Geographic Information System Technology Research Articles

Edy App: Earthquake Mitigation Innovation Using GIS for Disaster Response in Pariaman, Indonesia

Pariaman City, located along the Semangko fault line and the subduction zone of the Indo-Australian and Eurasian plates, is highly vulnerable to earthquakes and tsunamis. The region's susceptibility to large earthquakes, followed by vertical deformations, highlights the need for effective disaster mitigation. In response, this study proposes the development of the Earthquake Buddy Application (EDY App), designed to assist with earthquake mitigation efforts. The EDY App leverages Geographic Information System (GIS) technology to map earthquake-prone areas, provide early warnings, suggest evacuation routes and Temporary Evacuation Sites (TES), and facilitate aid distribution. This Android-based mobile application focuses on four key aspects: education, mitigation, evacuation, and donation. Key features include an Earthquake Vulnerability Map, real-time early warnings, mitigation instructions, TES recommendations with distance and time estimations, emergency contact options, and donation channels. Built with React Native, PHP, and MySQL, and integrated with Google Maps API, the app is designed to be user-friendly and accessible to the public. The EDY App’s contribution to earthquake mitigation lies in its ability to create a disaster-aware community. By offering comprehensive information and support during critical moments, the app can potentially reduce casualties and enhance community preparedness in earthquake-prone regions like Pariaman. Through this innovation, it is expected that residents will be better equipped to respond to natural disasters, promoting a culture of safety and resilience.

Water quality assessment using national Water Quality Index (WQI): a case study of the Song Be River, Bing Duong Province, Vietnam

Abstract The Song Be River is a vital water source in Binh Duong Province, Vietnam, playing a crucial role in supplying water for domestic use and agriculture, as well as supporting local ecosystems. However, due to the recent rapid economic and industrial growth, the river’s water quality has encountered significant challenges, particularly from the improper discharge of untreated wastewater from various sources and activities. This study conducts a comprehensive analysis of the Song Be River’s water quality by employing the Water Quality Index (WQI) in conjunction with Geographic Information System (GIS) technology. Subsequently, several strategies are also proposed to effectively manage and enhance the water quality of the Song Be River. Over the period from March 2023 to March 2024, 52 samples were collected from four monitoring points (SB1, SB2, SB3, and SB4) along the Song Be River, with a frequency of once per month. All analytical parameters (such as NH4 +_N: 0.01–0.61 mg l−1, NO2 −_N: 0.014–0.03 mg l−1, Fe: 0.01–0.81 mg l−1, Chemical Oxygen Demand (COD): 4–26 mg l−1, Dessolved Oxygen (DO): 3.8–6.6 mg l−1, Suspendid Solids (SS): 5–69 mg l−1, Coliform: 1200–4300 MPN/100 ml, Total phosphorous: 0.01–0.08 mg l−1 and Total nitrogen: 1.16–4.5 mg l−1) fell within the permissible limits according to the Vietnamese National Standards. Furthermore, the WQI ranged from 73 to 100, indicating that the water quality of The Song Be River is good and suitable for domestic use.

Energy, environmental and economic performance of bi-facial photovoltaic noise barrier applied in city scale

Solar energy in transportation reduces fossil fuel consumption and supports carbon neutrality. Photovoltaic noise barriers (PVNB) are used globally to harness renewable energy along roads. This study's novelty lies in the detailed consideration of road orientation and the application of bifacial photovoltaic technology when assessing the potential for large-scale deployment of PVNB. Bifacial PV technology captures solar radiation from both sides, enhancing energy efficiency. A mathematical model was established and validated to predict PVNB power output at 5° azimuth intervals. Geographic information system (GIS) technology was used to quantify trunk roads, motorways, and RNB in Shenzhen, China. Accordingly, the electricity generation potentials of PVNB, as well as the economic and environmental benefits were calculated. The installed capacity and power generation of PVNB in Shenzhen are 432.29 MW and 313.37 GWh, respectively. The levelized cost of electricity is 0.4781 CNY/kWh. Compared to a 600 MW coal-fired unit, 9119.09 tce of fossil fuel can be saved, with lifecycle carbon reduction of 3.80 Tg and net carbon reduction of 3.05 Tg.

