Spatial Analysis Techniques Research Articles

Spatial dynamics of Culex quinquefasciatus abundance: geostatistical insights from Harris County, Texas

Mosquito-borne diseases pose a significant public health threat, prompting the need to pinpoint high-risk areas for targeted interventions and environmental control measures. Culex quinquefasciatus is the primary vector for several mosquito-borne pathogens, including West Nile virus. Using spatial analysis and modeling techniques, we investigated the geospatial distribution of Culex quinquefasciatus abundance in the large metropolis of Harris County, Texas, from 2020 to 2022. Our geospatial analysis revealed clusters of high mosquito abundance, predominantly located in central Houston and the north-northwestern regions of Harris County, with lower mosquito abundance observed in the western and southeastern areas. We identified persistent high mosquito abundance in some of Houston’s oldest neighborhoods, highlighting the importance of considering socioeconomic factors, the built environment, and historical urban development patterns in understanding vector ecology. Additionally, we observed a positive correlation between mosquito abundance and neighborhood-level socioeconomic status with the area deprivation index explaining between 22 and 38% of the variation in mosquito abundance (p-value < 0.001). This further underscores the influence of the built environment on vector populations. Our study emphasizes the utility of spatial analysis, including hotspot analysis and geostatistical interpolation, for understanding mosquito abundance patterns to guide resource allocation and surveillance efforts. Using geostatistical analysis, we discerned fine-scale geospatial patterns of Culex quinquefasciatus abundance in Harris County, Texas, to inform targeted interventions in vulnerable communities, ultimately reducing the risk of mosquito exposure and mosquito-borne disease transmission. By integrating spatial analysis with epidemiologic risk assessment, we can enhance public health preparedness and response efforts to prevent and control mosquito-borne disease.

Impacts of environments on school myopia by spatial analysis techniques in Wuhan

The prevalence of myopia in China has increased significantly in recent years, and the age of onset has become younger. Previous studies have indicated that various environmental factors can influence the development of school myopia. However, the environmental impacts on school myopia remains to be investigated. Discoveries in this field may contribute to better urban planning. This study involved 7,610 students (aged 6–12 years, 4084 boys and 3526 girls) from six primary schools in Wuhan, China. We evaluated the associations between school myopia and the environment by analyzing the geographical distribution of myopic children. We utilized the spatial statistical analysis model. The Normalized Difference Vegetation Index (NDVI) risk coefficient for a 5,000-m radius around target schools was 0.379 (p = 0.008), while the NDVI risk coefficient for a 100-m radius around target schools was 0.241 (p = 0.047). The sports area risk coefficient for a 5,000-m radius around target schools was 0.234 (p = 0.016). We found that the specific buffers of NDVI and sports area around schools were associated with the prevalence of school myopia in schools, which worth further research to guide future initiatives on school myopia from an environmental perspective.

Geographic Determinants and Spatial Epidemiology of Prescription Drug Abuse: A Comprehensive Analysis of Distribution Patterns, Treatment Accessibility and Intervention Strategies

This study examines the complex spatial patterns and geographic variations in prescription drug abuse, analyzing their impact on treatment outcomes and public health interventions. Through comprehensive spatial epidemiological analysis, we investigate how geographic factors influence abuse patterns across urban, suburban, and rural landscapes. The research synthesizes data on healthcare accessibility, socioeconomic conditions, and regional policy frameworks to understand their collective impact on prescription drug misuse. Our findings reveal significant geographic disparities in treatment accessibility, with rural areas facing substantial barriers to addiction services compared to urban centers. Analysis of prescription drug monitoring programs demonstrates varying effectiveness across regions, highlighting the need for spatially-tailored interventions. The study identifies distinct regional profiles of drug misuse, influenced by factors including healthcare infrastructure, cultural norms, and local regulatory environments. Advanced spatial analysis techniques, including geospatial mapping and hotspot analysis, revealed significant correlations between geographic determinants and abuse patterns. Results indicate that proximity to healthcare facilities, pharmaceutical distribution networks, and demographic characteristics contribute to localized risk profiles. The integration of multiple data sources, including prescription records and treatment admissions, provided insights into space-time clustering of abuse patterns. This research emphasizes the importance of developing geographically-informed approaches to combat prescription drug abuse, suggesting that intervention strategies should be tailored to specific regional contexts while addressing broader systemic issues. The findings have significant implications for public health policy, healthcare resource allocation, and the development of targeted prevention strategies.

