GIS-based Spatial Analysis Research Articles

An Analysis of the Spatiotemporal Distribution and Influencing Factors of National Intangible Cultural Heritage along the Grand Canal of China

Intangible cultural heritage (ICH) reflects a region’s history and culture, serving as a significant indicator of regional identity and cohesion. The Grand Canal Basin in China is rich in historical traditions, containing a rich array of ICH resources. Analyzing the spatiotemporal distribution characteristics and influencing factors of ICH within the Grand Canal Basin of China can provide a scientific basis for developing cultural industries and promoting sustainable regional economic growth. This study employed GIS-based spatial analysis methods, including kernel density estimation, the mean nearest neighbor index, and standard deviation ellipse, to investigate the spatiotemporal distribution of 504 national-level ICH items (including extensions) in the Grand Canal Basin of China. The results demonstrate the significant spatial clustering of ICH, with concentrations in high-density regions, particularly at the northern and southern ends of the canal. There is significant regional disparity in the distribution of ICH, with an uneven quantity and structure, predominantly featuring traditional skills and traditional drama categories. The average centroid shift of ICH exhibits a north-to-south oscillatory trajectory. However, overall, it demonstrates a southward-moving trend. This study also underscores the impacts of urbanization, population density, economic development, and transportation infrastructure on ICH distribution. Among these factors, urbanization exerts the strongest influence on the spatial distribution of ICH. The impact of the natural environment is relatively minor; however, it remains a significant element that cannot be overlooked during development. This research offers valuable data and insights for local governments and institutions to formulate evidence-based strategies for the protection and sustainable utilization of ICH resources, promoting sustainable cultural and economic development in the Grand Canal Basin.

Towards advanced sustainable criteria for choosing the best site for collecting solar energy in cities using multi-criteria GIS

Solar energy has become a prominent and crucial source of clean energy due to the increasing global demand for electricity. There is a prevailing global trend towards the construction of solar farms as a means of energy generation. This study aims to assess multiple criteria encompassing urban, environmental, and social aspects in order to ascertain the optimal site for constructing solar farms. The evaluation primarily focuses on characteristics such as topography, solar radiation, accessibility, land use, and proximity to roads and power stations. In order to acquire the necessary spatial fit model, the data was evaluated utilizing a Geographic Information System (GIS) program, and the criteria were subsequently consolidated into an integrated geographic information system. A comprehensive review of the existing body of literature reveals that environmental factors, specifically solar radiation and aspect, play a crucial role in determining the suitable places for the establishment of solar energy collection projects (Merrouni et al. in Energy Procedia 49:2270-2279, 2013; McKinney in J Student Res Environ Sci Appalac 4:1-14, 2014). Furthermore, other analysis factors such as proximity to built-up regions, closeness to power lines, and proximity to roadways are taken into account (Hott et al. in GIS-based Spatial Analysis For LargeScale Solar Power And Transmission Line Issues: Case Study of Wyoming, U.S. In: Proceedings of the 41st American Solar Energy Society Meeting, 2012; Effat in Int J Adv Remote Sens GIS 2:205-220, 2013). These criteria have an impact on the cost of solar farms. The objective of this study was to assess several aspects influencing the selection of an optimal location for a solar energy farm, taking into consideration the aforementioned criteria. The study was carried out in New Aswan city, utilizing data obtained from the Urban Planning Authority within the Ministry of Housing and Urban Development, as well as the New Aswan City AuthorityI generated cartographic representations and compiled quantitative data, which informed our selection of places that met the established criteria through the utilization of a Geographic Information System (GIS) software. Upon the conclusion of the study, numerous locations that satisfied the established criteria were selected. The present study focuses on regions with high capacity, and the findings are depicted in the form of spatial and objective maps. One of the primary benefits associated with the utilization of this methodology lies in its versatility, as it can be implemented across several domains. Furthermore, a straightforward adjustment of the criteria facilitates its application in the selection of optimal locations for wind farms.

