Geographic Information System Approach Research Articles

Assessment of coastal flood risk scenarios on infrastructure in the Keta municipality in Ghana using a GIS approach

Coastal flooding and erosion, caused by climate change-induced sea level rise, pose significant threats to low-lying coastal areas worldwide. The African continent, including Ghana, has experienced severe impacts from these hazards, affecting the socio-economic development of coastal communities. This research focuses on the Keta municipality in Ghana. The Keta municipality is highly vulnerable to coastal flooding and erosion due to its low elevation and the construction of the Akosombo hydroelectric dam. This research aims to predict the impact of coastal flooding on infrastructure in the Keta municipality using different flood scenarios. It also fills the existing knowledge gap in understanding how future flood risk can impact on critical infrastructure and consequently on other vital socio-economic sectors in the coastal community of Keta. The study utilizes a Geographic Information System (GIS)-based approach, combining various datasets, including topographic data, administrative shapefiles, field survey points, and infrastructure data. Two flood scenarios were considered to assess areas at risk: a 2.5-m sea level flood scenario representing potential climate change events and a worst-case 5-m sea level flood scenario. The findings reveal that 3.3 km2 (9 %) of coastal land area, 3.9 km of roads, and 69 structures are at risk under a 2.5m sea level rise scenario, increasing to 7.1 km2 (19.4 %), 13.6 km of roads, and 667 structures under a 5m scenario. The study highlights the urgency of addressing these risks to protect coastal communities' socio-economic development and livelihoods. Recommendations include implementing appropriate coastal management strategies, improving infrastructure resilience, and promoting sustainable land-use practices. By understanding and addressing the future impact of coastal flooding, decision-makers can mitigate climate change's adverse effects on coastal areas and ensure the region's long-term sustainability.

Monitoring and assessing of sustainable development in the urban area of Ouagadougou based on SDG 11.3.1 indicator and the city biodiversity index

Urban growth can induce changes in the use and transformation of urban land. In the context of rapid urbanization, monitoring key indicators of sustainable development is essential. The aim of this study was to monitor and assess the level of sustainable development in the city of Ouagadougou between 2002 and 2022, based on global indicators such as Sustainable Development Goal 11.3.1 indicator and the Singapore City Biodiversity Index. A remote sensing and Geographic Information System approach was used to acquire and analyze open-source geospatial data. The results show an increasing inefficiency in land use, with excessive consumption to population growth until 2013. Between 2013 and 2022, this trend declined, but urban biodiversity nevertheless decreased significantly, with a 40% loss of natural areas between 2002 and 2022. Fragmentation of natural areas, due to infrastructure development, has amplified this degradation, posing ecological risks to the city. This study underlines the importance of strengthening the ecological connectivity of urban spaces to improve their sustainability and resilience. It also recommends reorienting urban strategies by integrating nature-based solutions and placing biodiversity preservation at the heart of sustainable urban development policies.

Analisis Tingkat Kerawanan Banjir di Sub Daerah Aliran Sungai (DAS) Kampar Kiri di Kecamatan Kampar Kiri

This study aims to describe and analyze the flood vulnerability level in the Kampar Kiri Sub-Watershed, Kampar Kiri District, as well as the extent of flood-prone areas impacting settlements in the region. The primary focus of this research is to understand the flood risk of the area and its effects on the existing settlements. The method applied in this study is Multi-Criteria Evaluation (MCE) using a Geographic Information System (GIS) approach. MCE is used to determine the weights of parameters affecting flood vulnerability and to select appropriate methods for analysis. This approach has proven effective and efficient in flood risk analysis, as demonstrated in previous studies. The parameters analyzed include slope, elevation, rainfall, soil type, land use, and distance from rivers, which are calculated using scoring methods and overlaid to produce a flood vulnerability map. The results indicate that the flood vulnerability level in the Kampar Kiri Sub-Watershed is categorized into three classes: not vulnerable, vulnerable, and highly vulnerable. The areas for each class are: not vulnerable with 16,854 hectares, vulnerable with 58,543 hectares, and highly vulnerable with 11,506 hectares. The extent of settlements in the vulnerability zones includes: vulnerable zone with an area of 277 hectares (approximately 20.83%), and highly vulnerable zone with an area of 1,054 hectares (approximately 79.17%). Based on these findings, it is recommended that the Kampar Kiri District government enhance land use planning to reduce flood risks, collaborate with the Kampar Public Works and Spatial Planning Office, and improve infrastructure such as drainage channels and flood protection embankments.

