Geographic Information System Technology Research Articles

Hybrid delineation of landforms: Case of Bystrytsia-Pidbuzka drainage basin

Landforms, together with geological substrate and geomorphic processes, are essential for delineation of geoecosystems, which are indispensable for environmental management at landscape and regional levels. Geomorphometry is a geographic information system technology, which affords quantitative land-surface analysis and landform delineation using digital elevation models (DEM). Application of geomorphometry has been fostered by the emergence of free global high-resolution DEMs. However, automated geomorphometric extraction of landforms for flat areas, like wide river valleys, may be problematic owing to insufficient accuracy of the DEM. We selected the Bystrytsia-Pidbuzka drainage basin of 500 km², which has a transitional location between low flysch External Carpathian Mountains and wavy denudation-alluvial plains of the Fore-Carpathian Upland in Lviv Oblast (Ukraine), to test a hybrid methodology of landform delineation – manual and automated geomorphometric. We considered regional landforms as orotectonic units (morphostructures), which are used to characterize ecoregions, and morpholithotopes as the smallest local landforms – mesorelief elements together with surface deposits and current geomorphic processes. FABDEM V1-2 with a resolution of 30*30 m was used as a primary geodataset of elevation data. Ecoregions and morpholithotopes of wide flat valley bottoms were delineated via manual interpretation of the DEM and ancillary data, while the morpholithotopes of the hilly and mountainous interfluves were delineated automatedly using three topographic variables: topographic position index, slope, and flow accumulation. Within the study area, we singled-out six microecoregions and four mesoecoregions: Upper Dnister Depression, Upper Dnister Upland, Marginal Beskydy, and Dnister Beskydy. There are 21 classes of morpholithotopes distinguished belonging to flat valley bottoms with alluvial and lacustrine deposits, narrow valleys and big gullies, as well as lower concave and upper convex slopes formed by colluvial and eluvial-colluvial deposits respectively, divided into four inclination categories, and two lithological groups. Each morpholithotope class is attributed with a drainage status and probable current geomorphic processes. The obtained dataset is oriented on further ecological application. Key words: morpholithotope; ecoregion; geomorphometry; FABDEM; the Carpathian Mountains; the Fore-Carpathian Upland.

Training and Utilization of Geographic Information Systems at Rahmatullah Lempake Samarinda Islamic Boarding School

The application of Geographic Information System (GIS) technology in education is becoming increasingly vital for enhancing digital literacy and spatial analysis skills. Rahmatullah Lempake Islamic Boarding School in Samarinda is one of the educational institutions with significant potential to utilize this technology in supporting the management of its environment and local resources. The initiative aims to provide students with training in GIS, enhancing their knowledge and skills in spatial data management and geographic analysis. The training employed a combination of lectures, discussions, and practical sessions using GIS software. It was attended by students aged 12 to 15 and covered foundational topics, such as an introduction to GIS, mapping applications, and data analysis techniques. The results of this training demonstrated a notable improvement in the students' understanding and basic GIS skills, as well as increased awareness of the technology's potential applications in their local environment. The integration of GIS into the educational process offers significant benefits, particularly in enhancing students' technological literacy and spatial analysis capabilities, which can be applied to environmental management activities within the Islamic boarding school. In conclusion, the GIS training at Rahmatullah Lempake Islamic Boarding School has effectively developed the students' foundational skills in technology and geographic analysis, offering practical benefits for future resource management and environmental planning endeavors.

A New Methodology for Estimating the Potential for Photovoltaic Electricity Generation on Urban Building Rooftops for Self-Consumption Applications

As the world increasingly embraces renewable energy as a sustainable power source, accurately assessing of solar energy potential becomes paramount. Photovoltaic (PV) systems, especially those integrated into urban rooftops, offer a promising solution to address the challenges posed by aging energy grids and rising fossil fuel prices. However, optimizing the placement of PV panels on rooftops remains a complex task due to factors like building shape, location, and the surrounding environment. This study introduces the Roof-Solar-Max methodology, which aims to maximize the placement of PV panels on urban rooftops while avoiding shading and panel overlap. Leveraging geographic information systems technology and 3D models, this methodology provides precise estimates of PV generation potential. Key contributions of this research include a roof categorization model, identification of PV-ready rooftops, optimal spatial distribution of PV panels, and innovative evaluation technology. Practical implementation in a real urban setting demonstrates the methodology’s utility for decision making in the planning and development of solar energy systems in urban areas. The main findings highlight substantial potential for PV energy generation in the studied urban area, with capacities reaching up to 444.44 kW. Furthermore, implementing PV systems on residential rooftops has proven to be an effective strategy for reducing CO2 emissions and addressing climate change, contributing to a cleaner and more sustainable energy mix in urban environments.

