Geographic Information System Technology Research Articles

Groundwater Quality Prediction and Analysis Using Machine Learning Models and Geospatial Technology

The most prominent source of drinking water is groundwater, followed by lakes and reservoirs. Hydrological parameters like temperature, dissolved oxygen, pH, conductivity, ORP, and turbidity often change due to waste dumping into natural drinking water sources, particularly in densely populated areas. As a result, the water quality must be tested before public consumption to ensure healthy living in society. This research collected water samples from 129 wells in the Kanchipuram district in Tamil Nadu, India. An efficient integrated machine-learning-based prediction model has been proposed and modeled to determine the groundwater quality index (GQI). Several machine learning models were used to predict the water’s quality, including the naïve Bayes model, the KNN classifier, and the XGBoost classifier. Water quality predictions in 2024 were made using a combination of classification algorithms and models based on long short-term memory (LSTM) neural networks. The projected water quality characteristics were analyzed using geographical information system (GIS) technology to better understand and visualize the results. The XGBoost classifier model outperforms prior findings in the literature, with an accuracy of roughly 94.6%. The classification and prediction model was validated using collected and tested current data samples from a selected well. The findings were accurate within the 5% error range, promoting sustainability.

Common open source WebGIS platform for spatial and non-spatial data to enhance health services in Sri Lanka

This study explores the transformative potential and current limitations of Geographic Information Systems (GIS) in the context of Sri Lanka's health sector and broader development initiatives. Despite the global GIS market's expected growth to billions by 2025, driven by its adoption in infrastructure, urban planning, and the integration with emerging technologies, its application in critical areas such as public health, disaster management, and citizen services remains underutilized. This underutilization stems from a lack of ground-level information, limited knowledge of GIS capabilities, restricted access to essential geospatial data, and the high cost of GIS software. This paper discusses the significant hurdles in obtaining updated and comprehensive citizen, household, and health-related information, which impedes effective planning and decision-making within the health sector of Sri Lanka. It further examines the initiatives by the Ministry of Health, supported by the Asian Development Bank, to implement a GIS-based Health Mapping System focused on infrastructure and inventory management of health facilities, yet lacking in integrating critical citizen data for demand analysis of health services. The study underscores the necessity for a comprehensive "Geographical Citizen Information System for the Health Sector in Sri Lanka" akin to those in developed countries, to host, process, and analyze spatial and non-spatial information for enhanced policymaking and development planning. Through an analysis of current challenges and the exploration of potential solutions, this paper advocates for an integrated approach to harness the full capabilities of GIS technologies, thereby enabling more informed and effective governance in Sri Lanka’s Health sector.

Geomatics: Technology and Applications - A Training Programme for Women Scientists

Abstract. Geomatics, also known as geospatial technology and geomatics engineering, analyzes spatially referenced geographical information. Geomatics is a scientific term. It consists of tools and techniques. Technology is advancing, and modern Geomatics has the utility of maps by analyzing it with many coverages, each with interrelated themes combined to give meaningful answers for decision-makers. A multidisciplinary approach is essential to analyze spatial and nonspatial parameters together for decision-making at the local and global levels. Spatial information represented in the form of thematic maps about the respective attribute data, the system called, Geographical Information System (GIS), has been more popular during the last decades in government and private sectors. The decision support system can take input of data from these sources and analyze multiple parameters together to plan and manage available resources. This training program was intended for women scientists, researchers, academia, and professionals who were engaged and using spatial information, and who wanted to add and upgrade their skills. It was anticipated that a proportion of the trainee participants would come from research and academia. This training program helped participants generate interest in the use of GIS technology in their respective research and professional domains. This paper elaborately describes the process, and structure of the short-term capacity-building training program, and its usefulness for young scientists and professionals, specifically a target group is ‘women in science’ who have not been able to remain in the continue its use and are interested in building a career in geospatial technology field.