On Optimization of Factory Space Configuration

In factories, spatial configuration plays an important role in order to improve workers’ comfort which will result in maximising the productivity and at last will contribute to economy generation. With the goal of identifying the major variables influencing shoe factories' spatial layout choices, this study explores the spatial arrangement and organization of shoe factories. By analyzing a cluster of shoe manufacturing plants located in Agra in India through site visit and international case studies in Bangladesh, this study examines how factors such as workflow process, machinery placement, storage areas and logistical considerations impact the spatial arrangement of factories. With the help of workers and factory officials interviews in shoe factories, site visits, and spatial analysis techniques this research provides insights into the actual indoor environment of the factories in terms of spatial arrangement. This actual indoor environment is further comparatively analysed by existing standards for industrial buildings which helped to find out the potential areas for improvement. The findings of this research work aim at identifying the potential areas and best practices for improvement in spatial configuration of shoe factories which will contribute to workers’ comfort.

Assessing the Gap: Resource Efficiency of Institutionalised Elderly Care in Urban and Rural China

ObjectivesThe allocation of resources in elderly care institutions is directly linked to the well-being, quality of life and sustainable development of public health for the elderly. However, a disparity in elderly care resources between urban and rural areas exists. Therefore, this study aimed to explore resource allocation efficiency in China's urban and rural institutional elderly care. Study DesignEmploying a mixed-methods approach, the research integrated quantitative analysis with spatial-temporal assessments to investigate spatial-temporal evolution patterns of resource allocation efficiency. MethodsA Projection Pursuit Evaluation Model (PPM) utilising an Accelerated Genetic Algorithm was applied to measure the input and output of urban and rural elderly care institutions. Data Envelopment Analysis (DEA) was used to visualise the static and dynamic efficiency. Spatial analysis techniques determined the spatial evolution of resources. ResultsSignificant disparities in resource allocation between urban and rural areas were identified, with rural areas facing declining numbers of elderly care institutions despite having a larger ageing population. The efficiency analysis revealed room for improvement in both urban and rural settings, emphasising the need to strengthen management and technology in elderly care institutions. ConclusionsAddressing the challenges of elderly care in China requires policy reform, enhanced government support and stimulation of private investment, particularly in rural areas. A shift towards quality-focused elderly care and strategic investments is crucial for equitable and efficient service provision across China.

The positive influence of Tibetan Buddhist monasteries on forest conservation

The Qinghai-Tibetan Plateau (QTP) is vital for stabilizing climate in East and South Asia and its glaciers and snow meltwater nourish key continental rivers. The region’s forests are not only ecologically essential but also fragile. The practices of local herdsmen, shaped by long-standing cultural traditions, significantly affect forest dynamics. This study examines the vital role that Tibetan Buddhist monasteries play in forest conservation on the QTP. We utilize data sources including extensive field surveys and geospatial data to assess the impact of monastery and village locations on forest conditions. Spatial analysis techniques, such as Moran’s I and Ripley’s K function, reveal significant clustering of monasteries and villages, which are closely linked with forest conditions. Our findings indicate that forests near Buddhist monasteries have higher aboveground biomass and better quality compared to other areas, suggesting that their presence supports better forest conservation practices. This positive influence is attributed to the cultural significance of these sites and the environmental consciousness promoted by Buddhist cultural teachings. Additionally, this study employs analytical methods including Random Forest and Partial Least Squares Structural Equation Modeling (PLS-SEM) to explore the drivers of forest quality. Initial aboveground biomass, climatic factors, and monastery density emerge as key influences on forest quality within monastery buffer zones, indicating that cultural factors are crucial in shaping forest landscapes.

