgis.13215","DOIUrl":"https://doi.org/10.1111/tgis.13215","url":null,"abstract":"A significant share of our data are timeseries. Time can occur as the single dimension, or further (such as spatial) dimensions can be present as well, leading to multidimensional data such as 3D <jats:italic>x</jats:italic>/<jats:italic>y</jats:italic>/<jats:italic>t</jats:italic> satellite image timeseries or 4D <jats:italic>x</jats:italic>/<jats:italic>y</jats:italic>/<jats:italic>z</jats:italic>/<jats:italic>t</jats:italic> atmospheric simulations like weather forecasts. However, no user would like to count “seconds since epoch,” rather we all prefer calendar notation. Libraries, SQL, etc. support calendar arithmetics, yet more advanced functionality is needed. Instead of demoting advanced calendar functionality to low‐level coding, it seems desirable to have semantic support for calendars at high‐level, declarative query level. We present a conceptual framework for temporal modeling which allows the expression of a wide range of temporal queries. It smoothly enhances existing calendar handling by adding two new data and query description parameters, period of validity, and granularity. While our work is embedded in spatio‐temporal geo services, it can be incorporated in a non‐breaking manner in any environment needing calendar addressing. The concepts are implemented in an Array DBMS operational on several Petabytes of Earth datacubes.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"153 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141871397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Claire Wright, Chris Bone, Darcy Mathews, James Tricker, Ben Wright, Eric Higgs
The objective of this article is to present a novel GIS plugin for classifying and georeferencing high‐resolution oblique imagery with the intention of creating landcover datasets for spatial analysis. The Mountain Image Analysis Suite (MIAS) is a newly released plugin for the open‐source software, QGIS. MIAS was developed with images from Mountain Legacy Project, the world's largest systematic collection of high‐resolution mountain images. It works with both grayscale and color imagery, including historical images that predate aerial and satellite imagery. MIAS encompasses four tools for classifying and georeferencing oblique images. The plugin accesses pretrained deep learning models from a PyTorch‐based segmentation network to automate the classification of landcover in oblique images. Monoplotting is accomplished through the construction of a virtual photograph simulating the view from the camera using a shaded relief model. Once the virtual photograph is produced, the user aligns the classified image to the virtual photograph using a set of control points. This allows the creation of a classified and georeferenced raster representing the landcover for the area visible in the original oblique image. Similar workflows to the one contained in MIAS have been used for landcover mapping with oblique images to a high level of accuracy. However, MIAS is the first piece of software to bring all stages of image analysis into a single platform. MIAS has many applications across diverse fields such as mountain research, ecological restoration, community‐based mapping, environmental planning, and more.
{"title":"Mountain Image Analysis Suite (MIAS): A new plugin for converting oblique images to landcover maps in QGIS","authors":"Claire Wright, Chris Bone, Darcy Mathews, James Tricker, Ben Wright, Eric Higgs","doi":"10.1111/tgis.13229","DOIUrl":"https://doi.org/10.1111/tgis.13229","url":null,"abstract":"The objective of this article is to present a novel GIS plugin for classifying and georeferencing high‐resolution oblique imagery with the intention of creating landcover datasets for spatial analysis. The Mountain Image Analysis Suite (MIAS) is a newly released plugin for the open‐source software, QGIS. MIAS was developed with images from Mountain Legacy Project, the world's largest systematic collection of high‐resolution mountain images. It works with both grayscale and color imagery, including historical images that predate aerial and satellite imagery. MIAS encompasses four tools for classifying and georeferencing oblique images. The plugin accesses pretrained deep learning models from a PyTorch‐based segmentation network to automate the classification of landcover in oblique images. Monoplotting is accomplished through the construction of a virtual photograph simulating the view from the camera using a shaded relief model. Once the virtual photograph is produced, the user aligns the classified image to the virtual photograph using a set of control points. This allows the creation of a classified and georeferenced raster representing the landcover for the area visible in the original oblique image. Similar workflows to the one contained in MIAS have been used for landcover mapping with oblique images to a high level of accuracy. However, MIAS is the first piece of software to bring all stages of image analysis into a single platform. MIAS has many applications across diverse fields such as mountain research, ecological restoration, community‐based mapping, environmental planning, and more.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"39 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141783355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In an abstract sense, researchers have assumed that a population‐based centroid better represents a given polygon than a purely geometric centroid (GC) because it accounts for the internal distribution of the local population. In specific application contexts, when measuring place‐based spatial accessibility, for example, using a GC might be misleading because this practice could overestimate travel costs in large polygons; however, this assumption has not been quantitatively tested. In this article, we examine the role of centroid definition types by comparing the accessibility values of three different centroid estimation approaches. The analysis indicated that, in comparison to population‐based centroids, the GC typically underestimated accessibility values, particularly in sparsely populated polygons, and accentuated spatial disparities. The findings suggest that researchers need to pay more cautious attention to the potential impact of centroid methods when measuring spatial accessibility.
