GIS-based Multi-criteria Decision Analysis Research Articles

Mapping Vulnerability to Potential Crisis Events in Surabaya City: A GIS-Based Approach

Background This study aims to develop a vulnerability map for Surabaya using GIS-based Multi-Criteria Decision Analysis (MCDA) to assess the city’s vulnerability to COVID-19. Methods Six key factors influencing vulnerability were identified and their relative importance determined through the Analytic Hierarchy Process (AHP) pairwise comparison matrix. GIS was utilized to classify Surabaya’s vulnerability into five levels: very low, low, medium, high, and very high. Results The resulting vulnerability map provides essential insights for decision-makers, healthcare professionals, and disaster management teams. It enables strategic resource allocation, targeted interventions, and formulation of comprehensive response strategies tailored to specific needs of vulnerable districts. Conclusions Through these measures, Surabaya can enhance its resilience and preparedness, ensuring the well-being of its residents in the face of potential emergency outbreaks.

Assessment of the geothermal potential zone of India utilizing GIS-based multi-criteria decision analysis technique

India, with 80 % energy demand reliant on fossil fuels, is the world's third-largest greenhouse gas emitter, necessitating a shift from fossil fuels to renewable energy. While solar and wind production has grown, geothermal energy remains untapped despite enormous prospects in the country. In this regard, India's first regional-scale geothermal potential (GP) map has been prepared using a GIS based on a multi-criteria decision analysis technique. Five thematic layers (geology, fault, heat flow, thermal spring, and earthquake epicenter) have been used to calculate GP index, which is divided into high, moderate, and low categories. The result shows that most geothermal drilling sites are distributed in the high GP category zone, showing high efficacy. Further, a joint study of the geothermal surface and reservoir temperature with the present study shows that the northern and western parts of India have significant potential for geothermal exploration. Our result also reveals that the projected CO2 emissions are approximately 2.6 gigatons (which is lower than other energy sources) for an output of 10 GW using geothermal energy in the next 75 years. This study can enhance geothermal prospect identification, cutting exploration costs, and site selection, and contributing to multiple UN Sustainable Development Goals.

GIS-Based Multi-criteria Decision Analysis for the Optimal Location of Public Facility in Batna City, Algeria

GIS-Based Multi-criteria Decision Analysis for the Optimal Location of Public Facility in Batna City, Algeria

Delineation of Groundwater Potential Zones for Sustainable Development and Planning using AHP and GIS Techniques in the Coal Mining Province of Mahan River Catchment Area

The present research aims to address the drinking water crisis in the Mahan River catchment area resulting from the disruption of groundwater availability due to extensive coal mining. The study uses GIS-based Multi-Criteria Decision Analysis (MCDA) to map the groundwater potential of the area by analysing several factors that affect groundwater availability, including rainfall, water depth, geomorphology, geology, soil, land-cover/land-use, and topographic characteristics derived from DEM. The groundwater potential map created using the MCDA technique classified the area into low, moderate, and high groundwater potential zones. The map was validated and verified using water table depth and electrical conductivity values available in the region, indicating that it can be used to identify groundwater recharging sites. The study’s results show that about 30% of the area has high groundwater potential, and more than 45% of the area has moderate groundwater potential. The information derived from the study can be used for sustainable management and proper planning of groundwater resources in the Mahan River catchment area. Overall, the study presents a useful approach to address the groundwater depletion problem resulting from coal mining activities in the Mahan River catchment area.

How to delineate urban gravitational zones? GIS-based multicriteria decision analysis and Huff’s model in urban hierarchy modeling

Urban gravitational zones (UGZ) are related to cities' functions and population size. In strategic regional territorial planning adequate tools and detailed data are rarely used. This issue is not foreign to Croatia and other countries. How should the UGZ be accurately delineated for each city? A combination of Huff's model and GIS-based multicriteria decision analysis (GIS-MCDA) was used to delineate UGZ. In total, 95 criteria grouped into ten functions were used. The research resulted in a new methodological framework for deriving the urban hierarchy model, a tool that allows automation and simplification of the GIS-MCDA, and an urban hierarchy model of 20 major cities in Croatia.