A Comparative Analysis Machine Learning Techniques for LULC Classification Using Landsat-8 Satellite Imagery

This study compares various categorization methods to assign land use and land cover (LULC) classes. Using Geographic Information Systems (GIS) and Remote Sensing (RS) to leverage the dynamic and complex area of LULC, this study examines the potential of different machine learning classification methods. Precise differentiation and classification of various land cover categories, such as green vegetation, urban areas, water bodies, dark green vegetation, and bare terrain, are made possible by the great spatial and spectral resolution of Landsat imagery. For efficient land management and planning, the integration of Landsat data with GIS and RS approaches provides insightful information about the distribution and temporal changes in LULC. This study uses four classifiers to explore the principles of supervised machine learning techniques and identify their drawbacks and advantages. Testing results show that the Support Vector Machine with four kernel linear-99.17%, radial basis (RBF)-99.11%, Sigmoid-99.11% and Polynomial-99.11% is a reliable option for LULC classification, outperforming than other classifiers in terms of accuracy, including the Minimum Distance Classifier (MD-93.47%), Maximum Likelihood Classifier (MLC- 98.98%), and Mahalanobis Distance Classifier (MH-97.83%). Among the tested classifiers, SVM with four kernels notably shows the highest accuracy. With their essential insights for well-informed decision-making towards sustainable development and resource utilization, our findings add to a thorough understanding of LULC dynamics. For accurate mapping and long-term monitoring of deviations in land cover (LC), the study emphasizes the value of using front-line classification systems in remote sensing applications.

Integrated geophysical and GIS approaches for groundwater potential assessment: a case study of Aladja, Delta State, Nigeria

ABSTRACT This study explores the groundwater potential in Aladja, Udu, Local Government Area of Delta State, Nigeria, using an integrated approach combining electrical resistivity techniques with Remote Sensing (RS) and Geographic Information System (GIS) methods. The primary aim is to delineate aquifers and comprehensively assess groundwater resources. Methods include Vertical Electrical Sounding (VES) to gather resistivity data, RS and GIS for analyzing geological and hydrological parameters such as lineament density, drainage density, slope, soil type, and land use. The resistivity values ranged from 147 to 460.50 Ωm, with aquifer thicknesses varying between 6.50 and 36.30 m. The RS and GIS analysis indicated high groundwater potential in regions characterized by significant lineament density and moderate slopes. The study highlights the complementarity of VES and RS/GIS in groundwater exploration, revealing substantial groundwater resources in the northwestern regions of the study area. This approach underscores the importance of integrating these methods for a more accurate assessment of groundwater potential. The novelty of this study lies in validating RS and GIS findings with VES data, ensuring reliable groundwater potential mapping and effective resource management. This integrated methodology offers a robust framework for sustainable groundwater resource assessment and management in similar geological settings.

