GIS-based Method Research Articles

Optimal Routing of Gas Pipelines in Seismic Regions Using an Efficient Decision-Support Tool: A Case Study in Northern Greece

High-pressure gas pipelines are significantly vulnerable to earthquake-related geohazards (tectonic faulting, slope instabilities, and/or soil liquefaction phenomena). Avoiding geohazardous areas is not always techno-economically feasible, as it would increase the length and cost of the infrastructure. Conversely, crossing these areas may adversely affect the structural performance of the pipeline, leading to unfeasible mitigation measures. Thus, selecting cost-effective, safe, and resilient routing is crucial. This study presents a GIS-based decision-support tool for optimal routing, taking into account, among other criteria, earthquake-related geohazards. The proposed tool considers not only the aforementioned but also more complex earthquake-related geohazards, such as secondary fault ruptures that are non-parallel or even perpendicular to the main fault, which might have been overlooked during the design of existing pipelines. To validate its effectiveness, the present tool is applied in a real case study in northern Greece, where the aforementioned earthquake-related geohazards coexist. Through a GIS-based multi-criteria decision method, various scenarios are examined by assigning different weights to the adopted criteria, and several cost-minimized routes are derived. This tool could be highly beneficial for the pipeline industry since it can assist operators and stakeholders in selecting the optimal pipeline route in geohazardous areas.

A Methodological Framework for High-Resolution Surface Urban Heat Island Mapping: Integration of UAS Remote Sensing, GIS, and the Local Climate Zoning Concept

The urban heat island effect (UHI) is among the major challenges of urban climate, which is continuously intensifying its impact on urban life and functioning. Against the backdrop of increasingly prolonged heatwaves observed in recent years, practical questions about adaptation measures in cities are growing—questions that traditional meteorological monitoring can hardly answer adequately. On the other hand, UHI has long been the focus of research interest, but due to the technological complexity of providing accurate spatially referenced data at high spatial resolution and the requirement to survey at strictly defined parts of the day, information provision is becoming a major challenge. This is one of the main reasons why UHI research results are less often used directly in urban spatial planning. However, advances in geospatial technologies, including unmanned aerial systems (UASs), are providing more and more reliable tools that can be applied to achieve better and higher-quality information resources that adequately characterize the UHI phenomenon. This paper presents a developed and tested methodology for the rapid and efficient assessment and mapping of the effects of surface urban heat island (SUHI). It is entirely based on the integrated use of data from unmanned aerial systems (UAS)-based remote sensing methods, including thermal photogrammetry and GIS-based analysis methods. The study follows the understanding that correct SUHI research depends on a proper understanding of the urban geosystem, its spatial and structural heterogeneity, and its functional systems, which in turn can only be achieved by supporting the research process with accurate and reliable information resources. In this regard, the possibilities offered by the proposed methodological scheme for efficient geospatial registration of SUHI variations at the microscale, including the calculation of intra-urban SUHI intensity, are discussed in detail. The methodology builds on classical approaches for using local climate zoning (LCZ), adding capabilities for precise delineation of individual zone types and for geostatistical characterization of the urban surface heat island (SUHI). Finally, the proposed scheme is based on state-of-the-art technological tools that provide flexible and automated capabilities to investigate the phenomenon at microscales, including by enabling flexible observation of its dynamics in terms of heat wave manifestation and evolution. Results are presented from a series of sequential tests conducted on the largest residential area in Bulgaria’s capital city, Sofia, in terms of area and population, over a relatively long period from 2021 to 2024.

An Analysis of the Spatiotemporal Distribution and Influencing Factors of National Intangible Cultural Heritage along the Grand Canal of China

Intangible cultural heritage (ICH) reflects a region’s history and culture, serving as a significant indicator of regional identity and cohesion. The Grand Canal Basin in China is rich in historical traditions, containing a rich array of ICH resources. Analyzing the spatiotemporal distribution characteristics and influencing factors of ICH within the Grand Canal Basin of China can provide a scientific basis for developing cultural industries and promoting sustainable regional economic growth. This study employed GIS-based spatial analysis methods, including kernel density estimation, the mean nearest neighbor index, and standard deviation ellipse, to investigate the spatiotemporal distribution of 504 national-level ICH items (including extensions) in the Grand Canal Basin of China. The results demonstrate the significant spatial clustering of ICH, with concentrations in high-density regions, particularly at the northern and southern ends of the canal. There is significant regional disparity in the distribution of ICH, with an uneven quantity and structure, predominantly featuring traditional skills and traditional drama categories. The average centroid shift of ICH exhibits a north-to-south oscillatory trajectory. However, overall, it demonstrates a southward-moving trend. This study also underscores the impacts of urbanization, population density, economic development, and transportation infrastructure on ICH distribution. Among these factors, urbanization exerts the strongest influence on the spatial distribution of ICH. The impact of the natural environment is relatively minor; however, it remains a significant element that cannot be overlooked during development. This research offers valuable data and insights for local governments and institutions to formulate evidence-based strategies for the protection and sustainable utilization of ICH resources, promoting sustainable cultural and economic development in the Grand Canal Basin.

