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Copyright of Resources Development & Market is the property of Sichuan Resource Development & Market Magazine Co., Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The energy demand and associated greenhouse gas (GHG) emissions of buildings are significantly affected by the characteristics of the building and local climate conditions. While energy use datasets with high spatial and temporal resolution are highly needed in the context of climate change, energy use monitoring data are not available for most cities. This study introduces an approach combining building energy simulation, climate change modeling, and GIS spatial analysis techniques to develop an energy demand data inventory enabling assessment of the impacts of climate change on building energy consumption in Shanghai, China. Our results suggest that all types of buildings exhibit a net increase in their annual energy demand under the projected future (2050) climate conditions, with the highest increase in energy demand attributed to Heating, Ventilation, and Cooling (HVAC) systems. Variations in building energy demand are found across building types. Due to the large number of residential buildings, they are the main contributor to the increases in energy demand and associated CO2 emissions. The hourly residential building energy demand on a typical hot summer day (29 July) under the 2050 climate condition at 1 p.m. is found to increase by more than 40%, indicating a risk of energy supply shortage if no actions are taken. The spatial pattern of total annual building energy demand at the individual building level exhibited high spatial heterogeneity with some hotspots. This study provides an alternative method to develop a building energy demand inventory with high temporal resolution at the individual building scale for cities lacking energy use monitoring data, supporting the assessment of building energy and GHG emissions under both current and future climate scenarios at minimal cost. [ABSTRACT FROM AUTHOR]

The wind power industry is increasing worldwide every year. Thus, obtaining timely and detailed information on wind farms’ number and spatial distribution is critical for quantitatively estimating wind energy utilization and for planning the construction of new wind farms. Therefore, this study proposes a method for quickly identifying wind farms in a large-scale area. Given that wind farms mainly comprise individual objects such as wind turbines and substations, we labeled sample images of wind turbines and substations on a global scale. Then, these sample images are used to train a target recognition model and an object classification model and detect the specific locations of wind turbines and substations in the study area. Additionally, we deeply analyzed the location features of the wind turbines and further improved the recognition accuracy based on these known features using geographic constraints. Based on the location information of wind turbines and substations, a clustering model organizes them effectively into complete wind farms. A comprehensive evaluation of the clustering model verifies its scientific validity and reliability. Specifically, this framework was systematically tested throughout Vietnam with remarkable results, using high-resolution historical images provided by Google Earth. Indeed, our framework achieved 90.45% recall and 95.73% accuracy for wind turbines and 81.37% recall and 78.96% accuracy for substations. Finally, we successfully obtained the spatial location and distribution of 15 completed wind farms, demonstrating that the proposed scheme can quickly and accurately identify wind power plants in a large-scale area, which supports wind power management and energy utilization planning.

The spatial distribution of Leisure Urban Spaces (LUSs) is closely linked to urban sustainability and residents' quality of life. This study uses the Central Urban Area of Nanjing as the study area. Using POI and AOI data, the locations of LUS were precisely identified and categorized, including parks, squares, waterfront spaces, and leisure blocks. GIS spatial analysis methods, the nearest neighbor index, standard deviation ellipse, and kernel density estimation were used to analyze these spaces' form, directivity, and density. Population activity intensity (PAI) data at various time points, collected by Baidu heat map, are correlated with LUS distribution through multiple linear regression analysis. (1) Parks and squares exhibit significant clustering tendencies, whereas waterfront spaces show weaker clustering, and leisure blocks are randomly distributed; (2) The central points of all types of LUS are located in the city center, extending from southeast to northwest, with parks and squares offering a broader range of services; (3) The overall LUS layout shows a 'core and multiple points' structure, with varying density patterns across different spaces, indicating concentrated and dispersed leisure areas; (4) The correlation between LUS distribution and PAI strengthens throughout the day and is greater on weekends than weekdays. Leisure blocks significantly enhance activity intensity, while parks have a limited effect, and waterfront spaces often show a negative correlation due to their remote locations. These results provide insights for future urban planning in Nanjing and underscore patterns in residents' leisure activities. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive analysis of natural hazard susceptibility in the Makedonska Kamenica municipality of North Macedonia, encompassing erosion assessment, landslides, flash floods, and forest fire vulnerability. Employing advanced GIS and remote sensing (RS) methodologies, hazard models were meticulously developed and integrated to discern areas facing concurrent vulnerabilities. Findings unveil substantial vulnerabilities prevalent across the area, notably along steep terrain gradients, river valleys, and deforested landscapes. Erosion assessment reveals elevated rates, with a mean erosion coefficient (Z) of 0.61 and an annual erosion production of 182,712.9 m3, equivalent to a specific erosion rate of 961.6 m3/km2/year. Landslide susceptibility analysis identifies 31.8% of the municipality exhibiting a very high probability of landslides, while flash flood susceptibility models depict 3.3% of the area prone to very high flash flood potential. Forest fire susceptibility mapping emphasizes slightly less than one-third of the municipality's forested area is highly or very highly susceptible to fires. Integration of these hazard models elucidates multi-hazard zones, revealing that 11.0% of the municipality's territory faces concurrent vulnerabilities from excessive erosion, landslides, flash floods, and forest fires. These zones are predominantly located in upstream areas, valleys of river tributaries, and the estuary region. The identification of multi-hazard zones underscores the critical need for targeted preventive measures and robust land management strategies to mitigate potential disasters and safeguard both human infrastructure and natural ecosystems. Recommendations include the implementation of enhanced monitoring systems, validation methodologies, and community engagement initiatives to bolster hazard preparedness and response capabilities effectively. [ABSTRACT FROM AUTHOR]

Copyright of China Cultural Heritage is the property of Chinese Academy of Cultural Heritage and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The interconnection between the objectives of territorial development and those of the agro-ecological transition highlights the value of past knowledge in the sustainable management of resources and agro-ecological systems. However, the lack of data creates difficulties for retrospection in rural areas. This paper contributes to the search for such knowledge from the past by developing an interactive methodology capable of combining heterogeneous information sources with the activation of local collective memory. Its effectiveness is based on ensuring the interoperability of information and communication in an environment simultaneously shaped by geoinformatics and 3D geovisualisations. This virtual environment fostered participation and interactivity, supported by representations of the paleo-landscape (Ottoman period). Furthermore, synergies were achieved between information sources, which were integrated into local spatial systems. The application example involved identifying a rice field that existed between the 15th and 19th centuries in Thessaly, Greece. It is an interesting case because the research results indicated that the location and organisation of the crop, combined with the spatio-temporal coordination required, ensured the sustainable use of natural resources. The interplay between information and communication facilitated community participation and the activation of its collective memory as an information source that enriched the search itself and local intelligence. [ABSTRACT FROM AUTHOR]

