GIS-based Multi-criteria Analysis Research Articles

Mapping cellular coverage suitability: a GIS-Based approach to identifying poor service areas

Cellular coverage is a critical component of modern telecommunications, providing essential services for communication, commerce, and emergency response. Despite its importance, many regions, particularly those with challenging terrain or low population density, experience inadequate cellular service. This study focuses on the commune of Laghouat, Algeria, employing a GIS-based Multi-Criteria Analysis (MCA) to assess cellular coverage suitability. Using ArcGIS Pro, four key factors were integrated: cell tower locations, terrain elevation, population distribution, and restricted areas. The methodology includes performing a Viewshed analysis to identify dead zones, converting population data into raster format to map demand, and digitizing restricted areas where telecommunication infrastructure development is prohibited. All factors were standardized to a common scale to ensure comparability and a weighted overlay analysis was conducted to generate a comprehensive suitability map. The map highlights areas of poor cellular coverage, guiding the placement of new infrastructure. Additionally, the research considers regulatory restrictions on land use, ensuring compliance with governmental policies. The resulting suitability map provides valuable insights for telecommunications providers and policymakers, enabling them to target underserved regions for infrastructure improvements while adhering to legal constraints. This study offers a robust, scalable framework for identifying and addressing cellular coverage gaps, applicable to other regions with similar geographic and demographic challenges.

Identification of optimal locations for green space initiatives through GIS-based multi-criteria analysis and the analytical hierarchy process

Urban green spaces play a vital role in enhancing the well-being of communities and mitigating environmental challenges such as air pollution and global warming. Despite their importance, effective models to allocate these green spaces are often overlooked, particularly in developing countries. This study utilises GIS-based Multi-Criteria Analysis and the Analytical Hierarchy Process to recommend optimal locations for green space interventions in Lilongwe City, Malawi, based on nine factors: population density, proximity to roads, slope, Digital Elevation Model (DEM), Normalized Difference Vegetative Index (NDVI), land cover, existing green space, proximity to water bodies, and nitrogen dioxide concentration. The results show that 0.57% (23,776 hectares) of Lilongwe city is highly suitable while 14.50% (604,596 hectares) is unsuitable for green space interventions, where population density was the most determining factor. The suitability varied across the city, with highly suitable areas predominantly located in the southern part. The study highlights the importance of informed decision-making in urban green space planning, setting a standard for equitable access to green spaces and sustainable urban development.

Soil Erosion Susceptibility Prediction Using GIS-Based Multicriteria Analysis and Worldview-3 Satellite Images

Soil erosion has been identified as a major threat to existing soil deposits, which negatively affects ecosystem sustainability, agricultural production and clean water supply. This study covered the eastern part of Kaštela Bay with the aim of developing a model of susceptibility to soil erosion by applying the GIS-based multicriteria analysis, based on nine determinant criteria categorized by the Jenks method in five classes. The largest representation of soil erosion susceptibility was detected on the slopes of the Kozjak and Mosor massifs. According to the calculated weighting coefficients using the analytic hierarchy process (AHP), the slope was the most impactful criterion with 29.9 % importance. It was followed by hydrological criteria of topographic wetness index, standardized precipitation index and LS-factor, with 13.1 % importance each. After the development of the model, zones of very high and high susceptibility to soil erosion were delineated, with a combined coverage of 33.34 % of the study area. These areas were identified as a potential threat from the future occurrence of negative effects of soil erosion, which should be addressed in the future by land policy managers and government managers.