Geospatial Data Enrichment through Address Geocoding: Challenges and Solutions

Abstract. Enriching geospatial data, particularly through address geocoding, is fundamental to many geospatial analytical solutions, facilitating resource allocation, accessibility assessment, and urban development planning. This paper explores the address geocoding approaches from traditional GIS-based methods to advanced data-driven solutions, emphasising their accuracy, efficiency, and complementarity. Geospatial data enrichment challenges are explored using the SemTUI framework and QGIS platform. SemTUI employs a data-driven approach that facilitates interactive semantic enrichment and address reconciliation. QGIS is utilised for address geocoding, using the MMQGIS plugin with two geocoding web services provided by OSM and Google. The comparison between SemTUI and QGIS workflows highlights their complementary strengths. SemTUI offers intuitive interfaces and an automated solution, while QGIS provides advanced geospatial visualisation and analysis capabilities. Practical applications in supply-demand analysis of social amenities and walkability index calculation demonstrate the significance of geocoding in urban planning. Further research efforts are focused on enhancing the integration between SemTUI and QGIS to improve the precision and performance of address geocoding and further spatial data analysis.

GIS-based method for assessing the viability of solar-powered irrigation

To attain food security, sub-Saharan Africa needs to increase its use of irrigation to improve agricultural productivity and resilience to climate change-induced droughts and erratic rain patterns. Stand-alone solar-powered irrigation systems are a promising technology to power irrigation where grid electrification is unavailable. However, these systems’ economic viability and sustainability are affected by spatially varying factors such as climate, water availability, and solar potential, making it challenging to plan their roll-out. This study addresses the planning challenge by developing a novel open-source reproducible geospatial methodology to determine irrigation water demand, peak power demand, life cycle cost, and locations where solar-powered irrigation systems would be cheaper than alternative off-grid irrigation technologies. The method considers spatial–temporal data for meteorological conditions, soil quality, water distance and depth, solar resource potential, technology efficiency and local equipment and fuel costs. Maize cultivation in Kenya is taken as a case study to demonstrate the method. We find the median peak irrigation water demand in Kenya to be 65,000 l/ha/day and the median peak power demand to be 2.6 kW/ha. The levelized cost of solar-powered irrigation systems ranges from US$ 0.09/kWh to US$ 0.25/kWh, making solar irrigation cheaper than diesel-powered irrigation in all Kenyan regions. The results from the method offer valuable insights to governments, farmers and investors on where water use regulations are required for sustainable water use, where subsidies and innovative financial models are needed for the affordability of solar irrigation and where alternative uses of energy from the solar systems beyond irrigation are possible.

Factors Influencing the Efficiency of Demand-Responsive Transport Services in Rural Areas: A GIS-Based Method for Optimising and Evaluating Potential Services

Factors Influencing the Efficiency of Demand-Responsive Transport Services in Rural Areas: A GIS-Based Method for Optimising and Evaluating Potential Services

Erratum for “A GIS-Based Method for Identifying Rainwater Harvesting: A Case Study of Sulaimanyah Governorate, Iraq”

Erratum for “A GIS-Based Method for Identifying Rainwater Harvesting: A Case Study of Sulaimanyah Governorate, Iraq”

Evaluation of GIS-based spatial interpolation methods for groundwater level: a case study of Türkiye

Evaluation of GIS-based spatial interpolation methods for groundwater level: a case study of Türkiye

Spatio-Temporal Analysis of Erosion Risk Assessment Using GIS-Based AHP Method: A Case Study of Doğancı Dam Watershed in Bursa (Türkiye)