Optimizing site selection for construction and demolition waste resource treatment plants using a hesitant neutrosophic set: a case study in Xiamen, China

The site selection of construction and demolition waste resource treatment plants is a complicated multi-criteria decision-making (MCDM) issue of ‘not in my back yard’ (NIMBY) facilities, which is affected by spatial, economic, societal, environmental and other factors. Traditional site selection MCDM methods expose the shortcomings of evaluation information representation and spatial factor analysis. This study develops an optimized MCDM site selection method in a hesitant neutrosophic set (HNS) environment, capable of effectively handling uncertainty and fully incorporating spatial considerations. The innovation of this research lies in integrating HNS into MCDM, combined with geographic information system technology, revised DEMATEL-based analytic network process method, cosine similarity and Euclidean distance similarity measures. A case study in Xiamen, China, validates this method’s effectiveness, and sensitivity analysis and comparative studies demonstrate its superior stability, robustness and resolution. The main contribution of this study is the development of an MCDM optimization method for siting large-scale NIMBY facilities.

Enhancing municipal solid waste management efficiency through clustering: A case study

ABSTRACT This study leverages real-time datasets generated through IoT technology and smart city applications to enhance solid waste management in Yalova Province, Turkey. By integrating these datasets with the municipality’s Geographic Information System (GIS) using the ITRF/96 3 UTM X Y Coordinate System, a dynamic waste collection framework was established. The K-Means clustering algorithm was employed to determine the optimal waste container placement, considering capacities of 550, 800, 1,000, and 3,000 liters and walking distances of 50–100 ms. Results indicated that 1,000 and 3,000-liter containers with a 100-m walking distance maximized collection efficiency. Replacing 484 traditional containers with 105 units of 3,000 liters reduced total routes by 34%, transport costs by 42.2%, and CO2 emissions by 33.5%. The study underscores the importance of integrating GIS and IoT technologies for real-time waste management, aligning with the UN’s Sustainable Development Goals (SDG 11 and SDG 13). By combining data-driven decision-making with urban sustainability practices, it offers a replicable model for municipalities seeking to reduce costs and environmental impacts in waste collection.

Study of using GIS technologies in forestry cadastre and monitoring for environmental sustainability

Abstract The integration of Geographic Information Systems (GIS) technologies in the forestry cadastre and monitoring practices in Uzbekistan represents a significant advancement in sustainable forest management. This study explores the application of GIS in enhancing the accuracy, efficiency, and comprehensiveness of forestry cadastre, which is crucial for the effective management, conservation, and restoration of forest resources in Uzbekistan. Through spatial analysis, remote sensing, and data integration, GIS technologies offer detailed insights into forest cover, land use changes, and biodiversity, providing a robust framework for decision-making and policy formulation. The research highlights how GIS tools facilitate the precise mapping of forest boundaries, monitoring of illegal logging activities, and assessment of reforestation efforts. Furthermore, the study examines the challenges and opportunities in implementing GIS in Uzbekistan’s forestry sector, considering the country’s unique geographical and ecological context. The findings suggest that adopting GIS technologies can significantly contribute to achieving Uzbekistan’s environmental sustainability goals and improving the management of its forestry resources.

Study of monitoring of water bodies using remote sensing data and GIS technologies (Talimarjan water reservoir)

Abstract The study of water bodies using remote sensing data and Geographic Information System (GIS) technologies is crucial for effective water resource management. This research focuses on monitoring the Talimarjan water reservoir, a vital water source in Uzbekistan, by leveraging satellite imagery and GIS tools. Remote sensing offers a cost-effective and comprehensive approach to assess various parameters, including surface area, water quality, and seasonal fluctuations in water levels. By utilizing multi-temporal satellite data, changes in the reservoir’s volume and surrounding vegetation were analyzed. The integration of GIS technologies facilitated the mapping and spatial analysis of these changes, enabling the identification of trends and potential risks, such as sedimentation and water loss. The combination of remote sensing and GIS provides valuable insights into the health and sustainability of the water reservoir, aiding in decision-making for water management authorities. This study demonstrates the effectiveness of these technologies in environmental monitoring, highlighting their potential for broader applications in the management of water resources in arid regions. Through accurate, real-time data, remote sensing and GIS help in ensuring sustainable water use, promoting efficient resource management, and mitigating the impacts of climate change on water bodies.

Assessing Multi-Hazard Risk through Spatial Analysis: A Geographic Information Systems for Susceptibility Mapping in Java Island, Indonesia

Abstract The geographic location and population make Java Island a disaster-prone area with various threats, including earthquakes, floods, landslides, and volcanic eruptions. Based on historical data, these four types of disasters caused a total of US$24,303,159,688 in economic losses in the last 50 years. In regard to the big loss, it is considered important to identify potential disaster risks to avoid more sustainable economic losses in the future. By utilizing developments in Geographic Information Systems (GIS) technology, potential disaster risk mapping could be carried out. The process begins with preparing a map of the potential risk of earthquakes, floods, landslides, and volcanic eruptions by referring to the regulatory document of the head of the National Disaster Management Agency (BNPB) Number 2 of 2012 and Indonesian National Standard (SNI). Afterwards, the potential risk map for each type of disaster will be combined to determine the hazard level of each disaster in 1 square kilometer-sized pixels. The merging process uses annual economic loss data over a period of 50 years as a weighting factor. Based on the data, the results show that 11.554% (15.092 square kilometers) of the area of Java Island falls into the high hazard level class, 77.642% (101.413 square kilometers) into the moderate hazard level class, and 10.804% (14.112 square kilometers) into the low hazard level class. The resulting multi-hazard map could be further used for various specific purposes, such as creating an early warning system or estimating direct losses due to disasters.