ENGINEERING-GEODESIC EQUIPMENT OF THE TERRITORY USED BY USING GEOINFORMATION SYSTEMS

The purpose of the scientific article is the implementation of an important part of the agricultural spatial data infrastructure, planning of the domestic economy using geographic information systems (GIS). Taking this direction into account, the work examines the following main elements of designing the domestic economy: location of settlements and economic centers; design of internal roads; placement of external engineering networks; use of types of land reclamation for agricultural purposes; allocation of land for the construction of roads of various categories of local importance; placement of agricultural machinery in land use; conduct a technical and economic analysis of the effective use of road junctions and reclamation works as an engineering structure, as well as systematize the engineering and geodetic process necessary to implement these studies based on GIS technologies. With the help of geographic information systems technologies, it will be necessary to determine the following directions of engineering and geodetic equipment of the territory: Information about road transport and roads, Roads in plan, longitudinal and horizontal profiles, Driving through bodies of water and bodies of water on the road, Road surfaces, Road surveys and design of agricultural roads, The basic principle of organizing the construction, maintenance and repair of agricultural roads.

Groundwater pollution by nitrate and salinization in Morocco: a comprehensive review

ABSTRACT Groundwater plays a critical role in supporting a wide range of human activities. However, it faces substantial challenges due to the growing demand for water and reduced precipitation resulting from climate change. Various studies have revealed the high vulnerability of Morocco's groundwater to contamination from multiple anthropogenic sources. This review focuses on assessing nitrate and salinization pollution in Moroccan groundwater, with a specific emphasis on the Gharb region. A comprehensive analysis of research conducted from 2010 to 2023, using reputable databases, underscores the pressing need to address groundwater pollution in Morocco, especially in the Gharb region. The results highlight the significant challenges faced by Morocco's groundwater resources. Agricultural practices and poorly designed irrigation systems are identified as primary contributors to nitrate contamination. Additionally, salinization in the region is influenced by factors such as seawater intrusion, hydrogeological characteristics, and irrigation practices. An integrated approach, combining laboratory analysis, remote sensing, geospatial tools, modeling, and geographic information systems technology, has proven to be effective in addressing the complex issues of assessing groundwater pollution due to nitrate and salinization. This survey presents a comprehensive framework for future research and decision-making processes aimed at achieving sustainable water resource management, preserving the groundwater heritage and safeguarding public health.

Analysis of the Distribution and Influencing Factors of Antibiotic Partition Coefficients in the Fenhe River Basin

Affected by point and non-point source pollution, the Fenhe River Basin faces significant environmental challenges. This study aimed to analyze the distribution characteristics and influencing factors of antibiotics in the water and sediments of the Fenhe River Basin. Samples were collected from 23 sites within the basin, and 26 antibiotics from five different classes were detected and analyzed using high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS). The water–sediment partition coefficient (Kp) was calculated, and spatial analysis was conducted using geographic information system (GIS) technology. The results showed that 25 antibiotics were detected in the water, with concentrations ranging from 130 to 1615 ng/L, and 17 antibiotics were detected in the sediments, with concentrations ranging from 121 to 426 μg/kg. For quinolones (QNs), except for ofloxacin, all others could be calculated with overall high values of Kp ranging from 692 to 16,106 L/kg. The Kp values for QNs were generally higher in the midstream, with considerable point source pollution from industries and non-point source pollution from developed agriculture. The distribution of Kp is closely associated with risk. This study found that the Kp values of the antibiotics were influenced by various factors such as temperature, water flow, and the physicochemical properties of sediments. Correlation analysis revealed significant relationships between Kp and parameters such as river width, water depth, water quality (total nitrogen, total phosphorus, and chemical oxygen demand), and sediment pH and clay content.