Study on Changes in Comprehensive Land Prices for Expropriation Zones Based on Land Use Changes

Comprehensive land prices for expropriation zones can effectively alleviate many conflicts in China’s land expropriation practices. This contributes to achieving sustainable development goals such as “SDG-10: Reduced Inequalities” and “ SDG-11: Sustainable Cities and Communities”. The reasonable delineation of expropriation zones and scientific calculation of zone prices have become crucial. This study used the Cangzhou urban area in Hebei Province, China, as a case study. By integrating the CA–Markov model, multiple linear regression model, coupling coordination degree model, relative development degree model, and GIS spatial analysis techniques, the study deeply analyzed the spatiotemporal coupling relationship between land use and comprehensive land prices for expropriation zones from 2009 to 2021. Furthermore, it simulated and forecasted the changes in land use, expropriation zones, and zone prices in 2027. The study yielded the following conclusions: (1) The changes in land use reflected land economic value, land resource condition and land location condition shifts, which formed an interactive feedback mechanism with the comprehensive land price for land expropriation zones. (2) Land use impacted zone distribution through the spatial distribution characteristics of construction land, with recent development zones in the central urban area primarily extending east and southeast due to planning and policies related to land use for construction. (3) The coupling coordination and relative developmental degree between land use degree and zone price gradually develop in a good direction. A linear relationship is observed among land economic value, land resource condition, and land location condition concerning the zone price. Based on this, the predicted adjustment ranges for zone prices from high to low in 2027 will be 2.6400 to 2.7210, 2.1900 to 2.2537, and 1.8300 to 1.9306 million CNY/hectare. This study provides a new method for studying comprehensive land prices for expropriation zones, supporting decision making.

Integrated Assessment of Security Risk Considering Police Resources

The existing research on security risk often focuses on specific types of crime, overlooking an integrated assessment of security risk by leveraging existing police resources. Thus, we draw on crime geography theories, integrating public security business data, socioeconomic data, and spatial analysis techniques, to identify integrated risk points and areas by examining the distribution of police resources and related factors and their influence on security risk. The findings indicate that security risk areas encompass high-incidence areas of public security issues, locations with concentrations of dangerous individuals and key facilities, and regions with a limited police presence, characterized by dense populations, diverse urban functions, high crime probabilities, and inadequate supervision. While both police resources and security risk are concentrated in urban areas, the latter exhibits a more scattered distribution on the urban periphery, suggesting opportunities to optimize resource allocation by extending police coverage to risk hotspots lacking patrol stations. Notably, Level 1 security risk areas often coincide with areas lacking a police presence, underscoring the need for strategic resource allocation. By comprehensively assessing the impact of police resources and public security data on spatial risk distribution, this study provides valuable insights for public security management and police operations.

Assessing the impact of coal furnace activities on air quality: A comprehensive spatial and temporal analysis

Air pollution is a critical threat to public health and environmental systems, primarily driven by industrial activities such as coal furnace operations. This study uses advanced spatial analysis techniques, including kriging and Principal Component Analysis (PCA), to assess the impact of these activities on air quality in a designated study area. The Air Quality Index (AQI) is also employed to evaluate air quality in this research. Additionally, five key variables—number of households, coal furnaces, average income, average cost, and AQI—are normalized using the MinMaxScaler for comparative analysis. Also, the results indicate that the southern and western regions of the study area have the highest pollutant concentrations, correlating with high AQI values and the density of coal furnaces and industrial activities. The PCA results show that urban areas are mainly affected by CO2 and SO2, significantly influencing the AQI, while agricultural land and other types of land (rangeland, forest, dryland, barren land) show varying dominant pollutants. Agricultural lands were found to be primarily impacted by SO2, CO2, and CO. In addition, a temporal analysis reveals a 10% annual increase in coal furnace operations from 2003 to 2024, contributing to the rise in pollution levels. The AQI optimization results also indicate a strong negative correlation between the number of coal furnaces and AQI, suggesting that reducing the number of coal furnaces can lower air pollution levels. These findings highlight the significant role of industrial emissions in worsening air quality and emphasize the need for cleaner technologies, reduced coal furnace usage, and stronger regulatory measures.