Multi-criteria site selection for wastewater treatment plant in Bent Saidane, Tunisia

Optimal site selection for the establishment of a municipal waste-water-treatment plant (WWTP) is an amazingly complex task that involves several factors such as regulations, as well as environmental, economic and social considerations. This paper presents the criteria and applied methods (geographic information system (GIS)/fuzzy analytical hierarchy process (AHP)) used in the screening of potential sites for the WWTP of the Bent Saidane rural locality (northern Tunisia). For this reason, nine factors accompanied by three sets of site selection criteria were used. GIS-based multi-criteria analysis techniques based on the standardised fuzzy logic concept and weighted overlay were applied for generation of all maps in the Universal Transverse Mercator coordinate system. Multiscale evaluations based on the weighted linear combination method were also assessed. The study indicated that 0.14 and 0.11% of the total area of the Bent Saidane locality were found to be highly suitable and very highly suitable, respectively. According to these results, the GIS followed by the fuzzy AHP method could pinpoint the optimal sites selected as the most suitable, due to their minimum impact on the environment, as well as on public health, for the construction of a future WWTP in the Bent Saidane rural area.

Spatial Evaluation of Waste Disposal Site Selection Using GIS-Based Multi-Criteria Analysis: A Case Study of Dera Ghazi Khan District, Pakistan

The rapid population growth and rising per capita incomes have caused the city to generate massive amounts of municipal waste, indicating a serious environmental threat. Solid waste disposal has become a crucial problem for several municipalities. The selection of suitable waste disposal sites is a crucial problem in the urban areas of developing countries like Pakistan due to unsatisfactory urban planning and management to decrease human being’s health risks. Particularly, Dera Ghazi (D.G.) Khan district is facing the issue of identifying suitable sites for solid waste disposal. This research aims to select appropriate potential sites suitable for solid waste disposal purposes in the D.G. Khan. Primary datasets used for this study are Landsat-8 satellite imagery, digital elevation model (DEM) with 30-meter resolution for slope extraction. Other criteria included roads, railroads, and rivers digitized using the topographical map of the study area. The maps are prepared to incorporate overlay and suitability analysis using Geographic Information System (GIS), Remote Sensing techniques, and Analytical Hierarchy Process (AHP), a multi-criteria analysis. The final suitability map of study area is prepared using a GIS software suite and categorized as highly, moderately, least, and unsuitable regions, of which 3% is entirely unsuitable area, 70% less suitable, 26.16% moderately suitable, and 0.84% highly suitable area. The suggested disposal sites have been carefully selected to assist policymakers in determining the most sensitive areas and resolving waste management issues with the slightest contamination of water bodies and the environment.

GIS-based multi-criteria analysis for solar, wind, and biomass energy potential: A case study of Iraq with implications for climate goals

The study utilizes a GIS-Based Multi-Criteria Analysis to evaluate the viability of solar, wind, and biomass energy in Iraq, focusing on enhancing the nation's energy independence and meeting international climate objectives. Detailed spatial analysis revealed specific zones suited for the efficient installation of energy power plants. Zones with an energy surplus factor of less than 0.2 are deemed not viable for development, whereas regions with factors less than 0.4 are ideal for harnessing solar, wind, and biomass resources. Furthermore, zones with surplus factors greater than 0.6 are highly recommended for energy projects. Notably, the results show that strategic development of these zones can cater to between 45 % and 68 % of the country total energy demand, potentially reducing the CO2 footprint by 0.5. Moreover, with an increase in the construction threshold, the CO2 reduction potential has shown a decrease to 1.29E+08 tones, particularly evident in areas with rigorous construction standards. A plateau in reduction figures is observed once the construction threshold surpasses 3.5, stabilizing between 2.5E+07 tones. As the threshold exceeds 5, a further stabilization is noted, consistently around 2.17E+07 tones, persisting even when the threshold approaches 8. The outcomes underscores the critical role of strategic zoning in maximizing renewable energy potential, highlighting pathways for the country to achieve energy self-sufficiency and make significant strides in climate goals.