This research examines the evolution of the spatial collaborative network (SCN) within the Long March Cultural Tourism Belt in China, utilizing a mixed‐methods approach combining quantitative data analysis and GIS spatial analysis. Theoretically, it bridges national identity theory and political ideology using spatial network analysis; expanding understanding of how cultural heritage tourism contributes to national identity consolidation and the political narrative within a spatial framework. This contributes to the literature by demonstrating the role of SCNs in promoting cultural tourism's sustainable growth, addressing the call for methodological advances in cultural tourism research. In terms of the managerial side, it guides policymakers in leveraging SCNs for balanced cultural tourism growth through strategic planning and digital innovation. This research is distinguished by its comprehensive analysis of SCN evolution in a significant cultural tourism context, providing a model for global application. [ABSTRACT FROM AUTHOR]

The analysis of the spatial connection and structural characteristics evolution of the railway passenger transport network in Chengdu-Chongqing Economic Circle is of great significance to the future network construction and layout optimization. This paper constructs the railway passenger transport network of Chengdu-Chongqing Economic Circle based on the 46 863 617 railway passenger transport data, and uses GIS spatial analysis and social network analysis methods to analyze the space-time evolution of railway passenger transport links, the evolution of structure characteristics and the impact of network structure on economy and population in continuous time series. The results show that the polarization of railway passenger transport links in Chengdu Chongqing Economic Circle is obvious, and the passenger transport flow is mainly concentrated in Chengdu, followed by Mianyang, the main districts of Chongqing and Deyang, and other cities account for less than 20% of the passenger transport flow. The density of railway passenger transport network in Chengdu-Chongqing Economic Circle is increasing year by year, but it is still at a low level. The railway passenger transport network has a low average path length and a high average clustering coefficient, and it is characterized by a small world. The degree centrality and betweenness centrality of Chengdu and the main districts of Chongqing are far more than those of other cities. The accessibility of railway passenger transport in Chengdu-Chongqing Economic Circle is largely due to the intermediary role of Chengdu and the main districts of Chongqing. There is no railway passenger transport connection between most cities. The degree centrality, proximity centrality and intermediate centrality have positive effects on GDP, and pass the 1% significance level test. The degree centrality and intermediate centrality have negative impacts on the population, and pass the significance level tests of 5% and 10% respectively. Cities in the central position are not conducive to the permanent residence of the population. [ABSTRACT FROM AUTHOR]

Copyright of Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An urban growth boundary (UGB) is an important policy tool used to control urban sprawl, which can effectively balance the urban construction needs, residents’ quality of life, and urban ecological protection. Current studies of UGB delineation and its indicators have paid little attention to human factors, such as human activities and economic vitality, and weights for evaluation indicators have been determined highly subjectively. In response to these problems, this article integrated multisource geographic Big Data to construct a total of 30 natural, human, and ecological evaluation indicators. The GIS technology and machine-learning (ML) approach were combined to determine indicator weights with an officially manually drawn 2035 UGB as the reference, aiming to reduce the subjectivity. The suitability score was then calculated from indicator grading 4–1 and related weights, and high suitability (>2.15) regions were eventually delineated as the UGB. Results showed a delineated UGB of 1528.06 km2 with an overall accuracy of over 93% and high consistence with reference data for 2035 in the Chinese city of Changsha. The geographic Big Data totally contributed more than 33.72%, which mainly characterized role of human elements, and a 5–6 percentage point reduction in accuracy was found without these data. Compared with existing articles, our delineated UGB had higher accuracy and closer spatial pattern to the reference data, verifying the effectiveness and reasonability of ML-based weight setting approach and index system with geographic Big Data. The proposed method can provide scientific and accurate framework for UGB delineation, which can promote the territorial spatial planning and sustainable urban development.

To capture the factors influencing and measurements of pedestrian accessibility to high-speed rail station areas, ensure the balance between the transportation function and place performance of high-speed railway station areas, the correlation factors and laws of pedestrian space characteristics of high-speed railway station areas under different development modes are studied through the comparison of typical high-speed railway station areas in China and Japan. Combining the circle law and hierarchical analysis method, we establish a walking accessibility index system, construct a walking accessibility evaluation model for the high-speed rail station area, measure the degree of walking accessibility in the high-speed rail station area, and analyze the influence mechanism of different walking space components on the walking accessibility of the high-speed rail station area circle. The results indicate that: 1) Osaka Station space is much more walkable than Beijing Station in all circles; 2) The spatial development within the Beijing Station Station Circle is uneven, and the degree of pedestrian accessibility decreases as the circle’s extent increases; 3)Different station spaces have their own advantages and disadvantages in terms of the distribution of public facilities and amenities, roadway attributes, pedestrian path characteristics, depending on their respective national conditions and station development patterns.

With the rapid socio-economic development and urban expansion, land subsidence has emerged as a major environmental issue, impeding the high-quality development of the plain area in eastern Zhengzhou City, Henan Province, China. However, effective prevention and control of land subsidence in this region have been challenging due to the lack of comprehensive surface deformations monitoring and the quantitative analysis of the factors driving these deformations. In order to accurately identify the dominant factor driving surface deformations in the study area, this study utilized the Persistent Scattered Interferometric Synthetic Aperture Radar (PS-InSAR) technique to acquire the spatio-temporal distribution of surface deformations from January 2018 to March 2020. The acquired data was verified using leveling data. Subsequently, GIS spatial analysis was employed to investigate the responses of surface deformations to the driving factors. The findings are as follows: Finally, the geographical detector model was utilized to quantify the contributions of the driving factors and reveal the mechanisms of their interactions. The findings are as follows: (1) Surface deformations in the study area are dominated by land subsidence, concentrated mainly in Zhongmu County, with a deformation rate of −12.5–−37.1 mm/a. In contrast, areas experiencing surface uplift are primarily located downtown, with deformation rates ranging from 0 mm to 8 mm; (2) Groundwater level, lithology, and urban construction exhibit strong spatial correlations with cumulative deformation amplitude; (3) Groundwater level of the second aquifer group is the primary driver of spatially stratified heterogeneity in surface deformations, with a contributive degree of 0.5328. The contributive degrees of driving factors are significantly enhanced through interactions. Groundwater level and the cohesive soil thickness in the second aquifer group show the strongest interactions in the study area. Their total contributive degree increases to 0.5722 after interactions, establishing them as the primary factors influencing surface deformation patterns in the study area. The results of this study can provide a theoretical basis and scientific support for precise prevention and control measures against land subsidence in the study area, as well as contributing to research on the underlying mechanisms.

AbstractFollowing a major earthquake, disaster information services must deliver accurate damage assessment results during the emergency ‘black box’ phase when data is scarce. Seismic intensity maps contain crucial information for determining the damage in the affected area. For earthquakes with Mw between 5.5 and 7, this study proposes using GIS analysis to mine aftershock events in early aftershock sequences that are closely related to the mainshock fault, and then using these events to generate seismic intensity assessment maps. Regression curves were first obtained using a nonparametric method (rLowess) to analyse the geographical coordinates of early aftershocks. Then, a buffer of 1 or 1.5 km radius was made for the curve, and the aftershocks in the buffer were used to calculate the predicted peak ground velocity (PGV) values over a specific km-grid range. Finally, rapid mapping of seismic intensity was assessed based on the intensity scale. This straightforward and repeatable method employs seismic station data obtained shortly after the mainshock. The assessed seismic intensity accurately reflects the location and extent of the hardest hit areas and can be cross-referenced with geophysical results to accurately assess the damage in the affected areas.