Spatiotemporal Changes and Utilization Intensity of the Zhoushan Archipelago Coastline over Four Decades

Coastal changes in China, notably in the Zhoushan Islands, have primarily been driven by coastal reclamation since the establishment of New China. This study conducted a comprehensive analysis of the Zhoushan Archipelago shoreline spanning four decades, employing remote sensing, aerial photographs, and shoreline data since 1984, along with GIS (Geographic Information System) technology. We assessed shoreline changes using the shoreline change index and shoreline artificialization index, as well as examined the influence of the Yangtze River’s suspended sediment and impoldering activities on Zhoushan’s shoreline. Furthermore, the correlation between local economic development and shoreline development was explored. The results revealed the following key findings: (1) From 1984 to 2018, the Zhoushan Archipelago shoreline decreased by 7.05 km. Temporally, the shoreline change index was −0.08%, with the most significant reduction occurring between 2008 and 2018. Spatially, differences among island groups were not pronounced. (2) The shoreline diversity index consistently increased, indicating greater diversity and complexity in shoreline use over the four decades. (3) The shoreline artificiality index steadily rose, particularly after 2000. It was highest in the south, followed by the center, and lowest in the north. (4) The intensity index of coastal land use continuously increased, with the southern island group having a higher index compared to the Zhoushan Islands. (5) The Yangtze River contributed significantly to sand inflow, influencing shoreline changes and beach shaping in Zhejiang. However, reclamation projects were identified as the primary and direct factor. (6) A positive correlation existed between Zhoushan City’s economic development and the intensity of coastal land use. This study emphasized the need for improving the control over reclamation projects and the better management of coastal protection and use. These measures could optimize resource allocation and establish a more scientific and rational coastal zone pattern.

Recent innovations in land capability classification for sustainable development: a brief overview.

Land is a finite resource that must be managed wisely to ensure its sustainability. Consequently, land evaluation has become essential. Identifying and utilizing productive capacity of land efficiently and profitably is crucial; otherwise, resource degradation can severely impact natural ecosystems and food production. Over the years, various methodologies have been employed to assess land resources, and one such method is the Land Capability Classification (LCC). LCC is a widely used and fundamental approach to land-use planning, traditionally assessing land based on its intrinsic qualities and climate. This study aims to highlight new approaches and developments in land evaluation techniques. It provides a brief overview of recent technological and scientific advancements integrated into land evaluation. The findings suggest that LCC alone is inadequate for precise land assessment, emphasizing the need to integrate new technologies. Remote Sensing (RS) and Geographic Information System (GIS) technologies are becoming increasingly significant. Integrating various software, decision-making systems, and mathematical models can also enhance the accuracy of land assessment results. The continuous advancement of GIS and remote sensing technologies is paving the way for new tools to facilitate natural resource mapping, appraisal, surveillance, and management. Utilizing these technologies for future projections will be highly beneficial in accurately assessing the long-term impacts of current land management practices.

Developing a digital management system for museum collections using RFID and enhanced GIS technology

In recent years, the integration of Radio Frequency Identification (RFID) technology with deep learning has revolutionized the Internet of Things (IoT), leading to significant advancements in object identification, management, and control. Museums, which rely heavily on the meticulous management of collections, require precise and efficient systems to monitor and oversee their valuable assets. Traditional methods for tracking and managing museum collections often fall short in providing real-time updates and ensuring optimal environmental conditions for preservation. These shortcomings place a considerable burden on museum staff, who must manually track, inspect, and maintain extensive collections. This study addresses these challenges by proposing an advanced electronic management system that leverages the synergy between RFID technology and Geographical Information Systems (GIS). By integrating an enhanced LANDMARC algorithm into our geoinformation framework, the system visually represents the real-time location of museum collections on custom electronic maps, significantly improving the accuracy and timeliness of environmental monitoring. Additionally, RFID technology is utilized to continuously identify the real-time location of museum staff, facilitating the evaluation of their inspection tasks. This dual approach not only enhances the operational efficiency of collection management but also supports the development of intelligent, automated systems for museums, advancing the application of RFID technology in item identification and location management.