Landslide susceptibility assessment using GIS-based multicriteria decision analysis (MCDA) along a part of National Highway-1, Kashmir- Himalayas, India

Landslide susceptibility assessment using GIS-based multicriteria decision analysis (MCDA) along a part of National Highway-1, Kashmir- Himalayas, India

Evaluating lake water quality with a GIS-based MCDA integrated approach: a case in Konya/Karapınar

Considering water quality is an essential requirement in terms of environmental planning and management. To protect and manage water resources effectively, it is necessary to develop an analytical decision-support system. In this study, a systematic approach was suggested to evaluate the lake water quality. The methodology includes the prediction of the values in different locations of the lakes from experimental data through inverse distance weighting (IDW) method, creation of maps by using Geographic Information System (GIS) integrated with analytic hierarchy process (AHP) from multi-criteria decision analysis (MCDA), reclassification into five class, combining the time-related spatial data into a single map to predict the whole lake water quality from the data of sampling points, and finally overlapping the final maps with topography/geology and land use. The proposed approach was verified and presented as case study for Meke and Acigol Lakes in Konya/Turkey which were affected by human and natural factors although they have ecological, hydromorphological, and socio-economic importance. In the proposed approach, categorizing water quality parameters as “hardness and minerals,” “substrates and nutrients,” “solids content,” “metals,” and “oil-grease” groups was helpful for AHP with the determined group weights of 0.484, 0.310, 0.029, and 0.046, respectively. Assigning weights within each group and then assigning weights between groups resulted in creating accurate final map. The proposed approach is flexible and applicable to any lake water quality data; even with a limited number of data, the whole lake water quality maps could be created for assessment.

Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS

Floods are a widespread natural disaster with substantial economic implications and far-reaching consequences. In Northern Pakistan, the Hunza-Nagar valley faces vulnerability to floods, posing significant challenges to its sustainable development. This study aimed to evaluate flood risk in the region by employing a GIS-based Multi-Criteria Decision Analysis (MCDA) approach and big climate data records. By using a comprehensive flood risk assessment model, a flood hazard map was developed by considering nine influential factors: rainfall, regional temperature variation, distance to the river, elevation, slope, Normalized difference vegetation index (NDVI), Topographic wetness index (TWI), land use/land cover (LULC), curvature, and soil type. The analytical hierarchy process (AHP) analysis assigned weights to each factor and integrated with geospatial data using a GIS to generate flood risk maps, classifying hazard levels into five categories. The study assigned higher importance to rainfall, distance to the river, elevation, and slope compared to NDVI, TWI, LULC, curvature, and soil type. The weighted overlay flood risk map obtained from the reclassified maps of nine influencing factors identified 6% of the total area as very high, 36% as high, 41% as moderate, 16% as low, and 1% as very low flood risk. The accuracy of the flood risk model was demonstrated through the Receiver Operating Characteristics-Area Under the Curve (ROC-AUC) analysis, yielding a commendable prediction accuracy of 0.773. This MCDA approach offers an efficient and direct means of flood risk modeling, utilizing fundamental GIS data. The model serves as a valuable tool for decision-makers, enhancing flood risk awareness and providing vital insights for disaster management authorities in the Hunza-Nagar Valley. As future developments unfold, this study remains an indispensable resource for disaster preparedness and management in the Hunza-Nagar Valley region.