{"title":"Assessing the effects of centroid assignment methods on measuring spatial accessibility","authors":"Kyusik Kim, Mark W. Horner","doi":"10.1111/tgis.13228","DOIUrl":"https://doi.org/10.1111/tgis.13228","url":null,"abstract":"In an abstract sense, researchers have assumed that a population‐based centroid better represents a given polygon than a purely geometric centroid (GC) because it accounts for the internal distribution of the local population. In specific application contexts, when measuring place‐based spatial accessibility, for example, using a GC might be misleading because this practice could overestimate travel costs in large polygons; however, this assumption has not been quantitatively tested. In this article, we examine the role of centroid definition types by comparing the accessibility values of three different centroid estimation approaches. The analysis indicated that, in comparison to population‐based centroids, the GC typically underestimated accessibility values, particularly in sparsely populated polygons, and accentuated spatial disparities. The findings suggest that researchers need to pay more cautious attention to the potential impact of centroid methods when measuring spatial accessibility.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"16 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141783352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ci Song, Nan Chen, YueXue Xu, YiNing Zhang, HongChun Zhu
The current research focus on visualizing terrain features emphasizes quantification and detailed simulation, without adequately considering the impact of spatial–temporal variations in the terrain on human cognition. However, advancements in visualization technology, such as efficient and rapid construction of large‐scale three‐dimensional (3D) terrain scenes, real‐time dynamic display, and free‐roaming from any viewpoint, currently provide ample technical support for visualizing spatial–temporal information. Therefore, this article proposes a 3D terrain viewing model that considers the spatial–temporal changes in light intensity and incident direction in a terrain scene, based on the principles of radiometry and computer graphics theory and supported by the physically based rendering techniques. This model aims to accurately represent the subtle variations in real‐world terrain surfaces and highlight the key elements of hill terrain. Theoretically, this model provides a foundation for the virtual reconstruction of real‐world terrain.
{"title":"Field‐of‐view modeling of hilly terrain based on physically based rendering of spatial–temporal variations within optical radiation","authors":"Ci Song, Nan Chen, YueXue Xu, YiNing Zhang, HongChun Zhu","doi":"10.1111/tgis.13216","DOIUrl":"https://doi.org/10.1111/tgis.13216","url":null,"abstract":"The current research focus on visualizing terrain features emphasizes quantification and detailed simulation, without adequately considering the impact of spatial–temporal variations in the terrain on human cognition. However, advancements in visualization technology, such as efficient and rapid construction of large‐scale three‐dimensional (3D) terrain scenes, real‐time dynamic display, and free‐roaming from any viewpoint, currently provide ample technical support for visualizing spatial–temporal information. Therefore, this article proposes a 3D terrain viewing model that considers the spatial–temporal changes in light intensity and incident direction in a terrain scene, based on the principles of radiometry and computer graphics theory and supported by the physically based rendering techniques. This model aims to accurately represent the subtle variations in real‐world terrain surfaces and highlight the key elements of hill terrain. Theoretically, this model provides a foundation for the virtual reconstruction of real‐world terrain.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"31 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141783354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Samy Katumba, Serena Coetzee, Alfred Stein, Inger Fabris‐Rotelli
To realize the first sustainable development goal of ending “poverty in all its forms everywhere,” local governments in South Africa need to implement informed targeted policy interventions based on up‐to‐date data and sound analytics. Statistics South Africa (Stats SA) Censuses reveal the socioeconomic circumstances of people living in South Africa but are only conducted every 10 years. As a result, most analytical studies done in‐between Censuses rely on outdated socioeconomic data. This study demonstrates how poverty levels in one of the provinces of South Africa, Gauteng, can be predicted when up‐to‐date Census datasets are not available. The spatial lag model is used to explain the relationship between the South African Multidimensional Poverty Index (SAMPI) and statistically significant variables extracted from land use datasets (i.e., land areas classified as built‐up, informal, residential, township, and non‐urban), and to ultimately predict the levels of poverty. Out‐of‐sample predicted poverty levels obtained based on the spatial lag model correlate with the actual levels of poverty thereby reflecting known spatial patterns of the levels of poverty in Gauteng province.