Simplified Methodology for Assessing River Carrying Capacity Based on Land-Use Types

Land conversions or land use changes also become the main cause of the decline in Citarum River conditions. The relationship between river sustainability and its watershed carrying capacity plays a vital role in protecting watersheds to implement sustainable water resources management. Previous studies on river assessment for watershed management have predominantly focused on specific hydrological and/or technical results, rather than considering the process of the development of carrying capacity methodology due to land-use types. Motivated by this fact, the objective of this study is to develop a simplified carrying capacity methodology due to land-use types for sustainable river management by selecting the Upper Citarum Watershed (a main part of Citarum Watershed) located in West Java Province, Indonesia as an example of a study area. The conceptual framework development for watershed carrying capacity due to land-use types was designed the step-by-step methodology standard regarding the sustainable river management. The methodology of this study also used AHP method consisting of screening and selecting attributes, transforming and developing sub-indices, assigning weights, and formulating a runoff cumulative (Ccum) to examine standards and criteria for carrying capacity classification due to the changes of land-use types. The analysis revealed a significant change in the proportions of the various land use types of the study area. The conclusion is it integrates the measures of selected important land-use types to create a single dimensionless number of runoff cumulative and its classification, and a modified approach to communicate information on river status to the public and related policy makers. To advance future studies, it is necessary to develop a comprehensive evaluation and monitoring systems by using GIS-based spatial and temporal analysis.

Intoxication in the city: Investigating spatial patterns and determinants of drugs and alcohol-related illegal activities in India's geostrategic corridor

Illicit drug and alcohol-related activities pose significant challenges to metropolitan centres globally, impacting public safety and socio-economic stability. This research analyzes the spatial and temporal patterns of drugs and alcohol-related illegal activities (DARIA) in Siliguri, known as the "Gateway of North-East India." The primary objectives are to explore DARIA patterns, identify clusters and concentrated areas, and investigate contributing factors. Using GIS-based spatial analysis and geographical models, we studied incidents recorded over three years from 2021 to 2023. Advanced spatial statistical approaches were applied to identify specific clusters of DARIA occurrences. The pure temporal analysis highlighted periods of increased illegal activity. Various geographical models, including ordinary least squares (OLS), geographically weighted regression (GWR), and multiscale geographically weighted regression (MGWR), were used to examine the spatial association. The MGWR model, with an explanatory power of R2 = 0.816, provided a detailed understanding of spatial relationships and variations in DARIA. Our findings indicate specific zones with frequent DARIA occurrences, mainly near major transportation hubs, commercial points, and areas with significant mobility. Key exploratory factors such as illiteracy rate, population density, proximity to playgrounds and slums were highly associated with DARIA incidents. These findings contribute to developing safer, more resilient, and more sustainable cities worldwide.

Optimal site selection and potential power assessment for tidal power generation in the Seto Inland Sea, Japan, based on high-resolution ocean modelling and multicriteria analysis

In response to Japan's ambitious pursuit of carbon neutrality by 2050, this paper investigates the potential for tidal power generation in the Seto Inland Sea (SIS), Japan, utilising high-resolution ocean modelling and an analytic hierarchy process (AHP) combined with GIS-based spatial analysis. The analysis incorporates a 100 m resolution tidal current and water depth layers from the ocean model. The criteria used for evaluation were divided into main criteria, namely, proximity to existing infrastructure, wave height, and shipping density, and subcriteria, namely, distance from ports, power stations, highly populated areas, and coastlines. The identified optimal locations include the Naruto Strait, Akashi Strait, Matsushima Island, Hanaguri Strait, Funaori Strait, Taizaki Island, Kurushima Strait, Obatake Strait, and Tsuwaji Strait. With a focused analysis of the Obatake Strait in Yamaguchi Prefecture, analytical assessments of potential tidal power were conducted by considering two tidal turbines, Openhydro and Voith. The results indicate a power supply for approximately 100,000 households and a reduction of approximately 198,000 t-CO2 per year in the most optimistic scenario. In a less optimistic scenario, with the installation of only 10% of the maximum capacity, a power supply for approximately 10,000 households and a reduction of approximately 19,800 t-CO2 per year are observed. As Japan targets carbon neutrality by 2050, this research offers vital and practical insights for policymakers, energy planners, and environmentalists, identifying the Seto Inland Sea as a strategic area for tidal power development, aligning with Japan's commitment to a sustainable and resilient energy landscape.