Leveraging Spatial Analysis Techniques for Developing a Climate Resilient and Localized Urban Greening Plan for Pasig City

Abstract. A recent study has been conducted to evaluate the current state of green spaces in Pasig City, Philippines, and to propose a Climate Resilient and Localized Urban Greening Plan (CRLUGP) to address urban greening that is essential for creating sustainable cities, especially in the face of climate change and urban population growth. The study utilized Geographic Information Systems (GIS), Remote Sensing (RS), and Machine Learning (ML) to map green spaces, analyze climate risks, and identify necessary corrective measures. The findings revealed that Pasig City currently only has 70.18 hectares of green space, which is significantly below the World Health Organization's recommended minimum of nine (9) square meters of green space per capita. Projections indicate that by 2032, the city will need 925.72 hectares of green space to meet the needs of its growing population. Additionally, the study identified a connection between low canopy cover and increased urban heat island effects, with the top 10 barangays showing a canopy cover of only 27.64%, well below the recommended 40%. Moreover, areas with limited green spaces were found to be at a higher risk of flooding, highlighting the importance of more vegetation for managing stormwater and mitigating climate-related risks. The study recommends a strategic approach to urban greening, leveraging spatial analysis for continuous monitoring and evaluation. By integrating spatial technologies and data-driven decision-making, Pasig City aims to establish a more sustainable and resilient urban environment for its residents.

How Does the Three‐North Shelterbelt Engineering of China Improve Its Habitat Quality? A Study of 40 Years of Change Tracking and Driving Factors

ABSTRACTThe Three‐North Shelterbelt Engineering of China (TNSEC) is a large‐scale ecological restoration project that was initiated in 1978 to enhance the ecological environment of the Three‐North Shelterbelt Engineering Region (TNSER). However, the macro long‐term data and driving mechanisms behind habitat quality in the TNSER remain inadequately understood. Therefore, multi‐source observational data, the InVEST model, and spatial analysis techniques were employed to quantify the spatiotemporal evolution of habitat quality in the TNSER since 1980. Additionally, the Optimal Parameters‐based Geographical Detector (OPGD) model was utilized to quantitatively elucidate the driving mechanisms behind changes in habitat quality. The habitat quality of TNSER has remained stable from 1980 to 2020, exhibiting significant spatial agglomeration characteristics. Areas with higher habitat quality are demonstrating a trend of expansion, while regions with poor habitat quality are experiencing fragmentation and expansion. It is anticipated that the habitat quality of TNSER will continue to remain stable in the future; however, areas with poor habitat quality and their adjacent zones are showing signs of deterioration. Changes in habitat quality within TNSER are influenced by multiple factors, primarily socio‐economic factors in nature, with GDP accounting for 55% of the variations in habitat quality. This study offers valuable recommendations for policymakers from a sustainable development perspective, highlighting the critical role of large‐scale ecological projects in enhancing environmental quality amidst ongoing ecological challenges.

How Has the Source Apportionment of Heavy Metals in Soil and Water Evolved over the Past 20 Years? A Bibliometric Perspective

Exploring soil heavy metal sources is of great significance for ensuring the safety of ecological environments and agricultural product safety, as well as for guiding pollution control and management policies. This paper retrieved 452 research papers on soil heavy metal source analysis published over the 2004–2024 period from the Web of Science database. The collected literature was subjected to multidimensional bibliometric analysis using the CiteSpace 6.3.R1. The results showed significantly increasing trends in the scientific outputs and the number of papers on heavy metal source analysis in soils and water over the study period. In addition, related research topics have expanded from single to multiple heavy metal elements in environmental media and have increasingly recognized the impact of water pollution on soil contamination. Research methods have also evolved from basic statistical analysis to complex spatial analysis techniques, covering agricultural and urban soils. Previous related studies have focused on heavy metal pollution in different areas, and related research on heavy metal source analysis has now extended from ecological environments to associated human health risks. The present study provides directions for future related research and guidance for ensuring effective source control of heavy metal pollution and safe utilization of land and water resources.