Evaluating land use and climate change impacts on Ravi river flows using GIS and hydrological modeling approach

The study investigates the interplay of land use dynamics and climate change on the hydrological regime of the Ravi River using a comprehensive approach integrating Geographic Information System (GIS), remote sensing, and hydrological modeling at the catchment scale. Employing the Soil and Water Assessment Tool (SWAT) model, simulations were conducted to evaluate the hydrological response of the Ravi River to both current conditions and projected future scenarios of land use and climate change. This study differs from previous ones by simulating future land use and climate scenarios, offering a solid framework for understanding their impact on river flow dynamics. Model calibration and validation were performed for distinct periods (1999–2002 and 2003–2005), yielding satisfactory performance indicators (NSE, R2, PBIAS = 0.85, 0.83, and 10.01 in calibration and 0.87, 0.89, and 7.2 in validation). Through supervised classification techniques on Landsat imagery and TerrSet modeling, current and future land use maps were generated, revealing a notable increase in built-up areas from 1990 to 2020 and projections indicating further expansion by 31.7% from 2020 to 2100. Climate change projections under different socioeconomic pathways (SSP2 and SSP5) were derived for precipitation and temperature, with statistical downscaling applied using the CMhyd model. Results suggest substantial increases in precipitation (10.9 − 14.9%) and temperature (12.2 − 15.9%) across the SSP scenarios by the end of the century. Two scenarios, considering future climate conditions with current and future land use patterns, were analyzed to understand their combined impact on hydrological responses. In both scenarios, inflows to the Ravi River are projected to rise significantly (19.4 − 28.4%) from 2016 to 2100, indicating a considerable alteration in seasonal flow patterns. Additionally, historical data indicate a concerning trend of annual groundwater depth decline (0.8 m/year) from 1996 to 2020, attributed to land use and climate changes. The findings underscore the urgency for planners and managers to incorporate climate and land cover considerations into their strategies, given the potential implications for water resource management and environmental sustainability.

A study on ecological sustainable cities based on LCA-emergy-carbon footprint and geographic information system (GIS) approach

ABSTRACT Sustainable cities, as an effective response to global climate aberrations, have increasingly garnered the attention of researchers. However, due to the wide range of interpretations and applications associated with sustainable cities, diverse methodologies can yield starkly contrasting results. This paper adopts ecological and low-carbon perspectives to evaluate and discuss urban sustainability. The core of this investigation involves quantitatively measuring a city’s sustainability based on the lifecycle metrics of emergy and carbon footprint. The findings reveal that Yangzhou, recognized as a model ecological city by authorities, exhibits an emergy sustainability index below the standard benchmark (ESI = 0.02 < 1). GIS mapping reveals that the city’s largest ecological service system is situated in the northwest water region. Both the emergy and carbon footprint analyses indicate that urbanized areas exert a detrimental influence on the city’s overall sustainability. Additionally, the administrative authorities in Yangzhou have implemented proactive measures to transition the city towards sustainability. Currently, the impacts of clean energy adoption and urban wetland restoration are particularly pronounced. The application of lifecycle emergy and carbon footprint methods offers a holistic approach for urban managers, enabling sustainable urban planning that harmoniously integrates ecological emergy and low-carbon considerations. This approach is instrumental in the realization of sustainable cities.

Causes of Pediatric Deaths in Lusaka, Zambia: A Quantitative Geographic Information Systems Approach.

While childhood mortality has been declining in Zambia, it remains high at 58 per 1000 live births. Importantly, many leading causes of mortality in Zambia are preventable. This study was conducted to identify clusters of childhood mortality, causes of death of recently deceased children, barriers to care, and risk factors for mortality in Lusaka, Zambia. This study was conducted as a prospective cohort study. Family members or lawfully authorized representatives (LARs) were interviewed when they came to pick up death certificates for recently deceased children from Lusaka Children's Hospital. Each interview included a verbal autopsy, determination of the child's location of residence, and collection of demographic information. Demographic data was also collected from a healthy control group. Quantitative Geographic Information Systems was used to visualize mortality and evaluate for clustering. Leading primary causes of death included malnutrition (21%), complications of chronic illnesses (16%), and central nervous system infections (13%), while the leading barriers to care were cost (58%) and difficulties with travel (53%). Compared to controls, recently deceased children came from families with significantly lower incomes (1905 Kwacha vs. 2412 Kwacha, p = 0.03) and were significantly more likely to have a history of malnutrition (16.7% vs. 1.4%, p = 0.005). Mortality was clustered in two high-population density, low-income neighborhoods in Lusaka. Systems to reduce financial barriers to care and improve access to transportation could reduce childhood mortality in Lusaka. The aforementioned neighborhoods are ideal locations for public health interventions or improved healthcare services.