Creative industries, by their nature of innovation through creativity, add value to any territory by giving it spatial functionality, and at the same time, they favour sustainable development through the sustainability of the urban centres in which they operate. This paper develops a GIS methodology based on the implementation of a spatial analysis model that captures, in a comparative way, the spatial functionality of two different urban centres—(Cluj-Napoca (Romania) and Pécs (Hungary))—in terms of spatial extent based on the impact of the spatial distribution of creative industries. The spatial analysis model is based on the management of alpha-numeric databases representing the addresses of the creative industries, based on geolocation, for the development of spatial analyses of pedestrian accessibility. The main aim is to identify the specific areas of 15 and 5 min model cities. The comparative analysis was carried out by implementing a deterministic methodology through which the areas with certain degrees of accessibility were analysed in relation to the total analysed area, with the main aim of standardising the scale of analysis due to the difference between the two urban centres, thus facilitating the use of qualitative boning in the final comparison process. The results obtained highlight the local behaviour, at the same time making it possible to conduct a realistic deterministic comparative analysis of the two urban centres, which are also identifiable from the point of view of local territorial functionality, thereby validating the GIS model implemented in the present study. [ABSTRACT FROM AUTHOR]

Copyright of Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As the birthplace of Hemudu Culture, the Yaojiang Valley has a long history of civilization evolution. During Holocene, a dramatic environmental evolution took place in this area, making it an ideal sample for studying how humans adapt to environmental changes. In this study, we collect 63 archaeological sites of Neolithic Age and Shang-Zhou dynasties, together with their information such as geographical position, cultural periodization, size, cultural layer thickness, archeological relics and remains. ArcGIS software was used to analysis their inheritance, distance from mountains, nuclear density and scale. The results are as follows. First, during the first and second phases of Hemudu culture, the number of sites was small and the inheritance was high, with an overlapping coefficient of 0.83. The number of sites increased significantly in the third and fourth phases of Hemudu culture while the inheritance reduced relatively with an overlapping coefficient of 0.73. During Liangzhu Culture and Shang-Zhou dynasties, the number and inheritance of sites both showed a downward trend. The overlapping coefficient dropped to 0.43. This shows that significant changes in the environment and population composition occurred from the third to the fourth phase of Hemudu culture, the fourth phase of Hemudu culture to Liangzhu culture, and Liangzhu culture to Shang-Zhou dynasties. Secondly, in terms of spatial distribution, archeological sites first appeared in the middle of the Yaojiang Valley and spread to the east and west in the second and fourth phase of Hemudu culture successively until they occupied the whole valley. These archeological sites were generally not more than 1500 m away from the mountains, and only showed a trend of spreading to the plain in the fourth phase of the Hemudu culture and Shang-Zhou dynasties, suggesting that the Yaojiang River was relatively rich in land resources during these two periods, which may be caused by large-scale regression. Thirdly, From the first phase of Hemudu culture to Shang-Zhou dynasties, the Yaojiang Valley was filled from remnant ancient bay into coastal plain. During this period, the formation and the diversion of Yaojiang River, as well as the topographic inversion of coastal area and plain hinterland also happened in this area. [ABSTRACT FROM AUTHOR]

The energy demand and associated greenhouse gas (GHG) emissions of buildings are significantly affected by the characteristics of the building and local climate conditions. While energy use datasets with high spatial and temporal resolution are highly needed in the context of climate change, energy use monitoring data are not available for most cities. This study introduces an approach combining building energy simulation, climate change modeling, and GIS spatial analysis techniques to develop an energy demand data inventory enabling assessment of the impacts of climate change on building energy consumption in Shanghai, China. Our results suggest that all types of buildings exhibit a net increase in their annual energy demand under the projected future (2050) climate conditions, with the highest increase in energy demand attributed to Heating, Ventilation, and Cooling (HVAC) systems. Variations in building energy demand are found across building types. Due to the large number of residential buildings, they are the main contributor to the increases in energy demand and associated CO2 emissions. The hourly residential building energy demand on a typical hot summer day (29 July) under the 2050 climate condition at 1 p.m. is found to increase by more than 40%, indicating a risk of energy supply shortage if no actions are taken. The spatial pattern of total annual building energy demand at the individual building level exhibited high spatial heterogeneity with some hotspots. This study provides an alternative method to develop a building energy demand inventory with high temporal resolution at the individual building scale for cities lacking energy use monitoring data, supporting the assessment of building energy and GHG emissions under both current and future climate scenarios at minimal cost.

The interconnection between the objectives of territorial development and those of the agro-ecological transition highlights the value of past knowledge in the sustainable management of resources and agro-ecological systems. However, the lack of data creates difficulties for retrospection in rural areas. This paper contributes to the search for such knowledge from the past by developing an interactive methodology capable of combining heterogeneous information sources with the activation of local collective memory. Its effectiveness is based on ensuring the interoperability of information and communication in an environment simultaneously shaped by geoinformatics and 3D geovisualisations. This virtual environment fostered participation and interactivity, supported by representations of the paleo-landscape (Ottoman period). Furthermore, synergies were achieved between information sources, which were integrated into local spatial systems. The application example involved identifying a rice field that existed between the 15th and 19th centuries in Thessaly, Greece. It is an interesting case because the research results indicated that the location and organisation of the crop, combined with the spatio-temporal coordination required, ensured the sustainable use of natural resources. The interplay between information and communication facilitated community participation and the activation of its collective memory as an information source that enriched the search itself and local intelligence.

This study presents a comprehensive analysis of natural hazard susceptibility in the Makedonska Kamenica municipality of North Macedonia, encompassing erosion assessment, landslides, flash floods, and forest fire vulnerability. Employing advanced GIS and remote sensing (RS) methodologies, hazard models were meticulously developed and integrated to discern areas facing concurrent vulnerabilities. Findings unveil substantial vulnerabilities prevalent across the area, notably along steep terrain gradients, river valleys, and deforested landscapes. Erosion assessment reveals elevated rates, with a mean erosion coefficient (Z) of 0.61 and an annual erosion production of 182,712.9 m3, equivalent to a specific erosion rate of 961.6 m3/km2/year. Landslide susceptibility analysis identifies 31.8% of the municipality exhibiting a very high probability of landslides, while flash flood susceptibility models depict 3.3% of the area prone to very high flash flood potential. Forest fire susceptibility mapping emphasizes slightly less than one-third of the municipality’s forested area is highly or very highly susceptible to fires. Integration of these hazard models elucidates multi-hazard zones, revealing that 11.0% of the municipality’s territory faces concurrent vulnerabilities from excessive erosion, landslides, flash floods, and forest fires. These zones are predominantly located in upstream areas, valleys of river tributaries, and the estuary region. The identification of multi-hazard zones underscores the critical need for targeted preventive measures and robust land management strategies to mitigate potential disasters and safeguard both human infrastructure and natural ecosystems. Recommendations include the implementation of enhanced monitoring systems, validation methodologies, and community engagement initiatives to bolster hazard preparedness and response capabilities effectively.