Mapping areas suitable for agriculture and their accessibility: The case of the centre region of Cameroon

Given the pressure on land in the Central Region due to economic development and the search for opportunities, the best land for agriculture needs to be identified, so as to preserve it from urbanization, the expansion of mining areas, infrastructure and other occupations. It is in this context that the issue of mapping to identify agricultural zones and assess their accessibility was raised. This is an opportune moment to feed reflections on planning, agricultural production and natural resource management in the Center Region of Cameroon. GIS-based multi-criteria spatial analysis of data on land use, hydrographic network, slopes, soils and their suitability for cultivation provided precise, geolocalized information on land potentially suitable for agriculture in general. Following the analyses, we were able to establish and highlight the areas suitable for agriculture and accessible, which amounted to 8%, or 5662.42 km2 for high-potential and accessible areas. This was followed by 56%, or 37144.95 km2 for medium-potential and accessible zones, and finally 6%, or 4238.93 km2 for low-potential and accessible zones. Once the accessible areas had been removed, 5% or 3028.27 km2 of high-potential inaccessible areas remained, 19%, that is 14639.46 km2 of medium-potential inaccessible areas and 2% that is 967.12km2 of low-potential inaccessible areas.

Wind farm site selection using GIS-based multicriteria analysis with Life cycle assessment integration

The sustainability of wind power plants depends on the selection of suitable installation locations, which should consider not only economic and technical factors including manufacturing and raw materials, but also issues pertaining to the environment. In the present study, a novel methodology is proposed to determine the suitable locations for wind turbine farms by analyzing from the environmental perspective. In the methodology, the life cycle assessment (LCA) of wind turbines is incorporated into the decision process. The criteria are ranked using analytical hierarchy process (AHP). The study area is chosen as the western region of Türkiye. The obtained suitability map reveals that wind speed is not the sole criterion for selecting a site for wind turbine farms; other factors, such as bird migration paths, distance from urban areas and land use, are also crucial. The results also reveal that constructing wind power plants in the vicinity of İzmir, Çanakkale, Istanbul, and Balıkesir in Türkiye can lead to a reduction in emissions. İzmir and its surrounding area show the best environmental performance with the lowest CO2 per kilowatt-hour (7.14 g CO2 eq/kWh), to install a wind turbine due to its proximity to the harbor and steel factory across the study area. Çanakkale and the northwest region of Türkiye, despite having high wind speeds, are less environmentally favorable than İzmir, Balıkesir, and Istanbul. The findings of LCA reveal that the nacelle and rotor components of the wind turbine contribute significantly (43–97%) to the environmental impact categories studied, while the tower component (0–36%) also has an impact.

Soybean (Glycine max) Cropland Suitability Analysis in Subtropical Desert Climate through GIS-Based Multicriteria Analysis and Sentinel-2 Multispectral Imaging

Soybean (Glycine max) is a protein-rich oilseed crop that is extensively used for cooking oil and poultry feed and faces significant challenges due to adverse global climatic conditions aggravated by the ongoing climate crisis. In response to this critical issue, this study was initiated to assess suitable zones for soybean cultivation, aiming to facilitate informed land use decisions within the semi-arid terrestrial ecosystem. Through the utilization of geostatistical interpolation, data layers encompassing soil, irrigation water, land use and land cover, topographic features, and climate information were generated and overlaid based on criterion weightage derived from the Analytic Hierarchy Process. The accuracy of land use and land cover was rigorously evaluated, yielding a 70% overall accuracy and a Kappa (K) value of 0.61, signifying an acceptable level of precision. Validation through the Receiver Operating Characteristic curve for soybean crop suitability demonstrated a highly satisfactory area under the curve of 0.738. The study estimates that out of 172,618.66 hectares, approximately 47.46% of the land is highly suitable (S1) for soybean production, followed by 21.36% moderately suitable (S2), 11.91% marginally suitable (S3), 7.00% currently not suitable (N1), and 12.28% permanently not suitable (N2). Conclusively, the findings suggest that the study area exhibits conducive climatic conditions, optimal soil health, and access to quality irrigation water, all of which have the potential to support soybean crops with improved agronomic practices. This investigation offers valuable insights to both farmers and policymakers concerning irrigation water quality, agricultural productivity, and soil degradation.