The Influence of Land Use and Slope Variation to Soil Infiltration Rate on Semarang City, Indonesia

Abstract From 2018 to 2022, there have been 3 floods in Gunungpati District. One factor that influences flood in this area is the infiltration rate. Many factors influence infiltration rates, two of them being land use and slope. This study aimed to determine the distribution of land use and slope gradient in Gunungpati District using GIS-based spatial analysis. The results show that land use in the research area is divided into 5 classes: primary and secondary dry land forests; plantations; shrubs and grasslands; dryland farming; and settlements, paddy fields, bodies of water, and open land. Land use is dominated by settlements, paddy fields, bodies of water, and open land (33.7% of the total area). The slopes in the study area are divided into 5 classes: flat (<8%), gentle (8—15%), wavy (15—25%), steep (25—40%), and very steep (>40%). The wavy class dominates the slopes (29.3% of the total area). Based on these results, a moderate infiltration rate dominates the infiltration rate in the study area.

Hydrogeochemical Evaluation of Groundwater Quality and Its Applicability for Various Purposes in the Drought-Prone Konso Zone, Rift Valley, Southern Ethiopia

The present study area, the Konso Zone, is in Rift Valley, Southern Ethiopia, and highly depends on rivers and groundwater for economic and social development. Water availability in this area faces multiple challenges, including scarcity, quality concerns, and seasonal variations. In the Rift Valley region, including the present study area, groundwater quality is particularly problematic due to high fluoride levels. Moreover, the high concentrations of total dissolved solids in Konso Zone groundwater pose challenges for industrial, agricultural, and drinking purposes. GIS-based spatial analysis techniques, hydrogeochemical analyses, and water quality indices were used in the current study. The evaluation of water quality involved the utilization of both groundwater quality and irrigation water quality indices. In the study area, the cations and anions exhibited a general trend with Na+ > Mg2+ > Ca2+ > K+ > Fe2+ and HCO3− > Cl−, SO42− > NO3− > F−. Multiple water types were identified within the research area, including Na-HCO3, Ca-Na-HCO3, NaCl, and Ca-Mg/Cl, with Na-HCO3 being the most prevalent. The formation of the NaHCO3 water type is primarily attributed to ion exchange processes, with siliciclastic aquifers being linked to cation exchange in sodium bicarbonate groundwater. Total Dissolved Solids and SO42− contaminants significantly impact the water quality, resulting in deterioration. Gibbs’s figure indicates that 50% of the water samples were found where rocks were weathered, demonstrating the importance of water-rock interactions in groundwater composition. Water samples containing more fluoride than the WHO’s limit of 1.50 mg/L were deemed unsuitable for consumption. Regarding irrigation suitability, most water samples from the Konso area were acceptable, except for the sodium percentage in 66.6% of the samples, which was unsuitable for irrigation. There are 26.67% of samples that are of questionable quality, 66.67% that are deemed inappropriate, and 26.67% that are deemed unacceptable. These findings underscore the pressing need for comprehensive strategies and interventions to address water quality issues in the Konso Zone, emphasizing the critical importance of monitoring and managing groundwater resources to ensure sustainable and safe water access for various regional uses.