Prospects for the development of cartography through the integration of SLAM technology with GIS technology

Abstract. With the continued development of Simultaneous Localization and Mapping (SLAM) and Geographic Information Systems (GIS) technologies, their application scenarios have become increasingly complex. Combining these technologies can significantly enhance operational efficiency in challenging environments. This paper presents an analysis of existing cases where SLAM and GIS technologies have been integrated, demonstrating that such a merger facilitates the consolidation and complementarity of spatial data. This integration allows robots or systems to simultaneously utilize the global information provided by GIS and the dynamic local data captured by SLAM for a more comprehensive and detailed environmental analysis, which is highly beneficial for the field of cartography. Further research has developed a series of operational procedures for integrating SLAM and GIS, utilizing MATLAB as a tool. This study also reviews several existing technical challenges, including real-time performance and computational capacity, environmental complexity and dynamic changes, and multi-scale data processing, and proposes potential solutions. The paper concludes by predicting that the integration of SLAM and GIS will play a crucial role in areas such as smart city management and disaster emergency response, indicating that this research area will become a hot topic in future cartographic technology.

Reviewing the Impact of Engineering Measures on Soil Erosion in Jammu and Kashmir Anantnag Watershed

Planners now find that stopping soil loss in India's watersheds must be their top priority. Currently, a wide range of mathematical models are used worldwide to predict soil erosion. The Revised Universal Soil Loss Equation (RUSLE), which is frequently used to predict average soil loss, is one such model. Recently, there has been an increased emphasis on applying USLE/RUSLE in conjunction with Geographic Information System (GIS) technology, enabling grid-based analysis for predicting soil erosion and aiding management methods. This study assesses the efficacy of flood control and erosion management programs launched in 1914. Four different maps representing the possible erosion threats were created for four different time periods, and a comparison study was carried out to assess the changes that occurred. The implementation of various strategies such as terracing, afforestation, and rehabilitation in the watershed led to a noteworthy prediction of decreased soil loss in the watershed. In the temperate region of Jammu and Kashmir and sparsely vegetated areas, the rate of anticipated soil loss decreased from 632 to 378 metric tons per hectare per year between 1990 and 2020, indicating the efficacy of soil conservation measures in mitigating potential soil loss.

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.

GIS and Bhuvan Data as Tools for Agricultural Development and Economic Empowerment in Pune District

This paper examines the use of Geographic Information Systems (GIS) and Bhuvan data to enhance agricultural development and drive economic empowerment in Pune District, Maharashtra, India. GIS technology has been instrumental in optimizing water management, land utilization, and crop management. Likewise, Bhuvan data plays a critical role in monitoring crop growth, identifying diseases, and evaluating land use patterns. These advancements contribute to improved crop yields and increased profits for farmers. The paper highlights the significant impact of GIS and Bhuvan data in promoting agricultural progress in Pune district and suggests that these tools could be effectively implemented in other regions to achieve similar benefits.

Site Selection of Large Shopping Malls in Wanbailin District of Taiyuan City

The construction and site selection of shopping malls are directly related to their commercial operation effectiveness and market competitiveness. Some scholars have conducted extensive research in this field, particularly achieving notable results in terms of influencing factors, methodologies, and technological applications for site selection, yet there are still some deficiencies. Traditional site selection methods primarily rely on qualitative analysis and empirical judgment. However, with technological advancements, Geographic Information System technology has gradually been applied to shopping mall site selection. GIS technology enables the integration of multiple data sources, spatial analysis, and visualization, providing a scientific basis for site selection decisions. This article utilizes ArcGIS software to construct an application model for shopping mall site selection in Wanbailin District. Through spatial analysis, eligible areas are identified, achieving a scientific and visual approach to site selection. By considering the main factors affecting the location of large shopping malls in Wanbailin District and using ArcGIS as the basic platform, an application model is built to find the optimal location for building shopping malls. The results show that introducing GIS into mall location planning improves efficiency and accuracy while providing a reliable basis for scientific location.