GIS-based multicriteria and artificial neural network (ANN) investigation for the assessment of groundwater vulnerability and pollution hazard in the Braga shallow aquifer (Central Tunisia): A critical review of generic and modified DRASTIC models

Groundwater vulnerability and pollution hazard in the Braga shallow aquifer were assessed through an integrated GIS-based multicriteria analysis and Artificial Neural Network (ANN) approach, using DRASTIC and DRASTIC-LU models. The DRASTIC model integrates seven geological parameters. The DRASTIC-LU model includes an eighth parameter in addition to the previous ones. This parameter is the land use that represents the human source of groundwater pollution. The DRASTIC map showed four classes: very low (12.06%), low (81.88%), moderate (5.16%) and high (0.9%), where the vulnerability index ranged between 43 and 159. The DRASTIC-LU vulnerability index ranged between 53 and 204 and showed five classes: very low (3.10%), low (14.06%), moderate (17.11%), high (27.08%) and very high (38.65%). The DRASTIC-LU vulnerability map indicated that the high pollution risk is imposed by the intensive vegetable cultivation and the domestic wastewater. The pollution hazard index (PHI) was calculated based on the ANN modelling, using the land-use as an input and the vulnerability as a hidden layer. The DRASTIC model-based PHI map showed six classes: rare hazard (8.6%), very low (30.97%), low (6.18%), moderate (51.45%), high (2.43%) and very high (0.37%). While, The DRASTIC-LU model-based PHI map (PHILU) showed seven classes: rare hazard (2.91%), very low (11.9%), low (12.33%), moderate (13.78%), high (9.23%), very high (15.46%) and extremely hazardous (34.39%). The validation of these maps indicated that the DRSTIC-LU-based PHI is more reliable as it accurately identifies the hazardous zones.

Site suitability analysis for locating construction and demolition waste transfer station: an Indian case study.

Construction and Demolition Waste Management (CDWM) includes collecting, transporting, processing, and disposing construction and demolition (C&D) waste, where collection and transportation of bulky and voluminous C&D waste contribute significantly to economic and environmental impacts. Transfer station (TS) being a link between various waste management (WM) facilities plays a significant role in collection and transportation of waste. Thus, locating TS at suitable site can help in reducing the overall impacts. Employment of Geographic Information System (GIS) analysis tools in CDWM is a powerful strategy for site suitability study. A case study in Coimbatore, India, is presented in this study using GIS-based multi-criteria analysis for locating C&D waste TS. The criteria for site suitability analysis are chosen based on literature review, regulations, and experts' opinions. Weights of the chosen criteria are estimated using analytic hierarchy process (AHP), and the final suitability map is created by weighted overlay analysis (WOA) in GIS environment. Results provide first-hand information for local decision makers to locate C&D waste transfer station in the chosen study region and report that 12% of the entire area is "highly suitable" for transfer station location.

GIS-Based Multi-Criteria Analysis for Selecting Suitable Areas for Urban Green Spaces in Abomey-Calavi District, Southern Benin

Green spaces contribute to a significant improvement in quality of life and maintain the sustainability of cities. In Benin, despite the political willingness regarding greening, municipalities are experiencing technical issues in finding suitable spaces to achieve this goal. This study should therefore be applicable to many other towns in Benin. It aims at identifying suitable areas for green spaces to integrate landscaping into urban planning in Abomey-Calavi district. Multi-criteria analysis combining GIS and the hierarchical classification approach was performed. Six factors (land use, altitude, slope, distance from main roads, proximity to urban centres and distance from flood zones, water bodies) were combined using the ArcGIS “Spatial Analysis” extension to generate a map of green space suitability. The results show large areas of land, of which 23.27% is very suitable and 26.06% is suitable for landscaping in this municipality. The ranking of the factors revealed that elevation, proximity to road networks, large conurbations and distance from wetlands accounted for 18%, compared with 14% for the other factors regarding the study environment. However, the use of these results must take into account the existing inhabited areas for a good site selection. These outputs provide guidance for decision-makers in choosing suitable sites for green spaces and integrating them into sustainable development.