Estimating the extent of water erosion in the Wadi Al-Rumaitha Basin, northeast of Al-Muthanna Governorate

The Wadi Rumaitha Basin is located astronomically between two latitudes (30° 39' 18" - 30° 29' 56") north, between two longitudes (45° 52' 4" - 45° 45' 10") east, with an area of (68.5) km2, located in the southern part of Iraq within the administrative borders of Al-Muthanna Governorate, which is characterized by a dry climate. The research aims to study and estimate the extent of water erosion in the Wadi Rumaitha basin, detect risks and conditions that affect the properties and quality of soil and land uses in the region, highlighting the role of natural characteristics affecting its activity, different types of water erosion prevail in the study area, between rain erosion, stream erosion, and gully erosion. The locations and areas of the basins of the river network and the stream, gully, and rain erosion network were determined, by adopting several criteria, including the Fournier equation to measure rain erosion, and the Bergsma 1982 equation (to measure the degree of stream and gully erosion, then, modeling the areas of spread of each of them, by the use of geographic information systems technology. It became clear through the research that the Fournier index in the stations of the study area reached (19.87, 21.66, 16.53), respectively, this indicates that the Wadi Rumaitha basin area falls within the range of weak rain erosion, while funicidal erosion included (4) cases limited to the range of high and very severe fluid erosion, gully erosion included (7) areas confined between the (very light and very high) ranges, and their geographical distribution varies in the basin lands.

Potential assessment and development obstacle analysis of CCUS layout in China: A combined interpretive model based on GIS-DEMATEL-ISM

Although carbon capture, utilization, and storage (CCUS) has enormous emission reduction potential and application prospects, it still faces many obstacles and challenges in the actual deployment and promotion process. This study aims to evaluate the spatial suitability of the CCUS layout comprehensively and deeply analyze key development obstacles to provide a scientific basis for the promotion and layout of CCUS. Therefore, this article constructs a combination of Geographic Information Systems (GIS), Decision-making trial and evaluation laboratory (DEMATEL) method, and Interpretive structure model (ISM). Firstly, a comprehensive evaluation is conducted on the suitability of the CCUS layout in China based on GIS technology, identifying high-potential areas. The results indicate that when the threshold is 80 % of the highest score for suitability, a total area of 1.46 million square kilometers is suitable for the CCUS project layout. When it dropped to 60 %, this data increased to 2.04 million square kilometers. These areas are mainly distributed in large basin areas with abundant resources. Secondly, the DEMATEL-ISM analysis framework is improved to systematically identify and analyze the key obstacles that constrain the promotion of CCUS in China. The results indicate that there is a very complex relationship between the obstacles that constrain the development of CCUS, with the fundamental reasons being the lagging technological level and imperfect policies and regulations. Finally, goal-oriented suggestions and response measures were proposed, and targeted analysis was conducted on high-suitability areas. This study constructed an interdisciplinary methodology interpretive model to provide decision support for the CCUS layout and targeted strategies to break through current development barriers and promote the rapid development of CCUS.

Risk Assessment of Community-Scale High-Temperature and Rainstorm Waterlogging Disasters: A Case Study of the Dongsi Community in Beijing