Locating the suitable large-scale solar farms in China's deserts with environmental considerations

Desert areas offer rich solar resources and low land use costs, ideal for large-scale new energy development. However, desert ecosystems are fragile, and large-scale photovoltaic (PV) power facilities pose ecological risks. Current assessments of PV plant sites in deserts lack consideration of wind-sand hazards and ecological impacts. In this study, we have developed a new large-scale photovoltaic (PV) site selection model that integrates the analytic hierarchy process with geographic information system technology, and applies it to the desert regions of China. The results show that the potential for large-scale PV power plants in China's deserts is significant, with 69.4 % of the region assessed as medium or higher. The most suitable area is 12.7 × 104 km2 (7.6 % of the overall study area), mainly centered in the Tibetan Plateau's Qaidam Basin Desert and the deserts of northern China, characterized by favorable solar resources, climate, and terrain. Across all regions, gravel deserts are recognized as more suitable for the construction of large-scale PV power projects than sandy deserts. Considering varying PV installation density scenarios with an installed capacity potential of 36.4–84.9 TW and system costs ranging from 10.0 to 33.5 trillion USD, the study estimates an annual solar power generation potential of 47–110 PWh which is 1.7–3.9 times the global electricity demand. Carbon emissions could be reduced by 26.8–62.6 gigatons annually, offsetting 73–170 % of global emissions. Covering just 4.8–11.5 % of China's desert area (8 × 104–19.4 × 104 km2) would meet the projected 2025 electricity needs of the country. This study lays the groundwork for spatial planning and benefit assessment of large-scale PV projects in desert regions, and reduces conflicts between PV plant construction and local ecosystem.

Agricultural Land Use Mapping Analysis Using the Geographic Information System in Temu Village

The agricultural sector remains a significant source of income for the people of East Sumba, particularly in Temu Village, Kanatang District, which spans 46.50 km². In Temu Village, a large portion of the population engages in farming and gardening, utilizing agricultural land that includes rice fields, fields, and plantations. Analyzing the current use of this land is crucial for predicting agricultural yields and proposing optimal land use strategies to ensure sufficient local food production. However, the distribution of agricultural land has not been thoroughly mapped, leaving gaps in information regarding the location and potential of these lands. This research aims to map the agricultural potential of Temu Village using Geographic Information System (GIS) technology through overlay and scoring methods, resulting in informative land use maps. The findings reveal that fields dominate the agricultural landscape with 1.648903 km² or 81.10% of the total agricultural land, highlighting the primary focus on field crops. Rice fields cover 0.270512 km² or 13.30%, while gardens occupy the smallest area of 0.113825 km² or 5.60%. These results demonstrate the potential for effective geographical management of plantations, rice fields, and agricultural fields based on their respective areas.

The application of GIS technology in building a multivariate taphonomic profile for improving PMI estimations in Greece.

Environmental conditions highly affect decomposition rates and therefore a forensic practitioner should consider context-specific information when estimating the post mortem interval (PMI). Traditional methods of collecting environmental data, however, are time-consuming and often impractical for large-scale studies or routine forensic investigations. This study developed an automated computer method by employing the technology of geographic information systems (GIS) and Python programming language to provide contextual information for bodies found outdoors in Greece. The generated coding script underwent testing on 95 bodies in various stages of decomposition, which were examined between the years 1999 and 2022 at the National and Kapodistrian University of Athens and the Forensic Medical Service of Thessaloniki. Using ArcGIS Pro software and publicly available online data, a multilayer map was developed. Individual layers included high-resolution aerial images and data on the European Nature Information System ecosystem type, the Köppen-Geiger climatic type, the population density, the elevation, and the slope. Additionally, 99 national weather stations and their corresponding meteorological data were integrated. By leveraging the geographical coordinates of the recovery site of each case and information about the decedent's disappearance and recovery dates, this script automatically generates details from each of the above layers. Additionally, it calculates the accumulated degree days (ADD) and accumulated humidity days (AHD) values by extracting data from the nearest weather station. The GIS-based approach enables rapid, objective, and reproducible taphonomic profile construction, which can greatly improve the reliability of PMI estimations. By utilizing this method, forensic practitioners can accurately evaluate environmental effects on decomposition, thus standardizing taphonomic profiling globally.