Spatial patterns and trends of inter-city population mobility in China—Based on Baidu migration big data

Based on Baidu migration big data from the Spring Festival travel rush periods in 2022 and 2023, this study employs a combination of GIS-based spatial statistical analysis and social network analysis to analyze over 270,000 travel data records covering 297 prefecture-level cities. The research reveals that the population flow during the 2023 Spring Festival travel rush increased both in overall quantity and in the proportion of inter-provincial population flow compared to the same period in 2022. The distribution of population movement shows a distinct “southeast dense, northwest sparse” pattern, forming a diamond-shaped structure with the Bohai Sea Rim, Yangtze River Delta, Pearl River Delta, and Sichuan-Chongqing regions as the vertices. Among the most significant inter-city mobility routes are Guangzhou ↔ Foshan, Shenzhen ↔ Dongguan, Shanghai ↔ Suzhou, Xi'an ↔ Xianyang, and Beijing ↔ Langfang, which constitute the five routes with the highest flow volumes, each with its own distinctive patterns and characteristics. Significant agglomeration effects in population movement are observed, with the majority of the 40 cities experiencing higher net inflows situated in the Yangtze River Delta and Pearl River Delta regions. On the other hand, many cities in the western and northeastern regions, including some third-tier and even second-tier cities, are facing net population outflows. As the working population and major economic activities increasingly concentrate in large-scale central cities, the future development of prefecture-level cities may gradually diverge.

Investigation of climate change by analysing the rainfall pattern in kuzhithuraiyar sub-basin of India using GIS-based spatial analysis

Global climate change may have a significant effect on several environmental components in many different nations worldwide. Variations in the pattern of precipitation have an immediate impact on the management of water resources. To improve water resource management techniques, it is critical to investigate differences in the temporal and geographical rainfall patterns. The current study looks at rainfall patterns in the Kuzhithuraiyar sub-basin of the Kodayar basin, Kanyakumari District. Utilizing the mean monthly data from four distinct rain gauge locations, we have comprehensively compiled and analysed rainfall statistics over an extensive timespan of 30 years (1991–2020). For precision in temporal categorization, this data was meticulously divided into four seasonal classifications: pre-monsoon, post-monsoon, southwest monsoon (SW), and northeast monsoon (NE). Using ArcGIS 10.8, the rainfall pattern was analysed, and spatial distribution maps for the four seasons listed above were created using the inverse distance weighting (IDW) approach. The region receives an average of 1456.78 mm of precipitation each year, with the post-monsoon, pre-monsoon, SW monsoon, and NE monsoon providing 32.87 mm, 335.28 mm, 538.67 mm, and 549.97 mm, respectively. The results reveal that the model correlates mean rainfall and rainfall variability over areas of Tamil Nadu's Kuzhithuraiyar sub-basin with some accuracy in terms of the number of rainfall extremes and their spatial distribution maps.

Spatial-Based Landslide Vulnerability Index Assessment in Bogor Area, Indonesia

Within the concept of disaster risk, vulnerability is one of the key determinants. It acknowledges the degree of unsafe conditions in a susceptible zone so that mitigation measures and disaster resilience can be enforced. Bogor area is the most susceptible region to landslides with more than 485 landslide events since 2012. However, there is still inadequate information on its vulnerability to landslides, as the risk reduction challenge per se, is a long-run task. Correspondingly, this study aims to measure the degree of vulnerability to landslides in Bogor area from four focal points (i.e.: social, physical, economic, and environmental dimensions), through the proxy of Vulnerability Index (VI). This study employs a GIS-based spatial analysis on a sub-district level. The result shows that although having high records on landslide events, Bogor area mainly retrieves low VI. In general, Bogor area has low VI [0.347–0.454] on 26 sub-districts. Moreover, 13 sub-districts attain medium VI (0.454–0.562], and 7 sub-districts achieve high VI (0.562–0.670]. Sub-districts that have high VI are: Bogor Tengah, Bogor Barat, Bogor Selatan, Cibinong, Bojonggede, Ciomas, and Bogor Utara; which are mainly promoted by the high indexes on social and physical vulnerabilities. Nevertheless, further study is still needed to extend the knowledge of relationship between landslide susceptibility and this vulnerability result, by using a more extensive and longer data series. That is especially in accord with taking the appropriate mitigation measures in spatial planning and landslide risk management.