Spatial Coordination Analysis and Development Methods of the Catering Sector in Yongkang City

The catering sector is recognized as a crucial driver for stimulating domestic consumption and fostering sustained economic growth. A scientifically informed spatial planning of the catering sector in county-level cities can help mitigate the overconcentration or excessive dispersal of resources, thereby enhancing the efficiency of land and commercial resource utilization, reducing waste, and promoting sustainable development within a county’s economy. This study focuses on Yongkang City, located in central Zhejiang Province, as a case study. Using Python 3.1 software to extract point-of-interest (POI) data, spatial analysis techniques such as standard deviation ellipses and kernel density estimation are employed to elucidate the spatial distribution characteristics of the catering sector, comprehensive transportation, and public services in Yongkang City. Furthermore, a coupling coordination degree model is utilized to quantify the coupling coordination degrees between the catering sector and comprehensive transportation (D1), as well as between the catering sector and public services (D2), ultimately assessing the overall coupling coordination degree among the three sectors (D3). Based on the analysis results, the coupling coordination degrees are categorized into five levels, followed by a detailed evaluation of the catering sector’s development across different subdistricts. The findings indicate a certain degree of spatial imbalance in the distribution of the catering sector in Yongkang City, with the western region exhibiting a more favorable development trajectory. Notably, Dongcheng Subdistrict achieved the highest coupling coordination degree (0.993), while the northern region, hindered by underdeveloped economic conditions and limited transportation infrastructure, exhibited the lowest coordination degree (0.098). Considering the unique developmental characteristics and current conditions of each subdistrict, this study advocates for the formulation of a long-term sustainable development plan for the catering sector in Yongkang City. The findings of this research may offer valuable insights for other regions and countries, thereby promoting the sustainable advancement of the catering sector.

From textbooks to takeaways: a geospatial analysis of clustering of takeaway outlets near London schools

BackgroundWithin Greater London, the proliferation of fast-food outlets near schools has raised concerns about the nutritional choices available to children. Whilst previous research has examined children's food environments, nutritional studies have established variation in the nutrient profile of different types of fast-food. Thus, this study disaggregates fast-food outlet data more granularly by cuisine type sold and aims to investigate 1) if there is clustering of fast-food outlets around London schools, 2) which types of fast-foods are most accessible to children, and 3) whether this varies based on area-level deprivation. MethodsThis study identifies fast-food clusters within a 400 m radius (10 min walk) of school centres in London, aligning with Fast-Food School Exclusion Zones. Data on fast-food outlets were collected from Ordnance Survey and disaggregated into 10 major cuisine types using a machine learning algorithm. School data were collected from the Department for Education. The data were downloaded for December, 2021, geocoded, and analysed using spatial-analysis techniques (Multitype K-function & DB-Scan). FindingsPrimary and secondary schools had an average of five fast-food outlets within a 400 m radius. The most deprived quintile of schools had almost twice the number of fast-food outlets compared to the least deprived quintile. Initial results disaggregated by cuisine type in Haringey, Greenwich, Southwark, and Croydon, show that schools in the most-deprived areas had the highest number of chicken shop clusters, whilst the least-deprived had the most Southeast-Asian takeaway clusters. Further results will be available in August, 2024. InterpretationPreliminary findings indicate disparities in the number and types of take-aways that school children are exposed to, with greater clusters of energy dense outlets near schools in more-deprived areas, and fewer outlets but healthier cuisine types in less-deprived areas. This study's strengths lie in the novel methodological approaches adopted to characterise the food environment, providing evidence to support local authorities considering implementing Fast-Food School Exclusion Zones. FundingThis research was funded by the Medical Research Council as part of a PhD studentship awarded to CG (grant reference: MR/W006774/)]. Authors were not precluded from accessing data in the study, and they accept responsibility to submit for publication.