With the advancement of urbanization and acceleration of global warming, extreme weather and climate events are becoming increasingly frequent and severe, and climate risk continues to rise. Each community is irreplaceable and important in coping with extreme climate risk and improving urban resilience. In this study, the Dongsi Community in the functional core area of Beijing was explored, and the risk assessment of high temperatures and rainstorm waterlogging was implemented at the community scale. Local navigation observations were integrated into a theoretical framework for traditional disaster risk assessment. The risk assessment indicator system for community-scale high-temperature and rainstorm waterlogging disasters was established and improved from a microscopic perspective (a total of 22 indicators were selected from the three dimensions of hazard, exposure, and vulnerability). Geographic Information Systems (GIS) technology was used to integrate geographic information, meteorological, planning, municipal, socioeconomic and other multisource information layers, thus enabling more detailed spatial distribution characteristics of the hazard, exposure, vulnerability, and risk levels of community-scale high temperatures and rainstorm waterlogging to be obtained. The results revealed that the high-risk area and slightly high-risk area of high-temperature disasters accounted for 13.5% and 15.1%, respectively. The high-risk area and slightly high-risk area of rainstorm waterlogging disasters accounted for 9.8% and 31.6%, respectively. The high-risk areas common to high temperatures and waterlogging accounted for 3.9%. In general, the risk of high-temperature and rainstorm waterlogging disasters at the community scale showed obvious spatial imbalances; that is, the risk in the area around the middle section of Dongsi Santiao was the lowest, while a degree of high temperatures or rainstorm waterlogging was found in other areas. In particular, the risk of high-temperature and rainstorm waterlogging disasters along Dongsi North Street, the surrounding areas of Dongsi Liutiao, and some areas along the Dongsi Jiutiao route was relatively high. These spatial differences were affected to a greater extent by land cover (buildings, vegetation, etc.) and population density within the community. This study is a useful exploration of climate risk research for resilient community construction, and provides scientific support for the planning of climate-adaptive communities, as well as the proposal of overall adaptation goals, action frameworks, and specific planning strategies at the community level.

Mapping Population Densities and Waste Management Systems in Mombasa County: A Literature Review of GIS and Remote Sensing Techniques

Mombasa County is one of the five counties along the coastline of Kenya. Currently, Mombasa County has a human population of 1.2 million people, and the population is rapidly increasing through rural-urban immigration and natural births. However, the inadequacy of well-established waste management systems on the mainland and coastlines of the County is a threat to the well-being of the local residents. Poorly disposed of wastes both on land and at sea can lead to health problems not only for humans and terrestrial animals but also for aquatic animals such as fish, with the latter being one of the main sources of affordable proteins for poor coastal communities. This paper aimed to conduct a review of the spatial human population density of Mombasa County and the geospatial location of waste dumping sites and their proximity to settled areas. This literature review synthesized existing research on the application of Geographic Information Systems (GIS) and Remote Sensing techniques in mapping population densities and assessing waste management systems. The review began by examining studies that investigate population distribution patterns in urban and rural areas, utilizing GIS to analyze demographic data and satellite imagery. It explored methodologies used to estimate population densities, including dasymetric mapping, spatial interpolation, and land use classification techniques. Key findings were that limited studies have utilized GIS technologies to assess the population in Kenya. GRASP and Random Forest (RF) were the main techniques previously used to assess population densities in the rural Taita Hills area and along the coastal region. The population has exponentially increased in Mombasa County since the 1950s and is projected to increase further. Additionally, waste management in Mombasa County is majorly controlled by the county government. Ten geo-tagged waste collection spots were identified during the review, spread across the residential areas. In conclusion, the county should endeavor to employ GIS techniques to assess the rapid population change within the county and have targeted interventions to address the disparities in waste collection systems against population increase.

Modelling and Mapping of Aboveground Carbon of Oluwa Forest Reserve Using LandSat 8 TM and Forest Inventory Data

This research was carried out within the Oluwa Forest Reserve to evaluate and forecast its capacity for aboveground carbon sequestration using data from the Landsat Thematic Mapper. The Oluwa Forest Reserve, situated in Ondo State, Nigeria, is renowned for its abundant biodiversity and vast expanse. Assessing the forest's aboveground biomass and carbon traditionally involves intricate and expensive processes necessitating the expertise of diverse professionals and specialized equipment. Hence, this study investigated the utilization of Geographic Information System (GIS) and Remote Sensing (RS) technology, employing Landsat bands to calculate spectral indices and construct linear models for predicting the aboveground carbon sequestration potential of the tropical rainforest ecosystem within the Oluwa Forest Reserve. The measured aboveground carbon from sample plots, alongside the estimated spectral indices, was utilized to simulate the distribution of aboveground carbon across the Oluwa Forest Reserve. A positive linear correlation was identified between the observed data and the estimated spectral indices. Consequently, linear models were developed, and the most suitable model was determined through statistical analysis. The average aboveground carbon estimated from the sample plots was 150.70 tons per hectare (t/ha), closely aligning with the predicted value of 149.80 t/ha. Statistical analysis yielded a coefficient of determination of 94% and a Root Mean Square Error of 6.38E-16. These results indicate that the selected model accurately predicts the distribution of aboveground carbon within the Oluwa Forest Reserve. This study underscores the importance of spectral data, GIS, and RS in the efficient modelling and mapping of aboveground carbon in extensive forest ecosystems.