{"title":"Spatial prediction of poverty in Gauteng province (South Africa) in‐between Censuses using land use datasets","authors":"Samy Katumba, Serena Coetzee, Alfred Stein, Inger Fabris‐Rotelli","doi":"10.1111/tgis.13227","DOIUrl":"https://doi.org/10.1111/tgis.13227","url":null,"abstract":"To realize the first sustainable development goal of ending “poverty in all its forms everywhere,” local governments in South Africa need to implement informed targeted policy interventions based on up‐to‐date data and sound analytics. Statistics South Africa (Stats SA) Censuses reveal the socioeconomic circumstances of people living in South Africa but are only conducted every 10 years. As a result, most analytical studies done in‐between Censuses rely on outdated socioeconomic data. This study demonstrates how poverty levels in one of the provinces of South Africa, Gauteng, can be predicted when up‐to‐date Census datasets are not available. The spatial lag model is used to explain the relationship between the South African Multidimensional Poverty Index (SAMPI) and statistically significant variables extracted from land use datasets (i.e., land areas classified as built‐up, informal, residential, township, and non‐urban), and to ultimately predict the levels of poverty. Out‐of‐sample predicted poverty levels obtained based on the spatial lag model correlate with the actual levels of poverty thereby reflecting known spatial patterns of the levels of poverty in Gauteng province.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"42 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141783353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Urban sprawl and the shortage of proper sanitary infrastructures significantly jeopardize public health and urban sustainability. The problem is further aggravated as a result of the rapid urbanization and urban sprawl. This study investigated the relationship between urban sprawl and sanitation risk conditions in a rapidly growing city in India. This was accomplished by investigating changes in urban sprawl areas between the periods 2000–2020 using multispectral satellite images and Shanon's entropy model and studying the pattern of spatial variations in basic sanitation services derived from the 100 household‐based surveyed WASH (water availability, sanitation, and hygiene) data collected in 2018 before COVID‐19 from 45 sprawl regions. Spatial statistical techniques, namely, the inverse distance weighted (IDW) interpolation and the multicriteria decision technique, were employed for neighborhood analysis and assessing sanitation risks inside the sprawl region. Results showed that Raipur exhibited urban sprawl and around 93.68% of the sprawl area was classified between high (6.47%)‐ and medium (80.52%)‐risk zones.
{"title":"Understanding impact of urban sprawl over sanitation risks using GIS‐based multicriteria decision‐making approach","authors":"Debrupa Chatterjee, Dharmaveer Singh, Diganta Bhushan Das, Pushpendra Kumar Singh","doi":"10.1111/tgis.13220","DOIUrl":"https://doi.org/10.1111/tgis.13220","url":null,"abstract":"Urban sprawl and the shortage of proper sanitary infrastructures significantly jeopardize public health and urban sustainability. The problem is further aggravated as a result of the rapid urbanization and urban sprawl. This study investigated the relationship between urban sprawl and sanitation risk conditions in a rapidly growing city in India. This was accomplished by investigating changes in urban sprawl areas between the periods 2000–2020 using multispectral satellite images and Shanon's entropy model and studying the pattern of spatial variations in basic sanitation services derived from the 100 household‐based surveyed WASH (water availability, sanitation, and hygiene) data collected in 2018 before COVID‐19 from 45 sprawl regions. Spatial statistical techniques, namely, the inverse distance weighted (IDW) interpolation and the multicriteria decision technique, were employed for neighborhood analysis and assessing sanitation risks inside the sprawl region. Results showed that Raipur exhibited urban sprawl and around 93.68% of the sprawl area was classified between high (6.47%)‐ and medium (80.52%)‐risk zones.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"40 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141783359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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