Soil erosion, one of the most serious phenomena in watershed management, can be estimated based on various criteria. Land use change is one of the most important factors affecting the susceptibility of soil erosion. In this study, the effect of land use change on soil erosion risk in two plan periods (2005 and 2017) was investigated using Analytical Hierarchy Process (AHP) and Geographic Information Systems (GIS) for the forest planning units in the Doğancı Dam Watershed, located in Bursa, Türkiye. Eight criteria were evaluated including erosion-related slope, bedrock type, land use/land cover, precipitation, relative relief, aspect, drainage frequency, and density. According to the results, the most effective factor in soil erosion was slope (0.29), while bedrock type and land use/land cover ranked second with 0.19. It was found that full closure forests were characterized by high erosion resistance (0.3), while bare land was characterized as the most sensitive area to erosion (0.39). In terms of spatio-temporal changes in a 12-year period, the areas in the medium and high erosion risk decreased, while low and very low-risk areas increased. The ROC method showed a satisfactory accuracy of 72.8% and 80.2% for the 2005 and 2017 erosion risk maps, respectively.

Evaluation of Coal-Seam Roof-Water Richness Based on Improved Weight Method: A Case Study in the Dananhu No.7 Coal Mine, China

The safety of mines is a top priority in the mining industry, and a precise assessment of aquifer water levels is crucial for conducting a risk analysis of water-related disasters. Among them, the GIS-based water abundance index method is widely used in water-richness evaluation. However, the existing research lacks sufficient determination of evaluation indicator weights, specifically in the following aspects: (1) failure to consider the information differences between indicators and (2) inadequate differentiation of the relative importance of each indicator and their importance to the evaluation target. Taking the No.3 coal roof of Dananhu No.7 coal mine as the research object, six factors are selected as the main indexes for evaluating water richness. The weights were calculated using an improved entropy method and the scatter degree method, with the principle of information entropy used to reconcile the competitive and consistent relationship between the two evaluation methods. This approach resulted in the determination of combination weights for each influencing factor, highlighting the information differences between indicators and the importance of each indicator. Finally, the evaluation of aquifer water richness is partitioned by combining the GIS analysis function. The findings suggest that the Ⅰ division has low water richness, while the Ⅱ division is primarily medium-to-high water rich. The accuracy of the evaluation results exceeds 80%, providing valuable insights for hydrophobic programs for other coal-seam roofs.

Rainfall-Runoff Estimation in the North-Eastern Region of Bangladesh Using SCS-CN Method

Measuring discharge in a developing nation like Bangladesh is very important for flood prediction, land management, and sustainable development. Rainfall-induced runoff is a part of the cycle of hydrology and is required for efficient water resource planning. The most significant debatable procedure in hydrology is calculating and determining catchment surface runoff. The study aims to estimate runoff using the GIS-based Soil Conservation Service-Curve Number method (SCS – CN) method, where this hydrological model has a physical foundation and spatial distribution, and the curve number plays a key role in this model's runoff computation. The Hydrologic Soil Group (HSG) present in the study area and the land use pattern are used to find the Curve Number (CN). The calculated weighted CN for Antecedent Moisture Condition (AMC) I, II, and III for the study area was roughly 74.78, 87.12, and 94.06 respectively with the incorporation of Land use and land cover (LULC) and HSG. For total average rainfall of 35163.8mm, the SCS-CN approach determined the total average runoff 16077.55 mm for the period of 2009-2018. With a correlation coefficient of 0.966, the average rainfall and SCS-CN discharge have a significant linear relationship. The runoff regulates the amount of water that enters stream systems and returns extra precipitation to the ocean benefitting the hydrological cycle. With this runoff estimation, the quality and amount of water resources can be better understood, managed, and tracked. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 12(2), 2023, P 83-96

Assessment of methods for reconstructing Little Ice Age glacier surfaces on the examples of Novaya Zemlya and the Swiss Alps

Climate change since the end of the Little Ice Age (LIA) has driven observed glacier volume loss, significantly contributing to the rise of global sea level. The related calculation of volume change requires knowledge of glacier surfaces from at least two points in time, usually represented by two digital elevation models (DEMs). These are typically derived from photogrammetric techniques using stereo images, but such images do not go back to the LIA. Accordingly, several techniques have been developed to reconstruct LIA glacier surfaces from historic outlines and modern DEMs. Here we first evaluate various surface interpolation methods by replicating modern glacier surfaces from outline elevation points and analyse elevation differences and uncertainties. Secondly, we investigate different GIS-based methods for LIA surface reconstruction including a new method that is based on up-scaling of recent glacier-specific elevation change data and works also for ice caps without lateral moraines. The methods were tested on 90 glaciers (covering 643 km2) in southern Novaya Zemlya and 266 glaciers (524 km2) in the Bernese Alps of Switzerland. As in previous studies, we also found that the Natural Neighbor and Topo to Raster interpolation methods in ESRI's ArcGIS performed best for glacier surface reconstruction and that all methods are challenged by replicating the variable surface curvature of glaciers. The new reconstruction method shows the smallest mean difference to the reference dataset (RMSE of 26.7 vs. 39.8 m). The often neglected small surface lowering in the accumulation area can increase the derived glacier volume changes by 30–50 % and should thus be considered whenever possible. Applying the up-scaling method to both test regions revealed that elevation change rates over the last two decades (−0.8 m a−1 for Novaya Zemlya and -1.14 m a−1 for the Bernese Alps) were much higher than from 1850 until today (−0.13 m a−1 and -0.22 m a−1, respectively).