Mapping eating disorders in adolescents and young adults: an investigation of geographic distribution and access to care in Ontario, Canada

BackgroundThere is limited research on the spatial distribution of eating disorders and the proximity to available eating disorder services. Therefore, this study investigates the distribution of eating disorders among adolescents and young adults in Ontario, Canada, with a specific focus on geographic disparities and access to publicly-funded specialized eating disorder services.MethodsA community sample of 1,377 adolescents and young adults ages 16–30 across Ontario between November and December 2021 participated in this study and completed the Eating Disorder Examination Questionnaire. Utilizing Geographic Information System (GIS) technology, we mapped the geographic prevalence of eating disorders and examined proximity to specialized eating disorder services. Multiple linear and logistic regression analyses were utilized to determine the association between geographic region and eating disorder symptomatology. Additionally, t-tests were utilized to examine differences between time/distance to specialized services and clinical risk for eating disorders.ResultsApplying geospatial analysis techniques, we detected significant spatial clusters denoting higher eating disorder scores in rural areas and areas with fewer specialized services. Likewise, our findings report disparities between rural and urban areas, suggesting that rural regions exhibit elevated rates of eating disorders. There were no associations between distance/time to services and eating disorder symptomology.ConclusionsThe discrepancies in eating disorder symptomology between urban/rural may stem from stigma and unique socio-cultural contexts in rural communities. The study underscores the need for targeted intervention, including telehealth, in addressing the eating disorder challenges faced by adolescents and young adults in rural regions.

Methodology to assess the impact of urban vegetation on the energy consumption of residential buildings. Case study in a Mediterranean city

The global growth of urban areas is unstoppable, and this growth is accompanied by an intensification of urban heat island effects, exacerbating the challenges of climate change and sustainable urban development in warm climates. In this context, understanding the intricate dynamics of these phenomena and their implications on the thermal behaviour of buildings becomes paramount. This study focuses on València, a Spanish city characterized by a Mediterranean climate, where the interplay between ground temperature variations, vegetation levels, and the thermal demands of buildings is investigated.Land surface temperature measurements derived from satellite data, specifically from the Landsat-8 mission, provide a valuable lens through which to assess the heat island effect. These measurements are harmonized with data collected from local weather stations to establish a robust foundation for evaluating the thermal dynamics of the urban environment. European standards, coupled with Geographic Information System technologies, enable the simulation of temperature variations, and facilitate a nuanced analysis of their impact on the thermal demands of a building.Moreover, recognizing the crucial role played by the urban climate in the influencing of heating and cooling needs, this study explores nature-based solutions implemented in València. By leveraging satellite-derived temperature and vegetation data over an extended period, it is possible to identify actions and elements that contribute positively to mitigating UHI effects and improving the overall climatic conditions. Results indicate that vegetation has a notable impact on local temperature, with distinct patterns observed in different seasons. The research incorporated the simulation of climate scenarios, introducing varying levels of vegetation. Results demonstrated a substantial reduction in cooling demand, particularly during the summer months. Buildings with a lower exterior surface-to-volume ratio exhibited a more pronounced reduction in energy consumption.