GIS-based spatial analysis for lightning scenario in Bangladesh

Bangladesh has witnessed alarmingly rising lightning frequency, particularly during pre-monsoon and monsoon seasons. This has resulted in significant annual death tolls from lightning strikes over the past decade. Recognizing this crisis, the country officially declared lightning casualties a natural disaster in 2016. This study delves deeper into the landscape of lightning fatalities and causalities in Bangladesh. Utilizing secondary data sources, this research introduces a unique approach by integrating Bangladesh Meteorological Department (BMD) data and NASA's Lightning Imaging Sensor (LIS) data from the International Space Station's (ISS) Near-real Time (NRT) mission. This combined dataset allows for a more comprehensive analysis. Furthermore, Geographic Information Systems (GIS) was employed to analyze spatial distributions and generate maps. The Inverse Distance Weighted (IDW) interpolation tool was used to create detailed spatial distribution maps of lightning fatalities, thunderstorm days (TSDs), and lightning flash frequency (LFF) across Bangladesh. The analysis revealed that farmers and fishermen were the most vulnerable populations, with the northeastern regions experiencing the highest impact. Sylhet division emerged as the area with the most fatalities, highlighting the northeastern zone's susceptibility. The study also identified monsoons as the period with the highest occurrences of lightning deaths and injuries. By combining innovative data integration and spatial analysis, this study offers valuable insights into the alarming trend of lightning fatalities in Bangladesh. These findings can inform targeted prevention strategies and interventions to safeguard vulnerable populations and communities.

A study on GIS-based spatial analysis of emergency response for disaster management: Focusing on Seoul

This study aims to analyze the operation of fire emergency dispatch, understand the impact of golden time on fire emergency dispatch, and identify factors and improvement measures for effective fire emergency dispatch with in prime time. According to the results of the study, rescue dispatch activities varies depending on the nature of the incident. The summer season had a higher number of calls than other seasons, and Saturday was the day of the week with the highest number of calls (i.e., Spring: 13,189, Summer: 15,652, Fall: 13,128, Winter: 14,545). When analyzing the spatial distribution of rescue incidents, it is found that rescue incidents were concentrated in some areas. In particular, the arrival time tended to be relatively long in areas south of the Han River and in areas where some fire stations or safety centers were not deployed. Results showed that rescue incidents dispatched by the stations other than neighboring stations were also concentrated in certain points. Based on these findings, the following policy implications can be drawn: first, the location of fire stations or safety centers should be adjusted; second, dispatch personnel and equipment should be strengthened; third, interagency cooperation should be strengthened; and fourth, prevention and education programs should be strengthened. Implementing these policy recommendations will improve fire emergency services' efficiency and response capabilities and minimize the occurrence and damage of life-saving events.

GIS-Based Spatial Analysis Model for Assessing Impact and Cumulative Risk in Road Traffic Accidents via Analytic Hierarchy Process (AHP)—Case Study: Romania

On a global scale, traffic incidents are a leading cause of mortality and material damage. Romania exhibits the highest rate of road traffic fatalities both in the European Union and worldwide, requiring a comprehensive examination of its overall influence on a national level. The current study uses an extensive approach centering on a spatial analysis model based on the Analytic Hierarchy Process (AHP). Employing a series of spatial databases, this model delineates the geographical distribution and characteristics of road accidents to establish both their cumulative national impact and the identification of high-risk areas. The spatial database, containing traffic incident data, is constructed using geolocation techniques and integrated through network analysis to evaluate the impact in relation to distance. The AHP framework is applied in analyzing the impact across five key dimensions: accident severity, occurrence mode, prevailing weather conditions, traffic restrictions, and road markings. This multi-level AHP analysis not only identifies high-risk hotspots but also confirms the effectiveness of the proposed spatial model.