Undrained Shear Strength Mapping of Al-Khalis Districts: A Geotechnical GIS Approach

A geographic information system is an integrated collection of computer applications and materials that it is employed to assess geographic relationships, model spatial processes, and analyze and arrange geographic data. The gathering, organizing, and analysis of geographic data are made easier with the use of a geographic information system (GIS). Information systems pertaining to geography Thus, it is employed in the gathering, examination, assessment, updating, and presentation of geographic data. This study dealt with Al-Khalis District, one of the five districts of Diyala Governorate. Al-Khalis District is in the western part of Diyala Governorate and the northern part of the capital, Baghdad, about 55 km north of the capital, Baghdad. 227 boreholes were collected for the entire governorate. The soil was classified, its properties were taken, and they were collected in an Excel sheet. After that, this data was entered into geographic information systems to produce clay shear strength maps. A very helpful soil map that can be used in all aspects through structural and engineering simulation is produced when GIS is used in conjunction with physical and strong geotechnical qualities. Building engineering facilities, roadways, and industrial structures may be made easier with the use of a GIS map. Additionally, it offers a strong tool for extrapolating developed regions. GIS soil maps are anticipated to positively influence the next geotechnical work. The results revealed a significant variance in shear resistance across the depths of the Khalis area, with the soil's strength ranging from weak to medium in the first layer and increasing downward with depth. So, we recommend not going for more than three multi-story buildings unless doing site investigation on the site and making sure it is suitable for that or using a pile foundation. This study aims to give geotechnical engineers and designers a first impression of the type of soil and help them quickly make decisions in terms of the type of foundations and the number of floors for multi-story buildings

Watershed Modelling, Using the Geographical Information System (GIS) Approach (Federal University of Technology Owerri, Imo State Nigeria as Case study)

In a typical watershed area such as the Federal University of Technology, Owerri, Nigeria, watershed modelling is essential for the sustainable management of water resources, protection of ecosystems and more. In this study, we will be creating a watershed model for FUTO, this study will also cover other aspects such as estimating the depression-less flow direction, delineating the flow accumulation, extracting realistic drainage network using the Strahler’s stream order method and we will also delineate the watershed’s boundary and identify possible outlets / pour points, using the digital elevation model (DEM) gotten from Alaska satellite facility used as a main data source in combination with the PC version of ArcGIS software (ArcMap 10.7) and then we extract the hydrologic information from the DEM in ArcGIS using Hydrology tools. The estimation of depression-less flow direction is done by filling the digital elevation model (DEM). This includes performing fill on sinks to ensure proper delineation of basins and streams. If the sinks are not filled, a derived drainage network may be discontinuous. After the DEM has been filled, then we can now move on to delineating the flow accumulation in the study area. The results shows that by using watershed function in ArcGIS for watershed flow direction and accumulation in FUTO can be determined. The results also shows the drainage network that was extracted by Strahler’s method, showing different orders of streams and it also shows the watershed boundary and pour point / outlets along the Otamiri River which the watershed drains into. This work simply shows the applicability of GIS as a tool of watershed delineation and drainage extraction.