Tracking Urban Sprawl: A Systematic Review and Bibliometric Analysis of Spatio-Temporal Patterns Using Remote Sensing and GIS

The urban sprawl phenomenon refers to the expansion of urban areas driven by high population growth and migration. A spatio-temporal approach is indispensable in urban sprawl research. Monitoring and evaluating urban sprawl in a region is crucial for controlling drastic environmental changes. Integrated Remote Sensing (RS) and Geographic Information System (GIS) technologies can serve as essential tools for this purpose. The aim of this systematic literature review paper is to gather information on the latest data, methods, and findings to be considered in future urban sprawl research. The PRISMA method was employed, involving filtering from the Scopus database, resulting in 30 papers selected for an in-depth review to address the objectives of this paper. Landsat data remains the preferred choice for monitoring changes due to its extensive historical archive compared to other data sources. Landscape metrics represent a more advanced method com-pared to conventional change detection in quantifying urban sprawl. Other indices and quantifiers are also used to support the quantification of urban sprawl. Two perspectives exist in selecting the study's temporal intervals: consistent and inconsistent, which are adjusted based on the natural characteristics of "change," namely "abrupt" and "gradual." Suggestions for future research include using data with detailed spatial resolution and narrow study intervals while considering the patterns of urban sprawl formation.

Modernizing Land Survey Techniques in East Africa: Challenges and Opportunities

As East Africa undergoes rapid urbanization and economic growth, the need for modernized land survey techniques has become critical. Traditional methods are insufficient for keeping up with the evolving landscape. This article explores the adoption of advanced technologies such as Geographic Information Systems (GIS), remote sensing, and drone technology in land surveying. These innovations promise enhanced accuracy, efficiency, and comprehensive data collection, benefiting urban planning, infrastructure development, and environmental management. However, the transition is challenged by infrastructural deficits, high costs, limited technical expertise, and outdated regulatory frameworks. This article discusses the current technological advancements, challenges, and opportunities for improvement, emphasizing the need for investments in infrastructure, public-private partnerships, capacity building, and regulatory reforms. Vital information were sorted from recent related published database and utilised in writing this paper. Modernizing land survey techniques in East Africa holds significant potential to support sustainable development and effective land management practices. Keywords: Geographic Information Systems (GIS), Remote Sensing, Drone Technology, Land Survey Modernization, East Africa Development

Soil quality assessment and mapping in basaltic terrain of Central India for sustainable soil and crop management using integrated PCA and GIS

The cereal-based cropping system plays a vital role in ensuring food security in the Indian subcontinent. However, the productivity of these systems has seen a continuous decline due to the degradation of soil quality. This study aims to develop a Soil Quality Index (SQI) for such cropping systems. A detailed survey was conducted in the Bareli watershed of Seoni district, Madhya Pradesh, at a 1:10000 scale using high-resolution satellite data and Geographic Information System (GIS) technology. The survey identified and mapped 5 soil series: Diwartola, Diwara, Bareli-1, Bareli-2 and Bareli-3. Soil quality was evaluated based on morphological, physical and chemical properties as well as fertility parameters. Key indicators for soil quality assessment included sand, silt, clay content, bulk density, hydraulic conductivity, available water capacity and coefficient of linear extensibility (COLE). Additionally, pH, electrical conductivity, organic carbon, cation exchange capacity and nutrients like N, P, K, Fe, Mn, Cu and Zn were considered. The SQI was calculated using integrated principal component analysis, which involved selecting a minimum data set (MDS), assigning weights and scoring indicators. The results revealed that Diwartola soils had high quality (242.7 ha, 13.5 % TGA), Bareli-1 and Bareli-3 soils were of medium quality (462.8 ha, 25.7 % TGA), while Diwara and Bareli-2 soils were of low quality (966.1 ha, 53.8 % TGA). Agro-interventions such as agri-horticulture, agro-forestry, silvi-pasture, intensive cultivation and soil and water conservation measures were recommended based on the different mapping units.

Analyzing the Impact of Population Density on Hepatitis A Prevalence Using Geographic Information Systems (GIS) in Sudimoro District, Pacitan Regency

Background: This study examines the relationship between population density and Hepatitis A prevalence in Sudimoro District, Pacitan Regency, using data from 2019. Geographic Information Systems (GIS) technology was employed to analyze spatial patterns and correlations. Method: The research applied a quantitative approach, utilizing secondary data on Hepatitis A cases and population density. Simple linear correlation analysis revealed a moderate positive correlation (r = 0.48) between population density and the number of Hepatitis A cases, indicating that higher population density is associated with increased disease prevalence. Findings: Villages with high density, such as Gunung Rejo and Sudimoro, generally reported more cases, while those with lower density showed fewer cases. However, anomalies like Sembowo, which has high density but fewer cases, suggest that other local factors, such as sanitation and healthcare access, also play significant roles. The study underscores the importance of targeting high-density areas for public health interventions while considering additional factors influencing disease spread. Further research is recommended to explore these variables in more detail.