This study employs spatial theory to investigate rural social governance, revealing how it influences the spatial layout of rural settlements. By utilizing GIS spatial analysis and spatial autocorrelation methods, we systematically categorize and organize rural territorial spaces, developing an optimal regional planning system for rural areas. Through spatial econometric analysis, we examine selected villages’ comprehensive governance levels and ecological governance efficiency. Our evaluation focuses on five key areas: economic development, public services, social order, environmental livability, and overall governance effectiveness. Findings indicate a significant annual growth in the villages’ overall development level by 14.6%, with rural governance effectiveness improving from 0.819 to 0.859 between 2012 and now. Moreover, disparities in governance effectiveness within these areas are narrowing. This research broadens the scope of rural governance studies through a spatial lens, offering valuable insights and benchmarks for future inquiries.

Tourism is an important industry that promotes national economic and social progress. All-for-one tourism is a new concept of regionally coordinated development that uses the tourism industry as an engine to boost resource integration, industrial integration, and social sharing. Tourism service is the main embodiment of cultural ecosystem services for all-for-one tourism cities. Taking the city of Liyang in China as an example, this paper used a combination of GIS spatial analysis and big data text mining to evaluate tourism service from three aspects: the quality of tourism resources, the comprehensiveness of tourism service facilities, and the satisfaction of tourists. The results show that (1) tourism service is better in the northwestern and eastern areas of the city, while it is lower in the northeastern and southwestern parts; (2) the hotspot areas should focus on improving tour routes, transport capacity, and excessive charges; the cold spot areas should work on ecological restoration and creating new tourism attractions by combining the local industries; and (3) rural tourism integrating agriculture and visitation should be highlighted as a key growth point to improve the city's tourism service function. [ABSTRACT FROM AUTHOR]

Considering the United Nations’ Sustainable Development Goals (SDGs) and the need for a balanced spatial distribution of urban medical resources capable of perspective of hierarchical diagnosis and treatment, i.e. providing continuous and accessible medical services during potential public health emergencies, we assessed accessibility and service capacity of the three hospital levels in Beijing. Using geographical information systems (GIS) and the two-step floating catchment area method with the street as research unit, we found that there is an over-supply of medical resources in the centre of the city with weaker support in the peripheral areas as manifested by less supply in relation to popular demand of medical services. The spatial distribution of hospitals at all levels and their resources was found to be uneven: 82.4% of the residents can reach a tertiary hospital (a hospital offering advanced specialized medical and health services to multiple regions) within a 15-minute drive; 50.6% can reach a secondary hospital (a hospital offering comprehensive medical and health services to various communities) within a 10-minute drive; and 77.6% can reach a primary hospital (a hospital directly delivering prevention, medical treatment, healthcare, and rehabilitation services to the community of a certain population) within a 15- minute walk. It was noted that the supply/demand balance of medical resources in the tertiary hospitals decreases from the centre to the periphery, while the secondary hospitals show a dual-centre pattern and the primary hospitals a more uneven distribution, with oversupply in the East and the opposite in the Centre. The results of the study provide supplementary decision support for improving the hierarchical diagnosis and treatment system and accelerate the overall deployment of medical resources.

The study of climate element distribution models under complex terrain conditions is a popular topic in the field of GIS application in climatology, especially in plateau areas with a complex topography and scarce meteorological station information. In this paper, the spatial and temporal heterogeneity of temperature and precipitation at the northeastern edge of the Tibetan Plateau was analyzed by taking the northeastern edge of the plateau as the study area and constructing a topographic spatial statistical model using 47 meteorological stations and digital elevation models from 1981 to 2010. The following conclusions were drawn from the study: (1) The ME of the temperature distribution model for each month is below 0.9 °C; the maximum ME of the precipitation distribution model for each month is −5.808 mm in July, and the precipitation distribution model has similar error characteristics with the temperature distribution model, which can reflect the horizontal zone distribution pattern of meteorological data and can clearly show the changes of temperature and precipitation as the altitude increases. (2) The spatial distribution pattern of temperature is as follows: the temperature in the study area gradually increases from the southwest to the northeast, with Zhouqu County in Linxia Prefecture and Gannan Prefecture as the main high-temperature areas; the spatial distribution of precipitation is as follows: the precipitation in the southwest of the study area is significantly higher than that in the north, and the precipitation in Linxia Prefecture is significantly lower than that in Gannan Prefecture. (3) The temporal distribution pattern of the temperature distribution model is as follows: the overall temperature in the study area is at its lowest level in January, and the maximum temperature is only 2.6 °C, until July, when the maximum temperature rises to 24.2 °C and then gradually starts to decline; the spatial distribution of precipitation is as follows: the precipitation in the study area gradually rises from January, and the maximum precipitation rises to July and then starts to decline, and in December the precipitation falls to the lowest level. The temporal distribution characteristics of the precipitation distribution model are similar to those of the air temperature model, with obvious hydrothermal synchronization characteristics. [ABSTRACT FROM AUTHOR]

Recent discussions on flood disasters concern the risk factors and causes between nature and anthropogenic activities. This disaster requires serious handling, which needs to be analysed, especially in areas affected by flooding with the Tegal Regency, Indonesia case study. The weakness of the existing mitigation efforts still needed comprehensive analyses, requiring a multi-criteria assessment based on GIS spatial analysis. The GIS method used is a raster calculator and weighted superimpose by setting several calculation variables from both physical and non-physical aspects to support the multicriteria spatial analysis. The results show that spatially, more than 30% of areas with a high-risk index are located in the downstream or coastal regions of Tegal Regency. However, the index of capacity and resilience in several flood-affected sub-districts is at an index above 0.5, so they have good strength to disasters such as the four sub-districts of Adiwerna, Bumijawa, Bojong, and Kramat. From the analysis results, land use change is the biggest problem that affects the number of the flood event. With this condition, the appropriate mitigation effort for Tegal Regency is strengthening the spatial planning policy and increasing the capacity, especially in disaster governance in a high-risk area. Thus, the vulnerability and hazard factors will be anticipated with high community participation in strengthening the capacity index.