Mapping areas suitable for agriculture and their accessibility: The case of the centre region of Cameroon

Given the pressure on land in the Central Region due to economic development and the search for opportunities, the best land for agriculture needs to be identified, so as to preserve it from urbanization, the expansion of mining areas, infrastructure and other occupations. It is in this context that the issue of mapping to identify agricultural zones and assess their accessibility was raised. This is an opportune moment to feed reflections on planning, agricultural production and natural resource management in the Center Region of Cameroon. GIS-based multi-criteria spatial analysis of data on land use, hydrographic network, slopes, soils and their suitability for cultivation provided precise, geolocalized information on land potentially suitable for agriculture in general. Following the analyses, we were able to establish and highlight the areas suitable for agriculture and accessible, which amounted to 8%, or 5662.42 km2 for high-potential and accessible areas. This was followed by 56%, or 37144.95 km2 for medium-potential and accessible zones, and finally 6%, or 4238.93 km2 for low-potential and accessible zones. Once the accessible areas had been removed, 5% or 3028.27 km2 of high-potential inaccessible areas remained, 19%, that is 14639.46 km2 of medium-potential inaccessible areas and 2% that is 967.12km2 of low-potential inaccessible areas.

Enhancing Public Space Accessibility and Inclusivity in Residential Neighbourhoods: A Methodological Framework and Pilot Application

The paper adds to the debate on urban transformation, which plays a significant role in improving quality of urban life and liveability of public spaces, as also stated in UN Sustainable Development Goal No. 11. The research aims to test a methodology for identifying an abacus of urban regeneration interventions to enhance attractive and critical nodes through accessibility and inclusivity. The quality of the system of connections between polarities, the promotion of active mobility, zero soil consumption and the renaturalisation of urban spaces are fundamental criteria to define urban regeneration solutions. The proposed approach develops on two levels: a GIS-based spatial analysis of urban data and a participatory process. The innovative planning process is tested on the San Leonardo neighbourhood in the Municipality of Parma, Italy, which allows us to verify the potentials and limitations of the procedure, identifying future work perspectives. Moreover, the application allows us to check the replicability in other urban contexts, possibly envisaging other applications to more case studies. Our results consist of the identification of the vocations and the critical aspects of nodes and axes to regenerate urban space in medium-sized and large cities’ suburbs.

Measuring the Potential and Realized (or Revealed) Spatial Access from Places of Residence and Work to Food Outlets in Rural Communities of Québec, Canada

This study aims to bridge the gap between the potential and realized spatial access to food outlets in rural areas of Québec, Canada. By assessing both aspects, this research aims to provide a comprehensive understanding of the challenges faced by rural communities in accessing food resources and the effectiveness of existing interventions in addressing these challenges. A mixed methods approach was adopted to collect and analyze data, combining GIS-based spatial analysis with community-based surveys. The spatial analysis allowed for the quantification of the potential access metrics, while the community surveys provided valuable information on travel behaviors, preferences, and barriers experienced by residents when accessing food outlets. The results of the distance measurement calculations showed that for both the potential and realized distance measurements, convenience stores are more easily accessible than grocery stores and supermarkets. Thus, workers seem to have a strategy for minimizing the impact of long distances by combining work and grocery shopping. These results are measured for the realized accessibility to grocery stores and supermarkets and the principal retailer used. Finally, the results of the analyses show that there is a socio-economic gradient in the potential geographical accessibility from home to the food outlets. The importance of developing and strengthening the local food environment to make it favourable to healthy eating and supportive of food security is discussed.