Urban Geothermal Resource Potential Mapping Using Data-Driven Models—A Case Study of Zhuhai City

Geothermal energy, with its promise of sustainability and a minimal environmental impact, offers a viable alternative to fossil fuels that can allow us to meet the increasing energy demands while mitigating concerns over climate change. Urban areas, with their large energy consumption, stand to benefit significantly from the integration of geothermal systems. With the growing need to harness renewable energy sources efficiently, the detection of urban subsurface resources represents a critical frontier in the pursuit of sustainability. The Guangdong Bay area, known for its abundant geothermal resources, stands at the forefront of this green energy revolution, so, in our study, we chose to evaluate Zhuhai City, which is a city representative of the resource-rich area of Guangdong. With the progress of geographic information system (GIS) technology, the land surface temperature (LST) has been used to monitor the spatial distribution characteristics of geothermal anomalies. However, relatively few studies have been conducted in the field of urban geothermal resources. In this study, we calculated the LST of Zhuhai City using Landsat 8 remote sensing data and then investigated the distributions of geothermal hot springs. Spatial data layers were constructed, including the geological structure, DEM and derivatives, lithology, and urban regions, and, based on technology with the integration of machine learning, their spatial correlations with geothermal anomalies were analyzed. The support vector machine (SVM) and the multilayer perceptron (MLP) were employed to produce maps of potential geothermal resources, and their susceptibility levels were divided into five classes: very low, low, moderate, high, and very high. Through model interpretation, we found the moderate-susceptibility class to dominate at 26.90% (SVM) and 46.27% (MLP) according to the two models. Considering the influence of artificial areas, we also corrected the original LST by identifying urban areas of thermal anomalies via the urban thermal anomaly leapfrog fusion extraction (UTALFE) method; following this augmentation, the results shifted to 24.16% (SVM) and 28.67% (MLP). Meanwhile, the area under the curve (AUC) values of all results were greater than 0.65, showing the superior performance and the high applicability of the chosen study area. This study demonstrates that data-driven models integrating thermal infrared remote sensing technology are a promising tool for the mapping of potential urban geothermal resources for further exploration. Moreover, after correction, the reclassified LST results of urban areas are more authentic and suitable for the mapping of potential geothermal resources. In the future, the method applied in this study may be considered in the exploration of more southeastern coastal cities in China.

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).

Strategic Enhancement of Healthcare Services During the Hajj Season in Makkah: A Comprehensive Geographic Information System (GIS) Analysis.

Annually, over two million international pilgrims embark on the Hajj pilgrimage to Makkah, presenting a significant challenge for healthcare services. This study analyzes the spatial distribution of healthcare facilities in the Al Mashaer area using Geographic Information System (GIS) technology to enhance healthcare during this religious gathering. It evaluates the accessibility and efficacy of healthcare facilities, including primary care centers, clinics, and hospitals, each addressing distinct medical needs to ensure a holistic approach for pilgrims. The study maps the distribution, service radius, and services offered by each facility, along with an analysis of travel distances and times, to evaluate the viability of healthcare services. Identifying coverage gaps and accessibility issues is critical for making strategic recommendations to enhance resource allocation and distribution. The research addresses challenges such as data precision, population density, infrastructural constraints, and resource limitations. The study offers recommendations to optimize resource distribution, improve transportation strategies, expand healthcare capacity, and enhance cultural competency, resulting in improved healthcare accessibility, reduced congestion, quicker medical responses, and a safer pilgrimage experience, promoting a world-class pilgrimage management system.