GIS-Based Methods for Identifying River Networks Types and Changing River Basins

GIS-Based Methods for Identifying River Networks Types and Changing River Basins

A combined Remote Sensing and GIS-based method for Local Climate Zone mapping using PRISMA and Sentinel-2 imagery

In the last decade, several methods have been developed for Local Climate Zone (LCZ) mapping, encompassing Remote Sensing and Geographic Information Systems (GIS) −based procedures. Combined approaches have also been proposed to compensate for intrinsic limitations that characterized their separate application. Recent work has disclosed the potential of hyperspectral satellite imagery for improving LCZ identification. However, the use of hyperspectral data for LCZ mapping is yet to be fully unfolded. A combined Remote Sensing and GIS-based method for LCZ mapping is proposed to exploit the integration of hyperspectral PRISMA and multispectral Sentinel-2 images with ancillary urban canopy parameter layers. Random Forest algorithm is applied to the feature sets to obtain the LCZ classification. The method is tested on the Metropolitan City of Milan (Italy), for the period from February to August 2023. A spectral separability analysis is carried out to investigate the improvement in LCZ identification using PRISMA in comparison to Sentinel-2 data, as well as improvements in LCZ spectral separability on PRISMA pan-sharpened images. The resulting maps’ quality is evaluated by extracting accuracy metrics and performing inter-comparisons with maps computed from the LCZ Generator benchmark tool. Inter-comparisons yield promising results with a mean Overall Accuracy increase of 16% using PRISMA for each LCZ class. Furthermore, we find that PRISMA improves the detection of LCZs compared to Sentinel-2, with a mean Overall Accuracy increase of 5%, in line with the higher spectral separability of PRISMA spectral signatures computed on the training samples.

Sustainability indicator for evaluating the ATES system in Halabja-Khurmal sub-basin NE-Iraq using GIS-based MCDA method

Thermal energy is utilized as an environmentally friendly energy source for seasonal heat and cold storage on a global scale. Specifically, the aquifer thermal energy storage system is highlighted for being cost-effective in cooling and heating applications. The study assesses the sustainability of the aquifer thermal energy storage in the Halabja-Khurmal sub-basin by evaluating six critical criteria: groundwater transmissivity, groundwater temperature, groundwater discharge, groundwater chemistry, population density, and per capita GDP. A multi-criteria decision analysis judgment is applied to analyze all criteria, resulting in a consistency ratio of 0.3% in the analytical hierarchy process. Consequently, the sustainability map for Aquifer Thermal Energy Storage in the Halabja-Khurmal sub-basin for heating reveals that 26.45% of the area is strongly sustainable located in the north and southwestern part of the sub-basin, 73.53% is moderate in the east, central, southeast, and southern regions, 0.02% is weakly sustainable as a tiny area in the southwestern. On the other hand, the sustainability map for Aquifer Thermal Energy Storage in the Halabja-Khurmal sub-basin for cooling reveals that 19% of the area is strongly sustainable located in the north, and southwestern parts of the sub-basin, 78% is moderate in the northeast, east, southeast, west, central, and southern regions, 3% is weakly sustainable as spots in the west and southwestern areas.

Redefining Neighborhood Boundaries Using Activity Spaces: Bringing Together Soft Spaces and Spatial Analysis to Further the Discussion on Planning in Functional Spaces

Neighborhoods are typically conceptualised as static administrative units with clearly defined boundaries. However, residents’ everyday mobility forms activity spaces which are variable in both extent and fabric. This study introduces a novel aggregate model of individualized activity spaces based on Public Participation geographic information system (PPGIS) data collected in Espoo (Finland) to capture the variable and fuzzy character of the spaces people frequent in their everyday lives. Building on the theoretical concept of soft spaces, we propose a GIS-based method for identifying functional neighborhoods which could be useful in planning practice with a view to knowledge, actor involvement, and planning policies.