Groundwater delineation for sustainable improvement and development aided by GIS, AHP, and MIF techniques

Exploration of groundwater is an integral part of viable resource growth for society, economy, and irrigation. However, uncontrolled utilization is mainly reported in urban and industries due to the increasing demand for water in semi-arid and arid regions of the world. In the background, groundwater demarcation for potential areas is vital in meeting necessary demand. The current study applied an integrated method comprising the analytical hierarchy process (AHP), multiple influence factors (MIF), combined with a linear regression curve and observatory well data for groundwater prospects mapping. Thematic maps such as flow direction, flow accumulation, elevation map, land use land cover, slope, soil texture, hill shade, geomorphology, normalized vegetation index, and groundwater depth map were generated utilizing remote sensing techniques. The relative weight of each parameter was estimated and then assigned to major and minor parameters. Potential zones for groundwater were classified into five classes, namely very good, good, moderate, poor, and very poor, based on AHP and MIF methods. A spatially explicit sensitivity and uncertainty analysis method to a GIS-based multi-criteria groundwater potential zone model is presented in this research. The study addressed a flaw in the way groundwater potential mapping results are typically presented in GIS-based multi-criteria decision analysis studies, where discrete class outputs are used without any assessment of their certainty with respect to variations in criteria weighting, which is one of the main contributors to output uncertainty. The study region is categorized based on inferred results as very poor, poor, marginal, and very good in potential ground quality 3.04 km2 is considered extremely poor, 3.33 km2 is considered poor, 64.42 km2 is considered very good, and 85.84 km2 is considered marginal zones, which shows reliable and potential implementation. The outcomes of AHP and MIF were validated by linear regression curve and actual water table in a study area. The study results help to formulate the potential demarcation of groundwater zones for future sustainable planning and development of groundwater sources. This study may be helpful to provide a cost-effective solution to water resources crises. The current study finding may be helpful for decision-makers and administrative professionals for sustainable management of groundwater resources for present and future demands.

SPATIAL CRITERIA FOR INDUSTRIAL AREA: SUSTAINABLE DEVELOPMENT STRATEGY IN SANGIRAN CULTURAL HERITAGE ZONE, GONDANGREJO DISTRICT

<span>Gondangrejo District is a suburb (peri urban) of Surakarta City with significant industrial growth in Karanganyar Regency. The driving factor of the development of the Gondangrejo District is the relocation of urban activities in Surakarta City. Gondangrejo District is an area of deconcentration of industrial activities because of its location directly adjacent to Surakarta City. A comprehensive site selection analysis is essential for industrial siting that supports sustainable builders. We select the optimal site for the industrial area by considering various criteria and inhibiting factors using GIS-based MCDA. Most suitable for industrial sites with GIS and AHP to build industries in The Gondangrejo District. This study aims to determine the most optimal industrial area by considering various appropriate criteria using multi-criteria decision analysis (MCDA) and geographic information system (GIS) methods. Based on the criteria used, namely proximity to roads, distance from rivers, distance from settlements, physiology, and population density with the same weight of 20%, a suitable location for the industrial area with a linear pattern or extending from east to west in the Gondangrejo District. Based on the same criteria with different weights from the results of the AHP analysis, suitable locations for industrial sites are Dayu Village, Rejosari Village, and Wonosari Village, which form a centering pattern. The study results found that the optimal industrial areas in Gondangrejo District are Dayu Village, Rejosari, and Wonosari. The results of the suitability of this industrial area can be used by decision-makers in the development planning of the Gondangrejo District.</span>

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

Integrating multi-criteria decision analysis (MCDA) with kriging and entropy methods for optimising streamflow measurement in a scantly monitored river basin

ABSTRACT Streamflow data is one of the most important inputs for the management of water resources in river basins. In this study, a GIS-based multi-criteria decision analysis (MCDA) was integrated with kriging and entropy methods for optimising a streamflow monitoring network in the upper Tekeze River basin, north-western Ethiopia. An initial evaluation based on the WMO (2008) guideline showed that the density of existing streamflow monitoring network for the upper Tekeze River basin was inadequate. Hence, 41 new streamflow monitoring stations were needed. The most important criteria for identifying suitable streamflow monitoring sites in the upper Tekeze River basin were stream order, accessibility (distance to roads), slope gradient, land use/cover and soil texture. The required number of new streamflow monitoring stations for the upper Tekeze River basin was reduced from 41 to 33 after an optimisation using ordinary kriging and entropy. The optimal number of monitoring stations for the upper Tekeze River basin including the existing ones was therefore 47. An integrated application of MCDA, kriging and entropy methods aids to optimise the location and number of streamflow monitoring stations in a catchment. The use of optimisation techniques for designing streamflow monitoring network is essential for collecting adequate streamflow data in scantly monitored basins.