Recent discussions on flood disasters concern the risk factors and causes between nature and anthropogenic activities. This disaster requires serious handling, which needs to be analysed, especially in areas affected by flooding with the Tegal Regency, Indonesia case study. The weakness of the existing mitigation efforts still needed comprehensive analyses, requiring a multi-criteria assessment based on GIS spatial analysis. The GIS method used is a raster calculator and weighted superimpose by setting several calculation variables from both physical and non-physical aspects to support the multicriteria spatial analysis. The results show that spatially, more than 30% of areas with a high-risk index are located in the downstream or coastal regions of Tegal Regency. However, the index of capacity and resilience in several flood-affected sub-districts is at an index above 0.5, so they have good strength to disasters such as the four sub-districts of Adiwerna, Bumijawa, Bojong, and Kramat. From the analysis results, land use change is the biggest problem that affects the number of the flood event. With this condition, the appropriate mitigation effort for Tegal Regency is strengthening the spatial planning policy and increasing the capacity, especially in disaster governance in a high-risk area. Thus, the vulnerability and hazard factors will be anticipated with high community participation in strengthening the capacity index. [ABSTRACT FROM AUTHOR]

Creative industries, by their nature of innovation through creativity, add value to any territory by giving it spatial functionality, and at the same time, they favour sustainable development through the sustainability of the urban centres in which they operate. This paper develops a GIS methodology based on the implementation of a spatial analysis model that captures, in a comparative way, the spatial functionality of two different urban centres—(Cluj-Napoca (Romania) and Pécs (Hungary))—in terms of spatial extent based on the impact of the spatial distribution of creative industries. The spatial analysis model is based on the management of alpha-numeric databases representing the addresses of the creative industries, based on geolocation, for the development of spatial analyses of pedestrian accessibility. The main aim is to identify the specific areas of 15 and 5 min model cities. The comparative analysis was carried out by implementing a deterministic methodology through which the areas with certain degrees of accessibility were analysed in relation to the total analysed area, with the main aim of standardising the scale of analysis due to the difference between the two urban centres, thus facilitating the use of qualitative boning in the final comparison process. The results obtained highlight the local behaviour, at the same time making it possible to conduct a realistic deterministic comparative analysis of the two urban centres, which are also identifiable from the point of view of local territorial functionality, thereby validating the GIS model implemented in the present study.

Malaysians’ overall well-being, particularly in urban areas, has been seriously affected physically and emotionally due to the series of imposed lockdowns in the country. The number of mental health problems such as depression, anxiety, and loneliness has increased tremendously during the lockdown period. Various studies suggest that these mental health issues could be coped with if people are allowed to access urban greeneries and public green spaces during the pandemic. However, the degree to how adequate existing green areas are to fulfil an urban community’s needs with strict social distancing compliance is still vaguely interpreted in the literature. It is still arguable that the current 10 per cent green area requirement is still relevant to the current context of the COVID-19 pandemic. This study aims to determine the sufficient amount of green areas for people’s well-being during the pandemic, based on the local population, accessibility to green areas, and compliance with the new norm of social distancing by a minimum of one meter. Therefore, an urban neighbourhood in Iskandar Puteri, Johor, Malaysia was selected and simulated using GIS spatial analysis based on the highlighted parameters. As a result, the study found that the current size of existing green areas in the neighbourhood is insufficient in terms of compliance with the parameters, especially Malaysia’s social distancing requirements. This study could provide a platform for future planning to include pandemic risk reduction into urban planning policies, especially in the context of Malaysia, to cater to future uncertainties

Since China acceded to the WTO, the industrial economy of urban areas has experienced a prosperous phase. However, disturbed by the global financial crisis and reverse globalization since 2008, the past crude development path has been unsustainable. Therefore, it is urgent and necessary to improve industrial resilience to avoid falling into a declining trap. This study integrates multi-source spatiotemporal information such as enterprise big data and panel data using the methods of GIS spatial analysis, complex network analysis, and multi-indicator comprehensive evaluation to evaluate the industrial economic resilience of Taihu Lake Basin (TLB). Resistance indicators such as resistance sensitivity, industrial land area, and regional economic connections are used to evaluate the resistance ability of the industrial economy in the TLB during the 2008 financial crisis and the 2018 Sino-US trade conflict. Resistance sensitivity and independent innovation ability are introduced to assess the recovery ability after two rounds of shocks, and comprehensive economic resilience is evaluated based on the entropy weighting method. The results show that in the face of the two economic shocks, the industrial economy in the TLB is increasingly vulnerable to external economic shocks and has a significantly stronger ability to adapt to economic shocks. Under successive shocks, the industrial economy of the TLB continues to transition to a new path of innovation, which contributes to higher value-added and more efficient use of industrial land. Shanghai and Suzhou, which not only have shown strong economic resilience of their own but are also centers of independent innovation in the TLB, badly need to further reduce their reliance on low-end manufacturing in the future. Among the other cities, Huzhou and Zhenjiang show the highest level of resilience, while Changzhou, Wuxi, and Jiaxing are at the middle level, and Hangzhou is evaluated as the city with the lowest industrial economic resilience. Changzhou and Wuxi need to further increase the technical complexity of their industrial products, while Jiaxing, Huzhou, and Zhenjiang are supposed to strengthen their economic connections with Shanghai, Suzhou, and Hangzhou to expand the industrial scale further. Although Hangzhou shows the lowest comprehensive resilience, it still has a catalytic role to play in the development of industrial land and the upgrading and transformation of manufacturing in Jiaxing and Huzhou. [ABSTRACT FROM AUTHOR]

The sustainable development of tourism is essential for revitalizing historically and culturally significant ancient villages in China. Despite the longstanding recognition of the relationship between the spatial distribution of village destinations and their sustainable development, there is a dearth of longitudinal studies in village tourism. Using the geographic information system (GIS) spatial analysis method and the exploratory spatial data analysis model, this study explored the spatial-temporal features of ancient village tourism over three important time nodes of rural tourism development (in Zhejiang, China), as well as the contributing factors at both the provincial and prefectural city levels. The findings of this study suggested a spatial inequality in the distribution of ancient villages, in terms of tourism development over time. In particular, tourism development was clustered in the southern region, with a noticeable spillover effect. Meanwhile, transportation, source markets, and physical topography are essential factors contributing to this spatial distribution. The study contributes to ancient village tourism development literature and offers meaningful, practical implications for regional governments and business investors. [ABSTRACT FROM AUTHOR]

Land Use Land Cover (LULC) dynamics and the associated drivers are vehemently debated issues among scientific community due to its significant impact on global scale. Therefore, this study aimed to investigate the major trends and drivers influencing LULC change in District Abbottabad, Pakistan. Mixed method approach comprising of remote sensing, Geographic Information System (GIS) and household survey were employed to collect data from 130 households. Descriptive data was analyzed through index-based ranking. Further logistic regression was employed to examine the impact of perceived drivers of LULC change. Ranking of major perceived and proximate drivers identified were unplanned urbanization, natural conditions, agricultural decline and increase infrastructure. While population growth, lack of financial resources, poor marketing and weak governance were identified as underlying drivers of LULC change. Similarly, findings of GIS data revealed massive increase in built-up (3.12%) areas and urbanization at the expense of agricultural and bare land (-15.7%) between 1987 and 2019. [ABSTRACT FROM AUTHOR]

Abstract Background Nitrate contamination of groundwater often occurs in urban and industrial areas due to point and non-point sources of anthropological activities. Groundwater constitutes a a significant portion of the water supply system for Bahir Dar City in Ethiopia, though the level of groundwater pollution is not known. This study was conducted to assess the the extent of the aquifer and groundwater pollution (nitrate) based on contaminant vulnerability risk mapping using the GIS integrated modified DRASTIC model. A field survey was conducted to collect samples from boreholes for nitrate analysis and to modify the DRASTIC model. Results Compared to the original intrinsic vulnerability assessment, land use as external factors changed from moderate-high to high vulnerability class from 18 to 88%. The FR-APH modified model showed a good correlation (0.53) compared to the other methods. Based on the FR-APH modified model, about 31% of the area was under moderate to high and high vulnerability range, 39% was under moderate vulnerability range while 30% was under low and moderate to low vulnerability range. Conclusions The integrated vulnerability map showed high risk in the central part of the City due to the flat slope and shallow depth to groundwater. Besides, the sensitivity analysis indicated that the contribution of aquifer media and vadose zone to contaminant risk was found trivial. In general, groundwater at Bahir Darwas found vulnerable to nitrate contamination and needs proper management.