Applying the water quality indices and geographic information system approach to assessing the suitability of groundwater quality for drinking and irrigation purposes in the semi-arid region of Tebessa-Ain Chabro, Northeastern Algeria

Assessing the groundwater quality is important for the efficient exploitation of water resources in semi-arid areas. The study area in northeast Algeria mostly depends on groundwater as its main source of water, and the quality of groundwater is becoming important due to the increasing need for freshwater. The hydrochemical characteristics and water quality of groundwater in the Tebessa-Ain Chabro were assessed using water quality indices, geochemical modeling, and multivariate statistical approaches. The study discovered that the groundwater samples could be classified into four distinct water groups using hierarchical cluster analysis in Q mode (HCA) based on their electrical conductivity. We identified three forms of water: mixed (Ca2+–Mg2+–Cl−), Na+–K+–HCO3−, and Ca2+–Cl−. According to the water quality assessment, only 38% of the samples were deemed suitable for human consumption, while 34% were categorized as poor water, 10% as extremely poor, and 17% as unsafe for drinking. The irrigation water quality index identified four classifications: low, moderate, high, and severe restriction, with corresponding percentages of 31%, 31%, 7%, and 31%. The nitrate pollution index (NPI) showed that 48% of samples fell into the moderate pollution class. Human activity, such as sewage infiltration and waste disposal in open areas, was the cause of this nitrate contamination. The saturation index values showed that groundwater was less saturated in halite and sylvite and more saturated in aragonite, calcite, dolomite, anhydrite, gypsum, and hydroxyapatite. The Tebessa region’s groundwater’s hydrochemical properties and water quality have been assessed using multivariate statistical techniques, geochemical modeling, and water quality indexes. The study’s conclusions can provide a foundation for upcoming research evaluating the region’s groundwater quality.

Oued Lakhdar watershed (Morocco), monitoring land use/cover changes: remote sensing and GIS approach

ABSTRACT Landsat is a series of Earth-observation satellites jointly managed by NASA and the United States Geological Survey (USGS) that capture multispectral images of the Earth’s surface dating back to the 1970s, providing a valuable tool for tracking changes in land cover over time. In this study, Landsat satellite data were combined with remote sensing and Geographic Information System (GIS) technologies to monitor land cover changes in the Oued Lakhdar watershed, which covers an area of 1,638 km2. Landsat satellite data for the years 1987, 1994, 2004, 2014, and 2021 were used, and the maximum likelihood method was applied in ArcGIS software version 10.4.1 to classify land components. The classification was validated using total accuracy, the kappa index, Google Earth, and terrain knowledge. The results show remarkable changes in land cover, with an increase in bare soil and irrigated crops between 1987 and 2021, especially in the last six years, totaling 0.672 km2/yr and 15.028 km2/yr of the study area, respectively, and a decrease in water bodies and dense forests, totaling −0.941 km2/yr and −30.046 km2/yr, respectively. Water retention coefficient analysis indicates that the watershed is anthropized and has a low retention capacity. This study provides valuable information for land use planning and management in the Oued Lakhdar watershed (Morocco).

Use of Geographic Information Systems to Analyze the Distribution of Water Catchment Areas in Ambon City, Indonesia

Background: Ambon City, as the capital of Maluku province, faces serious challenges in water resources management due to rapid urbanization and climate change that affects rainfall patterns. This study aims to analyze the distribution of water catchment areas using Geographic Information Systems. Methods: This study used variables of rainfall, soil type, land use, and slope which were analyzed using Geographic Information System (GIS) approach with overlay technique. Findings: The results showed that the water catchment area in Ambon City with a rather critical condition has an area of 2,350.27 ha, good condition of 13,524.39 ha, starting critical condition of 2,827.62 ha, normal natural condition of 13,636.20 ha and very critical condition of 236.12 ha. This research shows that soil characteristics, land use, slope, and rainfall in Ambon City have a significant influence on the capacity of water catchment areas. Findings from analysis using Geographic Information Systems (GIS) show that soil type, land use, and slope have a significant effect on water infiltration capacity, with alluvial soils having the best infiltration capacity. Conclusion: The results of this study emphasize the need for better management and strict implementation of spatial policies to protect water catchment areas, in order to reduce disaster risk and support sustainable development in Ambon City.