Nitrogenous Compound Exposure in Unsanitary Rural Environments: A Case Study from Al Hoceima Province, Northern Morocco

Groundwater is a crucial drinking water resource for rural communities; however, the absence of adequate monitoring programs in these regions often results in uncertainties about groundwater quality. This study focuses on assessing the impact of nitrogen compounds from domestic wastewater on groundwater in rural communities within the province of Al Hoceima. The hydrochemistry of 33 groundwater samples was analyzed using various methods, including descriptive statistics, the Nitrate Pollution Index (NPI), the Chronic Health Risk Index (CHR), and a GIS-based spatial analysis. The investigation revealed significant contamination by nitrogen compounds in regions characterized by high population density. In these areas, nitrate (NO3-) and nitrite (NO2-) concentrations exceeded 50 mg/l and 0.2 mg/l, respectively, surpassing the WHO recommended limits. Notably, NO3- levels ranged from 0 to 89.63 mg/l, with 84.84% of groundwater samples contained more than 10 mg/l. The NPI values ranged from -1 to 3.48, with 33.33% of the samples were categorized as significantly and very significantly polluted. Additionally, CHR values ranged from 0 to 2.43 for adults, 0 to 2.03 for children, and 0 to 2.51 for infants. The CHR values exceeded 1 suggests that the contamination observed in the samples can be attributed to the widespread use of septic tanks in densely populated regions. Thus, to ensure the safety of rural communities, further assessments of health risks are mandatory.

Exploring Road Traffic Accidents Hotspots Using Clustering Algorithms and GIS-based Spatial Analysis

Exploring Road Traffic Accidents Hotspots Using Clustering Algorithms and GIS-based Spatial Analysis

GIS-integrated multi-criteria suitability anal¬ysis for healthcare facilities site selection in Rajouri district, Jammu and Kashmir, India

The study aims to develop a Decision Support model for the selection of a suitable site to establish a new healthcare center with adequate facilities based on the analytical hierarchy process (AHP) in the Rajouri district of Jammu and Kashmir. This study utilized AHP and GIS to identify an appropriate location for a new healthcare center. The study employed eight criteria to evaluate potential locations and utilized pairwise comparison to assign weights to each criterion. GIS-based spatial analysis was used to create factor and suitability maps for each criterion. Suitability was evaluated on a scale of 0 to 10 and each factor map was combined using the ArcGIS weighted overlay selection tool. The final map of the study represents the suitable site for a healthcare center in the Rajouri district and it shows the sites from the highly suitable to the least suitable area. In Rajouri district, mostly the central part can be considered very suitable as the population density of this area is higher compared to other areas of the district. The southwestern parts of the district are moderately suitable or least suitable sites for a new healthcare center. The study displays the pattern of the existing location of healthcare centers, mostly, the existing locations are not proper and suitable. Therefore, in the future, the allocation of healthcare centers must be in more adequate areas. Policymakers and healthcare professionals can be benefitted from this study in selecting suitable locations for future hospitals, which could ultimately improve access to healthcare services in the region. Additionally, the study can be contemplated in developing new policies for better transportation system in the study area.

The impact of urbanization on urban flood risk of Nakhon Ratchasima, Thailand

Urban flooding is a hazardous consequence of urbanization, climate change, and spatial factors. It occurs when people gather in specific areas, disrupting natural and built environments. Despite its importance, the manner in which urbanization transforms land use patterns and overall land topography, contributing to the uncertainty of urban flooding, remains unclear. This study presents a comprehensive spatiotemporal assessment of the impact of urbanization on urban flood risk based on the Urban Flood Risk Triangle Index (UFRTI) of Nakhon Ratchasima, Thailand, in 2000, 2010, and 2020. The study developed this assessment framework through spatial analysis using Bivariate Local Indicators of Spatial Association and K-means clustering analysis. The revised parameters for urban flood hazard, exposure, and vulnerability constitute the UFRTI, illustrating how urbanization influences the degree and characteristics of urban flood risk. This study highlights the potential of using BiLISA and K-means clustering in GIS-based spatial analysis that reveals flood risk characteristics are shifting towards the city's periphery, requiring land use regulations and efficient flood risk management to confront urban growth.