To carry out the diagnosis and evaluation of the ecosystem health in Yuxi three-lake watershed, this paper presents the changing trend of its health state, and predicts the future development. This also provides ideas for maintaining the regional ecosystem health, and then gradually improves the ecological environment quality. Taking Fuxian Lake, Qilu Lake and Xingyun Lake (the three-lake watershed) in Yuxi City, Yunnan Province, Southwest China as the research object, a model combining pressure-state-response and kernel density estimation (PSR-KDE) adopts to diagnose and evaluate the ecosystem health of the "three lake" watershed from 2010 to 2020, and the distribution map of ecosystem health index has obtained by the evaluation indexes integration based on GIS spatial analysis. Hence, the evaluation results have visualized on the map. The results show that: The distribution of ecosystem health index in the study area was 0.1530–0.7045 in 2010, 0.2056–0.7512 in 2015, and 0.2248–0.7662 in 2020. 0.12% was in the pathological area in 2010. After 2015, the pathological condition of ecosystem health has completely solved, and the proportion of unhealthy ecosystems was 11.95% in 2010, 7.38% in 2015, and 5.97% in 2020. The ecosystem health index of the study region was 0.5523 in 2010, 0.5807 in 2015, and 0.5815 in 2020, it indicates that the ecosystem was in a sub-health state. From 2010 to 2020, the ecosystem health around Qilu Lake was the most worrying, followed by the northwest of Fuxian Lake and the northern and southern regions of Xingyun Lake. The ecosystem health of the three-lake watershed showed significant improvement from 2010 to 2020. The study ecosystem health assessment and early warning in the three-lake watershed is significant to the ecological environment protection and management of the plateau lake basin, the restoration of the territorial space ecology and the economic development of the surrounding area. • Build the three-lake watershed ecosystem health evaluation model of PSR-KDE. • Ecosystem health of three-lake basin from 2010 to 2020 was diagnosed and evaluated. • Achieve a distributed effect on the map for ecosystem health. • In 2010, 2015 and 2020, the ecosystem of three-lake basin was in a sub-healthy state. • The government has been actively and vigorously maintaining the ecosystem health. [ABSTRACT FROM AUTHOR]

A scientific grasp of the macro law of coal mining accidents can contribute to strengthening their prevention and control and guaranteeing a stable energy supply. In this study, 2,269 investigation reports of China's coal mining accidents from 2005 to 2022 were adopted as the basic data source, and GIS spatial analysis and rescaled range analysis methods were utilized to comprehensively reveal the spatial-temporal distribution features, and evolutionary patterns of coal mining accidents in China. The findings indicate that the numbers of gas explosion, permeability, outburst, suffocation and roof fall accidents has rapidly declined. The coverage area of coal mining accidents has gradually moved toward western of China. However, the center of the area covered by coal mining accidents during the study period was mainly concentrated in Shanxi and Henan Provinces. Besides, the number of deaths resulting from coal mining accidents across the country has gradually decreased, while the time series exhibited high continuity, with future changes consistent with past changes. The average cycle period of the coal mining accident sequence was 5 years. Through the systematic analysis of coal mine accidents conducted in this research, the law of accident occurrence was more comprehensively revealed, providing a reference and basis for the government and enterprises to implement precise preventive measures. [ABSTRACT FROM AUTHOR]

Tourism is an important industry that promotes national economic and social progress. All-for-one tourism is a new concept of regionally coordinated development that uses the tourism industry as an engine to boost resource integration, industrial integration, and social sharing. Tourism service is the main embodiment of cultural ecosystem services for all-for-one tourism cities. Taking the city of Liyang in China as an example, this paper used a combination of GIS spatial analysis and big data text mining to evaluate tourism service from three aspects: the quality of tourism resources, the comprehensiveness of tourism service facilities, and the satisfaction of tourists. The results show that (1) tourism service is better in the northwestern and eastern areas of the city, while it is lower in the northeastern and southwestern parts; (2) the hotspot areas should focus on improving tour routes, transport capacity, and excessive charges; the cold spot areas should work on ecological restoration and creating new tourism attractions by combining the local industries; and (3) rural tourism integrating agriculture and visitation should be highlighted as a key growth point to improve the city’s tourism service function.

Exploring the influence range of early cities is significant for understanding the mechanisms behind ancient settlement systems and human-environment interactions. Due to a lack of effective research methods, the evolution processes and impact mechanisms of the influence ranges of prehistoric cities are still ambiguous. In this study, we chose the Songshan Mountain region for research, which witnessed the origin and development of Chinese civilization. Using GIS spatial analyses such as the 'average nearest neighbor' and 'Thiessen polygon', we explored the spatial-temporal distributions and influence ranges of Neolithic-Bronze Age cities in the region. The roles of human culture and the natural environment in the process were also investigated. The results indicated that the spatial distributions of early cities were random during the Yangshao (7000–5000 BP) and Longshan (5000–4000 BP) cultures. During the Erlitou culture (3800–3500 BP) and Shang Dynasty (3600–3046 BP), the spatial distributions changed into dispersed models. During the Zhou Dynasty (3046–2256 BP), the spatial distribution model was random again. Correspondingly, the influence range of early cities during the Erlitou culture is the largest, followed by those of the Longshan culture, Yangshao culture, Shang Dynasty, and Zhou Dynasty. This is different from the conventional view that the ancient city's influence range continuously expands as time advances. Both the natural environment and human culture are believed to impact this evolutional process. Specifically, the Holocene climate variation and the consequent cyclic river downcutting and silting affect the city site selection and thus the spatial-temporal distribution and influence range of early cities. The enfeoffment system occurring during the Erlitou culture should also have played a vital role in this evolution. In general, the natural environment is more important for the spatial distribution and influence range of early cities during Yangshao, Longshan, and Erlitou cultures, while human culture represented by the enfeoffment system plays a dominant role during Shang and Zhou Dynasties when the natural environment is relatively stable. [ABSTRACT FROM AUTHOR]