Ever-shifting border: West Bank case study, Palestine

ABSTRACT In 1949, the West Bank “Green Line” (or the “Armistice Line”) was established and drawn on maps of Palestine, but it is not a firm border: the line is continuously shifting due to its elastic and virtual nature. The border in the region has shifted to accommodate Israeli expansion strategies. Colonies, checkpoints, military areas, security zones, and a physical wall are the driving forces of border elasticity and dynamics. This study aims to shed light on the chronological border shifting by Israel, leading to changes in the current border situation on the ground. The research presented here focuses on a study area of 30 × 30-km sq, in which the border was shifted many times inside the West Bank region. Geographic Information System (GIS) technologies were used as the main analytical tool. The outcomes of the research are maps illustrating the border shifts and its reasons.

Geo-Spatial Technology for Identifying Optimal Well Locations in Kolugala Pahalagama Grama Niladhari Division for Effective Groundwater Management

This study utilized Geographic Information System (GIS) technology to pinpoint optimal locations for establishing wells, addressing the issue of declining water yields in the Kolugala Pahalagama Grama Niladhari Division (GND); a geographically diverse region. The research integrated geospatial data, including geolocations of sample wells, garbage pits and quarterly water level measurements collected through field surveys. Several thematic layers, namely, geology, elevation, slope, drainage density, soil type, and land use types were analysed to delineate groundwater potential zones within the GND. Satti's analysis hierarchy was employed to assign appropriate weights to these factors, reflecting their influence on groundwater recharge and well productivity. Spatial analysis revealed that 9.64% of the area displayed very good groundwater potential, 42.17% had good potential, 39.76% showed moderate potential, and 7.23% exhibited poor potential. The distribution of existing wells was also evaluated, showing that 6% were located in very good groundwater potential zones, 56% in good groundwater potential zones and 38% in moderate groundwater potential zones. Despite this, only 34% of the wells were placed in regions suitable for the establishment of wells, while the majority, 66%, were located in unsuitable areas. Notably, 18 wells displayed lower water levels, likely due to their excessive distance from neig-bouring wells. Further spatial analysis identified 29 hectares as unsuitable and 54 hectares as suitable for the future establishment of wells. These findings underscore the significance of geographic factors in the placement of wells, emphasising the need for strategic planning to ensure that wells are sited in areas with high groundwater potential, thus improving long-term water yield sustain-ability in the region.

Assessing Land Use Ecological-Social-Production Functions and Interrelationships from the Perspective of Multifunctional Landscape in a Transitional Zone between Qinghai-Tibet Plateau and Loess Plateau

Investigating the evolution and drivers of multifunctional land use is essential for sustainable land management and regional biological conservation. This research focuses on the Hehuang Valley, where we developed an “ecological-social-production” evaluation system for assessing land use multifunctionality from the perspective of multifunctional landscape. Leveraging Geographic Information System technologies, we conducted a quantitative analysis of spatiotemporal variations in multifunctional land use across the valley in recently twenty years. Correlation coefficients were employed to identify trade-offs and synergies among various land use functions. Additionally, geographical detector and grey relational analysis models were utilized to pinpoint the factors influencing spatiotemporal changes in land use functions during the specified period. The results showed that: (1) During the period, the overall multifunctionality of land use in the Hehuang Valley exhibited an increasing trend. The economic production function of the land showed the highest growth, while the ecological and social functions showed lower growth. (2) In most areas of the Hehuang Valley, there was a positive correlation between social and economic production functions and a negative correlation between social and ecological functions, as well as between economic production and ecological functions. (3) Natural conditions were the main factors of spatial variation of land use comprehensive functions, but human factors, including land use intensity and the rate of farmland conversion to non-agricultural uses, were the primary drivers of temporal changes in multifunctional land use. The findings provide valuable references and scientific support for policymakers in optimizing land use and multifunctional landscape conservation.