GIS-based multi-criteria analysis for flood hazard areas mapping of M’zab wadi basin (Ghardaia, North-Central Algeria)

Located in the hyper-arid regions of Algeria, the M’zab Wadi basin has historically experienced severe flash flooding, causing severe economic damage and loss of life. Identifying potential flood hazard areas in such an arid environment, challenged by data scarcity, is necessary to forecast flood and to create early warning strategies. The paper aims to map and highlight potential flood hazard areas in the M’zab Wadi basin using geographic information system coupled with the Analytical Hierarchy Process method based on seven related flood hazard factors. The accuracy of the flood hazard map was validated using the Receiver Operating Characteristic based Area Under Curves method. The results show that 3.04% (50.35 km2) and 0.53% (8.74 km2) of the basin area are under high and very high flood vulnerability levels, respectively. The obtained results can offer significant insights to policymakers and decision-makers to make well-informed judgments regarding the effectiveness of flood protective infrastructure/measures. Furthermore, the approach adopted can be advantageous for other regions under similar conditions.

A novel GIS-based multicriteria analysis approach for ascertaining the catchment-scale degradation of a Himalayan wetland

Wetland degradation through a diverse spectrum of anthropogenic stressors worldwide has taken a heavy toll on the health of wetlands. This study examined the health of a semi-urban wetland Bodsar, located in the Kashmir Himalaya using multicriteria analysis approach assimilating data on land use land cover (LULC), landscape fragmentation, soil loss, and demography. Wetland and catchment-scale land system changes from 1980 to 2022 were assessed using high-resolution imagery. Fragmentation of the natural landscape was assessed using the Landscape Fragmentation Tool (LFT) and soil loss was assessed using the Revised Universal Soil Loss Equation (RUSLE). In addition, the water quality was examined at 12 sites distributed across the wetland using standard methods. Satellite data revealed 12 categories of land use with areas under exposed rock, orchards, built-up and sparse forest having increased by 1005%, 623%, 274%, and 37% respectively. LFT indicated that the core (>500 acres) and core (<250 acres) zones decreased by approximately 16% and 64%, respectively, whereas the areas under the perforated, edge and patch classes increased significantly. RUSLE estimates show a ∼77% increase in soil erosion from 116.26 Mg a−1 in 1980 to 205.68 Mg a−1 in 2022, mostly due to changes in LULC. Total phosphorus (0.195–2.04 mg L −1), nitrate nitrogen (0.306–2.79 mg L −1), and total dissolved solids (543–774 mg L−1) indicated nutrient enrichment of the wetland influenced by anthropogenically-driven land system changes. The wetland degradation index revealed that 21% of the wetland experienced high-to-severe degradation, 62% experienced moderate degradation, and 17% did not face any significant degradation pressure. The novel GIS-based approach adopted in this study can act as a prototype for ascertaining the catchment-scale degradation of wetlands worldwide.

Validating the GIS-based Flood Susceptibility Model Using Synthetic Aperture Radar (SAR) Data in Sengah Temila Watershed, Landak Regency, Indonesia

In Indonesia, especially in regions where natural conditions and human activity coexist, flood disasters are a strong possibility. Flooding regularly has an impact on Sengah Temila, which is a component j/ of Indonesia's West Kalimantan Province. The issue in Sengah Temila is that there is little knowledge of the distribution of flood susceptibility in this region. The GIS-based flood susceptibility model has been widely used in Indonesia, but research dedicated to validating the model is limited. SAR-based analysis has been used for flood mapping in Indonesia, but its use for validating flood models has been limited. The objective of this study is to identify the optimal weighting scenario for a GIS-based multi-criteria analysis flood model for use in the Sengah Temila Watershed. The GIS-based model is created by merging spatial parameters, including slope, elevation, flow accumulation, drainage density, land use and land cover (LULC), soil type, normalized difference vegetation index (NDVI), curvature, rainfall, distance to river, and topographic wetness index (TWI) with weighted multi-criteria analysis. In addition, Sentinel-1 GRD images from before and after the floods have been retrieved from Google Earth Engine using past floods of the watershed. In order to create a SAR-based flood model, the researchers then integrated and categorized the results. Eleven weighting scenarios were used to create eleven GIS-based flood models. To calculate the degree of spatial similarity, all of these models were contrasted with the SAR-based model using the Fuzzy Kappa approach. We found that in order to achieve ideal weighting, slope, topographic wetness index (TWI), rainfall, and flow accumulation should each be given a larger value.