In low-altitude rescue, civilian helicopters, relying on their speed, efficiency and flexibility, play at center stage. Due to the terrain restrictions of the disaster area, it is difficult for helicopters to carry out safe and efficient rescue in cities. In order to facilitate emergency rescue, fixed helicopter takeoff and landing points for rescue missions must be selected strategically and wisely. However, the traditional method is to analyze the satellite data and conduct field surveys manually, which is rather subjective. A scientific, simple and efficient method of location selection is in urgent need. This paper analyzes the normativeness of the location of the helicopter's take-off and landing point and establishes a model of the slope and undulation of the landing site. It utilizes ArcGIS software to build layers and selects for the terrain element models that meet the specifications. It also studies the rescue radius commonly used in the world and then maximizes the location range of the take-off and landing point based on the greedy algorithm. Considering the construction cost, the final optimized site selection result is obtained. The results show that the use of GIS space technology can effectively select suitable take-off and landing points and gain valuable time for low-altitude rescue. [ABSTRACT FROM AUTHOR]

The study of climate element distribution models under complex terrain conditions is a popular topic in the field of GIS application in climatology, especially in plateau areas with a complex topography and scarce meteorological station information. In this paper, the spatial and temporal heterogeneity of temperature and precipitation at the northeastern edge of the Tibetan Plateau was analyzed by taking the northeastern edge of the plateau as the study area and constructing a topographic spatial statistical model using 47 meteorological stations and digital elevation models from 1981 to 2010. The following conclusions were drawn from the study: (1) The ME of the temperature distribution model for each month is below 0.9 °C; the maximum ME of the precipitation distribution model for each month is −5.808 mm in July, and the precipitation distribution model has similar error characteristics with the temperature distribution model, which can reflect the horizontal zone distribution pattern of meteorological data and can clearly show the changes of temperature and precipitation as the altitude increases. (2) The spatial distribution pattern of temperature is as follows: the temperature in the study area gradually increases from the southwest to the northeast, with Zhouqu County in Linxia Prefecture and Gannan Prefecture as the main high-temperature areas; the spatial distribution of precipitation is as follows: the precipitation in the southwest of the study area is significantly higher than that in the north, and the precipitation in Linxia Prefecture is significantly lower than that in Gannan Prefecture. (3) The temporal distribution pattern of the temperature distribution model is as follows: the overall temperature in the study area is at its lowest level in January, and the maximum temperature is only 2.6 °C, until July, when the maximum temperature rises to 24.2 °C and then gradually starts to decline; the spatial distribution of precipitation is as follows: the precipitation in the study area gradually rises from January, and the maximum precipitation rises to July and then starts to decline, and in December the precipitation falls to the lowest level. The temporal distribution characteristics of the precipitation distribution model are similar to those of the air temperature model, with obvious hydrothermal synchronization characteristics.

Scientific analysis of the spatial features and driving factors of homestead agglomeration in different landform types of mountainous and hilly areas in Southwest China is of great significance for the optimization of national spatial patterns and high-quality rural development. This paper selects 22 villages in 3 towns with different landform types in Chongqing and examines the spatial features and driving factors of homestead agglomeration in different landform types from the perspectives of terrain gradient, kernel density estimation, farmer household agglomeration status, and landscape index. We analyzed the agglomeration spatial features of different landform types and explored their driving factors and mechanisms. It was found that (1) the distribution of homesteads in mountainous and hilly areas has obvious terrain gradient characteristics, and the layout of platform area homesteads is not constrained by terrain conditions. (2) Chongqing homesteads show a spatially dispersed pattern, but the degree of homestead spatial agglomeration varies significantly among different landform types, with those in mountainous and hilly areas being mainly dispersed and those in platform areas being mainly clustered. (3) Homestead spatial agglomeration is characterized by a combination of factors inside and outside the rural system and farmers' willingness. There are differences in the driving factors of homestead agglomeration in different landform types. Homestead agglomeration in mountainous and hilly areas is mainly driven externally, while homestead agglomeration in platform areas is mainly driven internally. In both situations, farmers' willingness must be fully considered. The results of this study can provide a scientific basis for the spatial planning and optimal allocation of land resources in the southwestern hilly area. [ABSTRACT FROM AUTHOR]

Top-down emission reduction target setting results in inability of local governments to develop differentiated plans for emission reduction. Forests have received considerable attention as an important source of carbon sequestration, especially following China's commitment to carbon neutrality. However, studies have paid little attention to spatiotemporal differences of downscale forest carbon sequestration in China over the long term due to data limitations, while also ignoring the large differences in forest carbon sequestration per unit area among different regions. Here, a basic dataset of forest carbon sequestration among counties and grids in China is constructed and the temporal drivers and spatial differences of forest carbon sequestration were investigated from the perspectives of counties' administrative boundaries and 0.5 by 0.5 degree grid combining modelling, GIS spatial analysis and a decomposition method. Changes in forest land use between 2000 and 2020 were also analysed. The results highlight the importance of forests in managing carbon sequestration among all types of terrestrial vegetation and the differences in forest carbon sequestration per unit area. The scale effect increased forest carbon sequestration in the first two periods (2000–2005 and 2005–2010), followed by a decrease since 2010. The intensity effect promoted carbon sequestration; in particular, a dramatic increase was observed from the second (2005–2010) to the third period (2010–2015). The heterogeneity of the scale effect of forest carbon sequestration increased compared to that of the intensity effect, both from administrative and geographical divisions. The scale and intensity effects of counties located in the northern regions of northeast China enhanced forest carbon sequestration, while counties located in southern and central China inhibited it during the study period. The scale effect of grids changed from enhanced to inhibited forest carbon sequestration mainly in northeast China near 120°E, whereas the intensity effect of grids increased from inland regions in central China to eastern coastal regions during the study period. This study provides references for policymakers to set differentiated emission reduction targets considering the local forest carbon sequestration. • Local governments lack downscaled information on forest carbon sequestration. • Spatiotemporal differences in forest carbon sequestration are identified. • Remote sensing data facilitates down-scaling and long-term research. • The constructed dataset enables differentiated emission reduction targets setting. • Future work may focus on complementary remote sensing data from other platforms. [ABSTRACT FROM AUTHOR]

This study explores the '15-minute city' concept in Hamilton, New Zealand, focusing on challenges related to car dependency and urban sprawl. Triggered by the greater emphasis on sustainable urban environments following the global pandemic, the research employs a mobility-based approach to assess the model's applicability across various urban districts. Geographic Information System (GIS) mapping is used to identify 'liveable areas' in business, residential, and industrial districts where essential services are accessible within three different thresholds of 5, 10, and 15 min walking distance. This tiered approach offers a detailed view of urban accessibility, highlighting the practicality and varying implementation levels of the 15-minute city concept across diverse urban areas. Geolocated mobile phone data from 88,660 residents is analysed with a focus on 'inflow' and 'outflow' travel distances at both city and district levels. While the results reveal the practical challenges of implementing the '15-minute city' paradigm, they also show partial alignment of Hamilton's urban fabric with the paradigm, offering scope for adjustments to better suit the city's specific characteristics and residents' behaviours. The study highlights opportunities for enhancing the diversity and accessibility of amenities and improving public transportation and alternative transport options, all key factors for sustainable urban development. This adaptable methodology serves as a valuable reference for other cities in developing strategies for sustainable living. The study concludes that while Hamilton shows potential for transformation, a nuanced and locally focused approach is crucial. These insights contribute to the current new urbanist literature by providing a comprehensive city-district perspective, extending the discourse to include distances beyond the '15-minute city' and highlighting areas where further urban planning or intervention is necessary. [ABSTRACT FROM AUTHOR]