Spatial analysis techniques for assessing groundwater vulnerability: a strategic approach to proactive conservation and mitigation strategies

Spatial analysis techniques for assessing groundwater vulnerability: a strategic approach to proactive conservation and mitigation strategies

URBAN HEAT ISLAND ANALYSIS USING GIS AND REMOTE SENSING IN KOSHOFE LAGOS STATE

Urban heat islands (UHIs) are a significant concern in urban areas, particularly in tropical regions like Lagos, Nigeria. This study employs geographic information systems (GIS) and remote sensing (rs) techniques to analyze the urban heat island effect in Koshofe, a rapidly urbanizing area in Lagos. The research aims to identify the spatial distribution, intensity, and factors influencing UHI in koshofe. Using Landsat 8 and sentinel-2 satellite imagery, land surface temperature (LST) was retrieved and analyzed. GIS spatial analysis and mapping techniques were applied to examine the relationship between lst, land use/land cover (LULC), population density, and urban morphology. The study also investigated the impact of urban planning strategies on UHI mitigation. Results show that Koshofe experiences significant UHI effects, with lst varying between 28°c and 38°c. Built-up areas, particularly commercial and industrial zones, exhibited higher (LST) values compared to vegetated areas. Population density and urban density were found to be positively correlated with (LST). The study identified areas with high UHI risk, including major road networks and informal settlements.

Urban Expansion and Changing Settlement Patterns of Hyderabad City After 1990s

This paper examines the urban expansion and evolving settlement patterns of Hyderabad city since the 1990s, a period marked by rapid growth and transformation in response to economic liberalization, population influx, and infrastructural developments. The study employs spatial analysis techniques, including Geographic Information Systems (GIS), to map changes in land use, density shifts, and the expansion of urban peripheries. Key factors such as migration, industrial growth, and policy shifts are analyzed to understand their role in reshaping the city's morphology. Findings reveal significant spatial reorganization, with traditional central areas experiencing densification and peripheral zones undergoing rapid development

Integrating Geospatial and Real Time Technologies for Risk zone monitoring in Periyar Tiger Reserve, India.

There are numerous monitoring technologies available today, owing to the rapid advancements in technology and the increasing demand for safety and security in forests. Real-time monitoring with AI cameras, which are commonly utilized for creating and updating real-time features through surveillance, stands out as one of the most effective monitoring solutions. The objective of this current research is to monitor various risk zones within the Periyar Tiger Reserve by integrating real-time AI camera with geographic data. AI cameras were strategically placed using spatial analysis techniques. Leveraging Geographic Information System (GIS) technology, the system facilitates the spatiotemporal management of multiple cameras and their associated data. The spatial distribution and monitoring range of the AI cameras are depicted on the GIS map, along with the layout densities of the cameras and other pertinent information stored in a geospatial database. Additionally, merging various risk areas identified from past incidents with the camera locations enhances the system's capability to establish accurate topological connections between cameras and other points of interest. The results revealed that only 13% of the risk zone was observable from the nine available Real Time Monitoring towers. However, with the addition of 51 more towers, the visibility of the risk zone would increase to 40%. The remaining 15% of the risk zones were not visible through the existing infrastructure. To address this visibility gap, if permitted by the Wildlife Protection Act, wired communication may need to be implemented instead of wireless for monitoring these areas.

Demographic Change and Regional Specialisation: The Case of Greek NUTS II Regions

This paper investigates the impact of demographic changes on regional specialisation across Greek NUTS2 regions from 2001 to 2021. It explores the relationship between age-specific variations in the economically active population and gross value added (GVA) across different economic sectors. Using demographic and GVA data alongside spatial analysis techniques such as spatial regression models, median Local Moran’s I, and location quotient, the study identifies spatial autocorrelation patterns. Findings reveal strong correlations between the economically active population and GVA, highlighting demographic factors’ crucial role in regional economic performance. Over the period 2001 to 2021, the 15–24 and 25–34 age groups generally experienced declining growth rates in total, male, and female economically active populations, while the 45–54 and 55–64 age groups saw increases. Regions adjacent to those with higher economically active populations showed high–high clustering. Especially, Attiki and Kentriki Makedonia, the two metropolitan regions of Greece, influence neighbouring regions through economic spillover effects, fostering economic sector clustering and emphasising regional specialisation. These findings highlight the complex interplay between demographic shifts and regional economic outcomes, noting spatial disparities and the need for targeted policy interventions. The study provides empirical evidence demonstrating how demographic changes influence regional economic development across different regions.

Whole-process survey of a landslide based on UAV tilt photography and 3D reconstruction and spatial analysis techniques

Whole-process survey of a landslide based on UAV tilt photography and 3D reconstruction and spatial analysis techniques