Integration of GIS and Water-Quality Index for Preliminary Assessment of Groundwater Suitability for Human Consumption and Irrigation in Semi-Arid Region

The Setifian high-plains region, Northeast of Algeria, grapples with challenges in water resource management. As the water demand intensifies across a diverse range of sectors, assessing groundwater quality becomes indispensable. This article responds to the critical need for a thorough assessment of groundwater quality in the Wadi Boussellam sub-watershed. Employing a GIS-based method, we evaluate groundwater geochemistry by estimating the Water Quality Index (WQI), offering a comprehensive overview of water consumption. The analysis of groundwater samples reveals distinct facies, including calcic bicarbonate, calcic chloride, calcic sulfate, and magnesium sulfate, contributing to an enhanced understanding of the hydrochemical composition in the Setif region. Hydrochemical indices, specifically the WQI, Sodium Adsorption Ratio (SAR), and Na% are applied to assess groundwater suitability for various applications. The results indicate that most crops are generally suitable for irrigation, though they advise exercising caution with regard to human consumption. This study underscores the significance of regular monitoring to avert groundwater contamination and ensure sustainable use in the Setif region, providing insights that emphasize the ongoing necessity for efforts in water resource management and the preservation of this vital resource’s quality.

Assessing landslide damming susceptibility in Central Asia

Abstract. Central Asia regions are characterized by active tectonics, high mountain chains with extreme topography with glaciers, and strong seasonal rainfall events. These key predisposing factors make large landslides a serious natural threat in the area, causing several casualties every year. The mountain crests are divided by wide lenticular or narrow, linear intermountain tectonic depressions, which are incised by many of the most important Central Asia rivers and are also subject to major seasonal river flood hazard. This multi-hazard combination is a source of potential damming scenarios, which can bring cascading effects with devastating consequences for the surrounding settlements and population. Different hazards can only be managed with a multi-hazard approach coherent within the different countries, as suggested by the requirements of the Sendai Framework for Disaster Risk Reduction. This work was carried out within the framework of the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project as part of a multi-hazard approach with the aim of providing a damming susceptibility analysis at a regional scale for Central Asia. To achieve this, a semi-automated GIS-based mapping method, centered on a bivariate correlation of morphometric parameters defined by a morphological index, originally designed to assess the damming susceptibility at basin/regional scale, was modified to be adopted nationwide and applied to spatially assess the obstruction of the river network in Central Asia for mapped and newly formed landslides. The proposed methodology represents an improvement to the previously designed methodology, requiring a smaller amount of data, bringing new preliminary information on damming hazard management and risk reduction, and identifying the most critical area within the Central Asia regions.

A Research on Determining the Importance Levels of Criteria Effective in Forest Road Network Planning through GIS-Based Methods

This study investigated the importance levels of criteria effective in forest road network planning using Geopraphic Information System (GIS)- based Multi- Criteria Evaluation (MCE) method. It is crucial to determine the criteria to be considered in forest road construction and planning for a standardized application nationwide. The research was conducted within the boundaries of the Yaylacık Forest Management Directorate (YFMD) under the Tokat Forest Management. Firstly, the existing road network was identified in the research. After the identification of the existing road network, a GIS database was created. In this study, criteria to be used, in Forest Road Network Planning (terrain slope, aspect, road density, distance to road, land use, distance to main stream) were determined. Each criterion was classified and scored internally. Information from road and road network planning studies and previous works were utilized in determining the criteria to be used in Forest Road Network Planning. Five different degrees and suitability values are defined for the determined criteria. In this context, it was created to reach 5 fundamental road network planning functions to determine their positional statuses as Absence (Ab), Very Suitable Areas for road planning (VS), Suitable Areas for road planning (S), Less Suitable Areas for road planning (LS), and Very Less Suitable Areas for road planning (VLS). As a result, Terrain Slope and Road Density were determined as the most effective criteria in Road Network Planning, while Distance to Main Stream was identified as the least effective criterion. As a result of the study, a flow chart was created to determine the criteria and impact values that are effective in forest road network planning in order to ensure integrity and convenience in application throughout the country.

GIS-based prediction method of shallow landslides induced by heavy rainfall in large mountainous areas

GIS-based prediction method of shallow landslides induced by heavy rainfall in large mountainous areas