Analisis Perubahan Tutupan Lahan di Kecamatan Pangururan Kabupaten Samosir Menggunakan Sistem Informasi Geografis

Land cover changes in Pangururan District, Samosir Regency, are a significant phenomenon due to population growth and development. This study aims to analyze land cover changes over the period 2018-2022 using Geographic Information System (GIS) technology and Sentinel-2 satellite imagery. The analysis was conducted using the overlay method to compare land cover maps from two different time periods. The results indicate an increase in agricultural land and built-up areas, along with a decrease in shrubland. These changes have impacted the environment and local communities, including erosion potential, declining soil quality, and urbanization. This study is expected to provide insights for sustainable land management in Samosir Regency.

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.

An Assessment of Land Use and Land Cover Changes on Urban Flooding: A Case Study in Sri Jayewardenepura Kotte

This study investigates the relationship between Land Use and Land Cover (LULC) changes and urban flooding in the Sri Jayewardenepura Kotte Divisional Secretariat Division (DSD). The research objectives include analysing flooding patterns, mapping LULC changes, and assessing the correlation between these changes and flooding occurrences. Additionally, a temporal rainfall variation analysis was conducted to provide further context. The study employed Geographic Information System (GIS) technology, specifically utilising ArcGIS for LULC classification and Inverse Distance Weighting (IDW) interpolation technique for rainfall data. The analysis reveals a clear association between heightened precipitation and major flood events. In 2010, the flood inundation area was 5.762 km² during the major flood in May, despite a monthly rainfall of over 650mm. However, in 2016, with over 700 mm of rainfall in May, the flood-inundated area was reduced to 4.046 km², highlighting the role of other factors such as wetland recovery. Moreover, it identifies significant LULC changes, emphasising rapid urbanisation and wetland decline. From 2009 to 2018, built-up areas increased from 11.49 km² to 14.18 km², while wetlands decreased from 2.29 km² in 2009 to 1.19 km² in 2015, before recovering slightly to 1.58 km² by 2018. The expansion of built-up areas is found to slightly increase flood risks, while wetland recovery acts as a natural flood buffer. This research underscores the importance of targeted interventions for urban flood resilience, such as flood-resistant infrastructure and wetland management. The findings provide critical insights for evidence-based urban planning and flood management strategies, aiming to create more resilient and sustainable urban environments.

Enhancing Fault Detection and Location Identification using GIS-based Techniques: A Case Study of Arba Minch Distribution System

ABSTRACT Fault detection and location in distribution systems are critical for maintaining reliable electric power supply and minimizing outage time. The Arba Minch District distribution department of Ethiopian Electric Utility (EEU) currently employs a manual trial-and-error approach for fault detection and location, which is inefficient, time-consuming, and ineffective in resolving faults. This study evaluates the current approach and proposes an enhanced system utilizing Geographic Information System (GIS) technology to improve fault detection and location in the Arba Minch distribution system, specifically the Shecha feeder. The implementation of GIS-based fault detection and location aims to address the limitations of the manual method and mitigate economic losses associated with feeder faults. ETAP GIS simulations successfully detected and located faults, achieving effective reduction in fault detection and location time compared to the conventional method. By optimizing fault detection and location time, the System Average Interruption Duration Index (SAIDI) for the feeder was significantly reduced. Consequently, the GIS system highly minimizes the economic losses associated with energy not supplied. The results demonstrate the potential of GIS technology in enhancing fault detection and location, ultimately improving the reliability and efficiency of the distribution system.

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.

Enhancing sustainability through GIS mapping for groundwater quality analysis

Abstract The current study attempts to develop sustainability by utilizing Geographic Information System (GIS) technology by examining groundwater quality in Rajahmundry by dividing the region into 1 km × 1 km grids, resulting in 45 different areas. The grids are thoroughly dispersed, and groundwater samples have been collected from a variety of sources, including open wells, hand pumps, and bore wells, in each grid in order to assess water quality. The evaluation includes a physico-chemical parameter namely, pH, total alkalinity, TDS, total hardness, calcium hardness, magnesium hardness, chloride, nitrates, and sulphates. The purpose of this study is to create a map of the spatial distribution of these groundwater qualities using GIS in order to obtain a general understanding of the current state of the entire valorisation of groundwater resources. The current approach is novel in that it not only allows detecting the issues affecting water quality but also enables developing specific approaches for the sustainable management and protection of groundwater in Rajahmundry. Overall, through GIS mapping and conclusive water quality assessment, the study provides a significant input into the field of environmental science in terms of enhancing water sustainability practices.