Broadly accepted categorical differentiations of urbanisation understand cities as well-defined objects containing urban spaces in contrast to their hinterlands. However, urbanisation's multidimensional complexity challenges these approaches in the context of increasing social issues marked by rapid urban expansion, uneven development, ways of life, inequality, commodification, etc., that require fresh scientific answers grounded in innovative empirical evidence. Here, we analysed the population-based and the land-use/land cover-based categorical understandings of urbanisation, looking at their origins and main shortcomings. Our analysis makes a generalised description of urbanisation's spatial complexity, with an emphasis on the problematic spatial delimitation of urban boundaries; urbanisation occurring in remote wild areas; and the missing third spatial dimension. We discuss these shortcomings based on recent scientific developments, providing reasons why the categorical approach needs to be changed and how. We propose a continuous indicator of urbanisation which is based on the accumulation of anthropogenic materials, a physical, rather than a spatial or demographic characteristic. Our proposal allows the analysis of socio-ecological systems' spatial organisation, pursuing comparative studies across geographies and times, informing globally generalisable patterns of urbanisation processes and giving a material body to address claims for sustainable urban development. • Demographic and land use-based urbanisation approaches separate space into urban and rural producing several shortcomings; • Urbanisation produces material structures, purposive objects like buildings and infrastructures that we call technomass; • Technomass describes the continuous spatial structure of urbanisation based on a physical property; • Technomass is measured by weight and/or volume per unit of space and time (Ton/km2, m3/hectare/year); • This operational conceptualisation places the process of material accumulation as the urbanisation's DNA. [ABSTRACT FROM AUTHOR]

The mobility of the rural population has become an important issue to address, which ensures proper connectivity for the rural population from their villages to market centers, urban towns, schools, and health facilities. The better connectivities can bring substantial economic and social changes among the masses that can be achieved through sustainable mobility planning. However, the sustainability of the mobility systems can only be expressed if the key indicators are identified appropriately to reflect its multiple aspects. This study proposes a novel mixed-method approach to exploring and ascertaining the socioeconomic indicators that the construction of rural roads has impacted. Rural road infrastructure often instigates direct or indirect socioeconomic impacts (SEIs) on the target population. Assessing and ascertaining SEIs pose a wide range of challenges considering their high number and qualitative and quantitative nature. Thus, a set of indicators have been identified in five different dimensions to deal with the sustainability in the mobility system for the rural population using a unique and novel way of geographical information system (GIS) and principal component analysis (PCA)-based multidimensional development framework. It proposes a mixed-method approach to identify the most significant criteria and subcriteria of the SEIs. The five dimensions of the rural development process considered in this study are transport, income, health, education, and neighborhood, which are analyzed and validated using geo-regression modeling. The applicability of this method has been demonstrated by employing a case study of rural roads. The findings of the study ascertain the status of impacted indicators to achieve sustainability. The study found relative impact/influence indicators, i.e., multidimensional development index (MDI) for various habitats of rural blocks of Jhunjhunu, Rajasthan. The eastern region of the Buhana block and region of the northern Khetri block are found to have very low and very high MDI value, respectively. The study found a strong and positive spatial correlation between rural block's proximity and the rural road network with its MDI value. [ABSTRACT FROM AUTHOR]

Background: Nitrate contamination of groundwater often occurs in urban and industrial areas due to point and non-point sources of anthropological activities. Groundwater constitutes a a significant portion of the water supply system for Bahir Dar City in Ethiopia, though the level of groundwater pollution is not known. This study was conducted to assess the the extent of the aquifer and groundwater pollution (nitrate) based on contaminant vulnerability risk mapping using the GIS integrated modified DRASTIC model. A field survey was conducted to collect samples from boreholes for nitrate analysis and to modify the DRASTIC model. Results: Compared to the original intrinsic vulnerability assessment, land use as external factors changed from moderate-high to high vulnerability class from 18 to 88%. The FR-APH modified model showed a good correlation (0.53) compared to the other methods. Based on the FR-APH modified model, about 31% of the area was under moderate to high and high vulnerability range, 39% was under moderate vulnerability range while 30% was under low and moderate to low vulnerability range. Conclusions: The integrated vulnerability map showed high risk in the central part of the City due to the flat slope and shallow depth to groundwater. Besides, the sensitivity analysis indicated that the contribution of aquifer media and vadose zone to contaminant risk was found trivial. In general, groundwater at Bahir Darwas found vulnerable to nitrate contamination and needs proper management. [ABSTRACT FROM AUTHOR]

Managing urban water in many cities becomes more challenging under impacts of climate change and urbanization. Low impact development (LID) measures have been increasingly recognized and applied thanks to their capability of tackling multi‐dimensional water problems associated with both quantity and quality issues. Yet, in China limited attention has been paid to guide the planning strategy of LIDs in the preliminary stage, which often suffers from inadequate and imprecise data and information. In this study, an approach integrating a GIS‐based spatial evaluation model, a fuzzy comprehensive evaluation module and a multi‐objective optimization algorithm, is proposed to prioritize the spatial distribution of LIDs (i.e., type, placement, and extent) at the subcatchment scale in a case study in Southern China. By evaluating the trade‐offs among runoff reduction, pollution control, and economic investment, the synergies, and combination strategies of four types of LIDs are explored. Knowledge gained from this study is necessary and beneficial for water planners and practitioners to improve LID planning efficiency under constrained conditions. [ABSTRACT FROM AUTHOR]

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Abstract Managing urban water in many cities becomes more challenging under impacts of climate change and urbanization. Low impact development (LID) measures have been increasingly recognized and applied thanks to their capability of tackling multi‐dimensional water problems associated with both quantity and quality issues. Yet, in China limited attention has been paid to guide the planning strategy of LIDs in the preliminary stage, which often suffers from inadequate and imprecise data and information. In this study, an approach integrating a GIS‐based spatial evaluation model, a fuzzy comprehensive evaluation module and a multi‐objective optimization algorithm, is proposed to prioritize the spatial distribution of LIDs (i.e., type, placement, and extent) at the subcatchment scale in a case study in Southern China. By evaluating the trade‐offs among runoff reduction, pollution control, and economic investment, the synergies, and combination strategies of four types of LIDs are explored. Knowledge gained from this study is necessary and beneficial for water planners and practitioners to improve LID planning efficiency under constrained conditions.