Climate change-derived environmental and physical factors influencing the socioeconomic development in the Himalayan region

Spatio-temporal fluctuation of climatic variables with the terrain characteristics and their inter-relationship is a priority for predicting flash-flood-induced landslide hazards over the fragile Himalayas. The present study addressed this anxiety by assimilating satellite data products and auxiliary datasets in the Bhagirathi River basin of the Indian Himalayas. Snow Covered Area (SCA) is a critical indicator of the ecosystem that influenced the flash flood along different terrain features such as Altitude, Hill-Gradient, and Aspect. GIS-based multi-criteria decision analysis (GIS-MCDA) technique is used to analyze the possible landslide zones and flood extent along the river basin, and MODIS Terra (MOD10A2) data products derived annual SCA is 4278 km2 for the year 2021, the analysis of geospatial maps at 25° intervals of Altitude, hill-gradient, and Aspect. The SCA distribution reveals that apart from the Altitude, the Aspect of the hill gradient significantly impacts snow accumulation. Hill-Gradient, ranging from 13.06 to 19.52, occupies 24.7% of the total area, and 45.3 to 51.83 are found without snow. The highest variation of SCA is along the Western direction (9.19%), followed by North-East (8.79%), while the least (3.78%) variance is in the Southwest direction. Additionally, it was found that many bridges, roads, and other properties are under threat in this study area, even with a moderate flash flood. Findings from this study provide the spatiotemporal status of SCA in various geological stress conditions during the last decades and probable landslide zones. This will be a preliminary pathway to policymakers in rehabilitation and early evacuation of human lives due to flash flood occurrence.

Suitability Analysis for Waste Disposal Site Using GIS Based Multi-Criteria Decision Analysis: A Case Study of Jhapa District, Nepal

Environmental degradation resulting from rapid urbanization, industrialization, and overpopulation has become a critical global issue, primarily due to the generation of vast amounts of solid waste. Effective solid waste management and proper disposal arrangements are imperative to mitigate the adverse impacts on the environment. This research article focuses on identifying an appropriate waste disposal site for efficient waste management and dumping. Jhapa district in Nepal is chosen as the study area due to its diverse settlement zones, including industrial and commercial regions. To achieve this goal, Geographic Information based Multi-Criteria Decision Analysis (MCDA) method is used. The outcome of this project is a suitability model that categorizes different areas as least suitable, suitable, more suitable, and most suitable for establishing a waste disposal site. By considering multiple criteria, including environmental, health, residential and political factors, and the model provides a comprehensive assessment of potential sites. This research contributes to the field of waste management and environmental sustainability by offering a practical approach to decision-making in waste disposal site selection, promoting a healthier and cleaner environment for the residents of Jhapa district and beyond.

Evaluation of Flood Risk Map Development through GIS-Based Multi-Criteria Decision Analysis in Maran District, Pahang - Malaysia

Evaluation of Flood Risk Map Development through GIS-Based Multi-Criteria Decision Analysis in Maran District, Pahang - Malaysia

Investigating the Relationship between Surface Water Pollution and Onsite Wastewater Treatment Systems.