Determination of winter tourism potential areas in Türkiye using a GIS-based multi-criteria analysis

Tourism, one of the expeditiously growing and most important sectors, contributes to the national economy by increasing employment and foreign exchange income. As in many countries, the place of tourism in the country's economy is very important in T?rkiye (formerly known as Turkey). As one of the sources that have contributed significantly to the country's economy for many years, it has played a locomotive role in its development. T?rkiye is trying to increase its share of international tourism revenues with investments and incentives. Although it is a country that draws attention with its areas suitable for winter tourism, the development of winter tourism centers is very slow when some aspects are taken into account. Konya Province is one of the few religious and cultural tourism centers of T?rkiye. The region has qualified winter tourism areas. Bringing these areas to tourism can be an important resource for both the provincial and national economy. This study proposes a Geographical Information System based Multi Criteria Evaluation (MCE) model using Best Worst Method (BWM) to identify the most suitable locations for winter tourism facilities in the Konya region of T?rkiye. Among some suitable areas determined according to the results of the analysis, Alada? Mountain in Derbent region has been seen as the most suitable place for winter tourism investments, as it has all the features such as snow quality, transportation, and snowy day duration that should exist in a winter tourism center.

Groundwater potential assessment using remote sensing and GIS-based multi criteria analysis – the case of Montserrado County, Liberia

Liberia is marked by poor and insufficient hydrogeological data due to limited studies coupled with years of civil instability. Although Montserrado County has abundant water resources, lack of adequate knowledge of the available water resources has led to unsustainable groundwater utilization as well as investment losses from drilling unsuccessful boreholes. This research therefore aims at blending remote sensing with GIS-based multicriteria analysis to delineate suitable groundwater potential zones. Remote sensing and conventional data were used to construct a groundwater potential zone (GWPZ) map by integrating lineament and drainage densities, geology, slope and elevation, soil, annual rainfall, land use land cover, and the normalized difference vegetation index (NDVI) maps of the study area. The Analytic Hierarchy Process (AHP) was used in assigning weights to each thematic map, according to its influence on groundwater accumulation, for their integration. The results reveal that slope, lineament density, drainage density, geology, and land use land cover are parameters with the most influence (about 68%) on groundwater recharge within the area. The result also shows that about 10 %, 25 %, 30 %, 25 %, and 10 % of Montserrado County has very high, high, moderate, low zone, and very low groundwater potential zones, respectively. The study, therefore, provides very useful information that may guide the development and management of the groundwater resources within the study area.

Satellite remote sensing and GIS-based multi-criteria analysis for assessing the groundwater recharge potential zones in the Regueb basin (central Tunisia)

Satellite remote sensing and GIS-based multi-criteria analysis for assessing the groundwater recharge potential zones in the Regueb basin (central Tunisia)

GIS-based multi-criteria analysis of an eco-innovative APOC wastewater treatment and reuse system for irrigation purposes in the rural locality of Bent Saidane (NE Tunisia)

GIS-based multi-criteria analysis of an eco-innovative APOC wastewater treatment and reuse system for irrigation purposes in the rural locality of Bent Saidane (NE Tunisia)

Service area determination of fire stations in an urban setting through a GIS-based multi-criteria analysis: the case of Quezon City, Philippines

Service area determination of fire stations in an urban setting through a GIS-based multi-criteria analysis: the case of Quezon City, Philippines