Mapping new psychoactive substances: Leveraging GIS technology for advanced global surveillance and policy support

The escalating challenge of New Psychoactive Substances (NPS) necessitates enhanced global monitoring and analysis capabilities. This study introduces an advanced interactive visualization tool that employs Geographic Information System (GIS) technologies to improve the functionality of the UNODC's Early Warning Advisory. The tool enables dynamic observation and analysis of NPS's geographical and temporal distribution, thereby facilitating a comprehensive understanding of their public health impacts. By incorporating detailed choropleth maps and annual and cumulative bar charts, the tool allows policymakers and researchers to visually track and analyze trends in NPS usage and control efforts across different regions. The results demonstrate the tool's effectiveness in providing actionable insights, which support the strategic development of public health policies and interventions to curb the global rise in NPS usage. This initiative illustrates the essential role of digital tools in enhancing public health strategies and responses to emerging drug trends. This rising challenge underscores the urgent need for innovative solutions in monitoring drug trends, a theme explored in this paper. The web tool is available at https://nps-vis.cmdm.tw, and the code is available at https://github.com/CMDM-Lab/nps-vis.

Sustainable Spatial Distribution and Determinants of Key Rural Tourism Villages in China: Promoting Balanced Regional Development

Understanding the spatial distribution and sustainable development of rural tourism is essential for promoting balanced regional growth and formulating optimized policy strategies. This study aims to provide insights into sustainable development and policy optimization. Utilizing geographic information system technology, dominance analysis, and Geodetector statistical methods, this research offers a comprehensive examination of the spatial patterns and determinants of these distributions. The findings reveal significant regional disparities and clustering, with a higher concentration of key villages in economically developed eastern and central regions and fewer in the less developed western regions. The dominance analysis highlights that provinces such as Zhejiang, Shandong, and Beijing demonstrate strong advantages across multiple dimensions, including ecological environment, economic development, tourism infrastructure, transportation accessibility, policy support, and social development. Conversely, regions such as Ningxia, Qinghai, and Tibet exhibit lower dominance scores, indicating challenges in rural tourism development due to limited resources and infrastructure. Key influencing factors include forest coverage, GDP per capita, the number of star-rated hotels, transportation network density, policy initiatives, and urbanization rates. The results underscore the importance of a multi-dimensional approach to enhance rural tourism competitiveness and suggest targeted strategies for underperforming regions. This study contributes to advancing the theoretical framework of sustainable rural tourism and provides actionable insights for policymakers to foster balanced regional development, ecological conservation, and community-centered tourism practices.

Hydrogeological mapping of fracture networks using earth observation data to improve rainfall–runoff modeling in arid mountains, Saudi Arabia

Abstract Rainfall–runoff modeling is essential for the hydrological analysis of basins; however, the traditional modeling approach does not incorporate geological features such as fractures and fissures in the modeling task. These features are significant in the water loss during a rainstorm, which should be incorporated to obtain realistic rainfall–runoff results. A novel approach is presented here in to quantify the geological features and link them to the curve number (CN) method. The proposed methodology has not been applied in the literature. This approach is validated on five gauged basins, namely, Yiba, Al Lith, Liyya, Habawnah, and Tabalah, in the southwest part of Saudi Arabia. Four major stages are conducted. The first stage is the extraction of the geological lineaments using remote sensing and geographical information system technology; the second stage is estimating CN from rainfall–runoff data; the third stage is developing a relationship between CN and lineament density (LD); and the final stage is evaluating the developed equations on hydrological response. The least-squares method is employed to minimize the difference between observed and predicted runoff and determine the optimum range of CN. The research provides a comprehensive understanding of hydrological processes in fractured geologic systems and explores the influence of fractures on curve number. This study identifies two major lineament trends aligned with the Arabian trend direction, namely, north-northwest (NNW)–south-southeast (SSE) and north-northeast (NNE)–south-southwest (SSW). Furthermore, a moderate inverse correlation is established between LD and CN, highlighting the significance of geologic fractures on the hydrological response. The findings of this study provide insight into how the geological fissures in the mountainous region affected the rainfall–runoff response that leads to a low value of CN due to the water loss in the fissures and faults. As a result, this study clearly demonstrates the importance of the geological structures on rainfall–runoff responses.