Evaluating Urban Services in Neighbourhoods Through the Inequality Lens in Khulna City, Bangladesh: A Geographic Information System Approach

This article delineates the development of an integrated assessment tool to understand inequality in the provision of urban services among neighbourhoods in Khulna city, Bangladesh. The study considers eight key indicators to evaluate basic urban services related to the physical environment of the city. We use primary and secondary sources of information as well as geographic information system (GIS) to summarise the results in a scientific fashion. Additionally, we adopt the analytic hierarchy process (AHP) technique to distribute weights among the considered indicators and categorise the neighbourhoods as ‘good’, ‘average’ or ‘poor’ in terms of service availability. Results from the study demonstrate that a majority of the neighbourhoods lack basic urban services. Only 10 per cent of the neighbourhoods are equipped with basic urban services, whereas 74 per cent face difficulties with ‘average’ quality of services and nearly 16 per cent of neighbourhoods fail to provide basic services to city dwellers. Our study may be useful to development authorities, city corporations and local governments to visualise the neighbourhoods struggling for basic urban services and bring them under immediate attention to deliver the required resources. Further, the study provides an assessment model to understand urban service inequality in cities with similar characteristics in other parts of the world.

A comprehensive decision-making approach for the application of biochar in agriculture to enhance water security: A GIS-AHP based approach

In the context of climate change, biochar application is a promising approach to mitigate the adverse effects of climate change on agriculture. However, the selection of suitable biochar produced from food waste and optimization of loading rates to improve soil quality remains a significant challenge. This study explores the potential impact of biochar application using an integrated analytical hierarchy process (AHP) and geographical information system (GIS) approach. The study first aims to develop an AHP model to prioritize the appropriate biochar source and dosage for soil amendment. The different biochar sources considered are: peas pod shell, pistachio shell, and mixed vegetable waste. The AHP design evaluated the weight percentage of different types of biochar amendments ranging from 0 % to 8 % based on soil quality, nutrient analysis and water retention capacity. Furthermore, an integrated spatial analysis case study was conducted for fodder farms across Qatar using GIS mapping with seasonal variation to evaluate the impact of biochar on water management. According to the AHP decision making, 2 % mixed vegetable waste biochar achieved the goal with the highest priority score, with a value of 0.29, followed by 2 % pistachio shell biochar with a score of 0.22. This is attributed to the high water retention rate determined from the experimental study. The 2% biochar amendment retained 20 % more water compared to the 0 % biochar. Results from the GIS mapping identified priority areas for improving water retention and soil quality. The evapotranspiration maps for winter and summer generated using GIS provide valuable insights into the spatial disributio of biochar application across Qatar fodder farms. The outcomes may encourage policymakers and stakeholders to consider valorizing food waste into biochar.

Analysing the capacity of multispectral indices to map the spatial distribution of potential post-fire soil losses based on soil burn severity

The area burned in Spain exceeded historical records in 2022, when exceptionally warm conditions influenced wildfire events. The predicted intensification of wildfire regimes includes an increase in frequency, severity, and size. Therefore, a study of the wildfires that occurred in 2022 is necessary to understand their behaviour and possible environmental impacts. The objective of this study is to analyse the applicability of using spectral indices and Geographic Information System (GIS) approaches to map the spatial distribution and estimate potential soil losses using Sentinel-2 imagery and fire severity field data. Soil losses were estimated using an empirical model based on soil burn severity data collected in the field after wildfire. The relationship between the Normalized Difference Infrared Index (NDII), Difference Normalized Wildfire Ash Index (dNWAI), and the Blue Normalized Difference Vegetation Index (BNDVI) with the estimated soil losses was then evaluated. In addition, the influence of different time scales of the satellite images was analysed. The first period considered (Date I) ranges from 8 to 20 days after the beginning of the wildfire, which coincides with the field data collection. The second period considered (Date II) ranges from 28 to 35 days after the start of the wildfire. The results obtained showed a significant dependence relationship between the BNDVI index (using satellite images of Date I) and the estimated soil losses (R2 = 0.756), while the results of the NDII (R2 = 0.31) and dNWAI (R2 = 0.061), showed no spatial relationship with the estimated soil losses. Three of the largest wildfires in 2022 in Spain were analysed, and the results showed strong correlations of BNDVI index for Folgoso do Courel (R2 = 0.808), for Carballeda de Valedorras (R2 = 0.906), and for Sierra de la Culebra (R2 = 0.939). In addition, these results allowed the mapping and quantification of potential soil losses in areas where fire severity was high, totalling ∼2,50,000 Mg ha−1 in Folgoso do Courel, ∼3,70,000 Mg ha−1 in Carballeda de Valdeorras, and ∼4,70,000 Mg ha−1 in Sierra de la Culebra. Moreover, BNDVI values for estimating soil loss vary by vegetation type, and there is a positive correlation between severity classes and the BNDVI index. This approach can inform post-fire land management decisions in future wildfires and could be applied to other regions.