Onsite wastewater treatment systems (OWTSs) are important nonpoint sources (NPSs) of pollution to consider in watershed management. However, limited OWTS data availability makes it challenging to account for them as an NPS of water pollution. In this study, we succeeded in obtaining OWTS permits and integrated them with environmental data to model the pollution potential from OWTSs at the watershed scale using GIS-based multicriteria decision analysis. Then, in situ water quality parameters─Escherichia coli (E. coli), total nitrogen, total phosphorus, temperature, and pH─were measured along the main tributary at base-flow conditions. Three general linear models were developed to relate E. coli to water quality parameters and OWTS pollution indicators. It was found that the model with the OWTS pollution potential had the lowest corrected Akaike information criterion (AICc) value (35.01) compared to the models that included classified OWTS pollution potential input criteria (AICc = 36.76) and land cover (AICc = 36.74). These results demonstrate that OWTSs are a significant contributor to surface water pollution, and future efforts should be made to improve access to OWTS data (i.e., location and age) to account for these systems as an NPS of water pollution.

Optimal Urban Waste Dumping Site Selection in Kalutara DS Division of Sri Lanka using GIS-based Multi-Criteria Decision Analysis

Improper waste dumping is an emerging issue in Sri Lanka because of the unsystematic urbanisation process. The main problem of the study is determining sites that are ideal for waste dumping. The use of improper waste disposal methods adversely affects the environment and human lifestyle. This study focuses on integrating a structured approach under multi-criteria decision analysis for waste dumping. The present study has been carried out in Kalutara DS Division, integrating Analytical Hierarchy Process (AHP)-based Multi-Criteria Decision Analysis (MCDA) and geospatial techniques to find suitable waste dumping sites. Ten different types of criteria were selected for the study in vector and raster format, namely, land use, population density, schools, religious places, government offices, coastal areas, hospitals, roads, railways, and environmentally sensitive areas. After finalising the criteria, the GIS-based AHP-MCDA methodology was used for weighting, standardisation, and normalisation by obtaining the opinions of experts and conducting literature surveys. The results of the study are sorted into not-suitable, less-suitable, and suitable dumping sites. Classified suitability maps revealed that 36.94% are not suitable, 53.06% are less suitable, and completely 9.9% are suitable for urban waste dumping sites. The spatial variance of suitable and not suitable waste disposal sites was found in the north, north-eastern, and western and central parts of the study area. Hence, based on the results indicated using such methods, it will be an effective manual for engineers, regional planners, and decision-makers to implement sustainable waste management in the study area in the future.

Effective management of the watershed in response to historical climate change using a GIS-based multi-criteria decision analysis (MCDA)

Abstract Watershed management is necessary to conserve water resources because the watershed hydrological processes are more affected by climate and land use change, resulting in the problems of droughts, floods, soil erosion, etc. This study determined suitable alternatives that can ensure viable strategies for tackling the climate change impacts at the Soan River Basin (SRB). A framework was applied to assess the impacts of climate change and land use/cover change (LUCC) using the Soil and Water Assessment Tool (SWAT). A multi-criteria decision analysis (MCDA) was used to prioritize watershed management alternatives by comparing watershed management criteria and alternatives using the analytic hierarchy process (AHP). Framework findings showed a 69 and 31% decline in runoff, and a 58 and 42% increment in evapotranspiration (ET) due to climate change and LUCC, respectively. The top prioritized suitable alternatives were water harvesting structure (WHS) and vegetative cover (VC). Suitability analysis showed that 63.61 and 16.56% area of the SRB were moderately to highly suitable for WHS, respectively. For soil and water management, VC has been found suitable to moderately suitable for 72.68 and 26.75% of the basin area, respectively. So, there should be adoption of such measures which will assist in configuring the climate adaptive strategies.

GIS-based multi-criteria decision analysis for mapping flood-prone areas in Dehradun city, India

GIS-based multi-criteria decision analysis for mapping flood-prone areas in Dehradun city, India

Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria decision analysis method in Fetam-Yisir catchment, Blue Nile Basin, Ethiopia

Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria decision analysis method in Fetam-Yisir catchment, Blue Nile Basin, Ethiopia