Application of Geographic Information Systems (GIS) in the Study of Prostate Cancer Disparities: A Systematic Review.

Introduction: PCa is one of the cancers that exhibits the widest disparity gaps. Geographical place of residence has been shown to be associated with healthcare access/utilization and PCa outcomes. Geographical Information Systems (GIS) are widely being utilized for PCa disparities research, however, inconsistencies in their application exist. This systematic review will summarize GIS application within PCa disparities research, highlight gaps in the literature, and propose alternative approaches. Methods: This paper followed the methods of the Cochrane Collaboration and the criteria set of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Articles published in peer-reviewed journals were searched through the PubMed, Embase, and Web of Science databases until December 2022. The main inclusion criteria were employing a GIS approach and examining a relationship between geographical components and PCa disparities. The main exclusion criteria were studies conducted outside the US and those that were not published in English. Results: A total of 25 articles were included; 23 focused on PCa measures as outcomes: incidence, survival, and mortality, while only 2 examined PCa management. GIS application in PCa disparities research was grouped into three main categories: mapping, processing, and analysis. GIS mapping allowed for the visualization of quantitative, qualitative, and temporal trends of PCa factors. GIS processing was mainly used for geocoding and smoothing of PCa rates. GIS analysis mainly served to evaluate global spatial autocorrelation and distribution of PCa cases, while local cluster identification techniques were mainly employed to identify locations with poorer PCa outcomes, soliciting public health interventions. Discussion: Varied GIS applications and methodologies have been used in researching PCa disparities. Multiple geographical scales were adopted, leading to variations in associations and outcomes. Geocoding quality varied considerably, leading to less robust findings. Limitations in cluster-detection approaches were identified, especially when variations were captured using the Spatial Scan Statistic. GIS approaches utilized in other diseases might be applied within PCa disparities research for more accurate inferences. A novel approach for GIS research in PCa disparities could be focusing more on geospatial disparities in procedure utilization especially when it comes to PCa screening techniques. Conclusions: This systematic review summarized and described the current state and trend of GIS application in PCa disparities research. Although GIS is of crucial importance when it comes to PCa disparities research, future studies should rely on more robust GIS techniques, carefully select the geographical scale studied, and partner with GIS scientists for more accurate inferences. Such interdisciplinary approaches have the potential to bridge the gaps between GIS and cancer prevention and control to further advance cancer equity.

A fuzzy analytical hierarchy process -GIS approach to flood susceptibility mapping in NEOM, Saudi Arabia

The Kingdom of Saudi Arabia is undergoing massive and rapid urbanization as part of Vision 2030. This includes development projects along Saudi Arabia’s coastline across the Red Sea. Coastal areas, especially the ones along Saudi’s western regions are susceptible to natural disasters such as flooding. NEOM, a futuristic city currently being developed in the northwest of Saudi Arabia, exemplifies a potential flooding hazard due to its geographic location and proposed urbanization plans. This research aims to enhance flood hazard assessment in NEOM by applying the Fuzzy Analytical Hierarchy Process (FAHP) in combination with Geographic Information System (GIS). Acknowledging traditional limitations related to data availability and parameter selection consensus, the study carefully selects parameters such as drainage density, elevation, slope, rainfall, land use/land cover (LULC), soil type, normalized difference vegetation index (NDVI), and topographic wetness index (TWI). The 30 m DEM was used to derive Drainage Density, Slope, and TWI while LULC data helped assess land cover changes. Rainfall data and soil type information are integrated to evaluate their impact on flood susceptibility. NDVI is employed to analyze vegetation cover. Utilizing ArcGIS Pro’s weighted overlay model, the criteria were combined to generate the final flood susceptibility map. The research outcomes manifest in a flood susceptibility map categorizing areas into seven distinct susceptibility classes, ranging from ‘very low’ to ‘very high.’ A quantitative breakdown in a summary table provides insights into the proportional distribution of flood risk. Results indicate a significant portion of NEOM falls within varying degrees of moderate susceptibility range with relatively limited distribution of flood susceptibility on the extremes, equating to areas with ‘low to moderate’ susceptibility is 4,322.8 km2, areas with ‘moderate’ susceptibility is 5,109.69 km2, areas with ‘moderate to high’ is 4,081.39 km2. The flood susceptibility map developed in this study can shed insights on potential optimum areas for flood mitigation measures (i.e., optimum locations for establishing stormwater collection points).

Geo-Phenomenology: A Qualitative and Humanistic GIS Approach to Exploring Lived Experience

Critical discussions are developing to combine geographic information systems (GIS) and qualitative methods as an alternative approach to traditional quantitative GIS, but the possibility of integrating spatial information technology and phenomenology is still unknown. This study explores a new qualitative and humanistic GIS approach called geo-phenomenology. It attempts to improve the ability to validate and authenticate findings and to gain a holistic understanding of the complex interplay among space, place, and human emotion through a combination of phenomenology, natural language processing methods, and GIS. To illustrate this approach, this study focuses on international students and examines the effects of geographic mobility on individuals’ sense of attachment and belonging. Importantly, it allows for a more sensitive approach to the spatial scale of material culture as a mediator of sense of place. The overlay of emotional mapping and land use provided a perspective for narrative interpretation and hypothesis building, ultimately leading to the discovery of key evidence determining the main themes of international students’ sense of place attachment and belonging. By combining quantitative emotion detection with qualitative phenomenological interpretation in GIS, this study concludes that geo-phenomenology can help us consider the rich nuances of lifeworlds from multiple perspectives.

Criteria for selection of technology to exploit groundwater in water-scarce area in Vietnam

Abstract. Water extraction solutions in the high mountainous areas of Northern Vietnam commonly include rainwater harvesting, dug wells, drilled wells, groundwater springs, and hanging lakes. However, many water supply systems operate inefficiently and lack flexibility. This study established 10 criteria for selecting groundwater exploitation technology, divided into three groups: water resources, economic and technical, social, and environmental criteria. These criteria aim to identify appropriate water extraction technologies suitable for high mountainous and water-scarce regions, ensuring the long-term and efficient operation of water supply systems. The Geographic Information System (GIS) approach was utilized, integrating the criteria using the Analytical Hierarchy Process (AHP) method to select suitable water extraction technologies. The research results indicate that the evaluation criteria for determining suitable areas for implementing sustainable water extraction technologies, and the weights assigned to these criteria, ensure a consistent ratio (CR) &lt;10 % according to the hierarchical analysis method. This article presents the results of identifying areas suitable for implementing groundwater extraction technologies using drilled wells, based on seven criteria within three groups: water resources, economic and technical, and social criteria. The GIS approach has been employed, and the criteria have been integrated using the AHP to select and determine the areas suitable for implementing groundwater extraction technologies using drilled wells.