GIS-based multi-criteria decision analysis for dam site selection in the Pedieos River basin, Cyprus

A risk-based multi-criteria spatial decision analysis for solar power plant site selection in different climates: A case study in Iran

Chapter 16 - Municipal landfill site selection and environmental impacts assessment using spatial multicriteria decision analysis: A case study

Industrial site selection is one of the basic vital decisions in the start-up process, expansion or relocation of businesses of all kinds. Starting from the meeting criteria defined in the business strategy, site selection process begins as recognition of existing or projected need to meet new or growing market. Recognition of the need of new industrial location initiate a series of activities directed for looking geographical area and specific location. Conquer new territories for business starts with collecting geopolitical data, where location is a part of it. The selection of an industrial site involves a complex array of critical factors involving economic, social, technical, environmental, political issues, etc. It is obvious that many factors must be involved in the decision-making process, which makes the problem challenging choice in the selection of appropriate tools to enable concentration data, information and analysis. New trends in information technologies put geo-information technology in the centre of events in industrial locations science. Geographic Information Systems (GIS) provides functionality to capture, store, query, and analyse geographic information, but that is not enough for multi criteria analysis and decision making. Recent development in GIS leads to dramatic improvement in multi-criteria decision analysis (MCDA) and decision making. This paper presents the state of the art in GIS based multi-criteria decision analysis for industrial site selection.

GIS-based multi-criteria decision analysis for groundwater dam site selection in an arid and semi-arid region of Algeria

Utilizing multi-criteria decision-making analysis and 3D visualization techniques for dam site selection and irrigation area identification in Gedeb River, Ethiopia

A multi-criteria decision analysis approach towards efficient rainwater harvesting

This study presents a Geographic Information System-based (GIS-based) multi-criteria decision analysis for avalanche risk mapping using the Analytical Hierarchy Process (AHP) method in Van province of Turkey. Essential parameters for avalanche occurrence such as slope, elevation, aspect, curvature, and land cover are used in this study. Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) is used to generate slope, elevation, aspect, and curvature layers; Corine Land Cover data is used as a land cover map, and Landsat 8 OLI satellite imagery was used to extract snow-covered areas. The GIS-based multi-criteria analysis was used to assess the areas’ risk susceptibility; thus, 29% of the study area is classified as having a very low risk, 46% low risk, 18% moderate risk, 5% high risk, and 2% very high risk. The resulting avalanche risk map will create a clear view of the riskiest areas. It can be useful for taking emergency measures in the area and artificially trigger avalanches before they naturally start to form.

Land selection for crops is crucial for sustainable production and economic development in tropical regions. Climate play a significant role in determining suitable areas for crop growth. Land selection for cultivation in Ethiopia is evaluated using GIS-based multi-criteria decision analysis, combining weighted thematic layers of soil, climate, topography, and socioeconomic factors to classify land into four suitability classes. A systematic literature review was conducted using studies conducted primarily in Ethiopia detail a consistent approach for evaluating land suitability that readily extends to crop cultivation in the Abaya-Chamo watershed. All studies prepare layered data on soil, climate, topography, socio-economic factors, and current land use. Nine of ten relied on Geographic Information Systems to integrate this information, and five employed the Analytical Hierarchy Process to weight selected criteria. The common procedure involved: (1) Prepared thematic layers from sources such as Landsat imagery, digital elevation models, and soil surveys. (2) Combined these layers through spatial overlay techniques (including weighted overlays) to classify land into four suitability classes from highly (or optimally) suitable to not suitable. (3) Employed expert judgment and literature review to select relevant criteria for the target crop or agricultural use. The specific crop foci ranged from rice and wheat to sesame and agroforestry systems, the integration of numeric and categorical criteria using GIS-based multi-criteria decision analysis provides a replicable framework. The methods described by the studies support the application of these procedures to assess land suitability for crop cultivation in a watershed, relying on consistent quantitative criteria and mapping techniques.

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

Landfill site selection in an urban area like National Capital Territory (NCT) of Delhi is a challenging task due to shortage of suitable land and other environmental, economic and social parameters. This study focusses on the utilisation of geographic information system, open-source libraries and remote sensing for identification of potential landfill sites in Delhi NCT. Multi-criteria decision analysis (MCDA) and other GIS-based approaches are used for analysing various natural parameters derived using remote sensing satellite data products. Resourcesat LISS-III and Sentinel-2 multispectral satellite data is used for deriving the required parametric layers. Zones in the vicinity of monuments, transport, canals, drainages, lineaments are avoided altogether. Results reveal overall, most suitable places for landfill site in study area is around 4.05 sq. km (0.27%), moderately suitable places are 14.68 sq. km (0.98%), least suitable places are 25.46 sq. km (1.71%) and not suitable places is 1,419.11 sq. km (95.62%).

The current study presents the integration of geographical information system (GIS) and multi-criteria decision analysis (MCDA) for municipal landfill site selection, a case example in Iran. In the first step, useful criteria were determined based on the literature review, national standards and regulations, expert opinion, data availability and regional characteristics. Several criteria including distance from groundwater resources, distance from surface water, distance from urban and rural areas, distance from protected areas, land use, distance from faults, distance from roads and the slope were selected, and a hierarchical structure was formed for landfill suitability. The maps of the criteria were prepared using ArcGIS 10.2. Using different fuzzy membership functions, the maps were standardized. An AHP-based pairwise comparison was applied to calculate the weights of the parameters, and standardized maps were overplayed using the weighted layer combination approach to gain the landfill suitability map in the study area. The final map was assorted into four suitability classes, i.e., high, moderate, low and unsuitable regions. The result indicates that almost 92% of the study area is inappropriate and cannot be considered as landfill. The comprehensive field visits were performed to further assessment, and finally, three candidate sites were suggested. The result illustrated that an integrating approach of GIS and MCDA is effective in landfill site selection.

Demand for parking areas has increased with the growing population and increasing number of vehicles. Large cities are suffering from a lack of parking areas, which are one of the most significant parts of the modern urban transportation system and traffic management. Locating parking areas has become a major challenge for the urban transport planners, especially in the downtown of metropolises. Geographic Information Systems (GIS) with geographic analysis tools can provide a scientific approach to determine optimum locations for parking areas. In this paper, the essential factors affecting parking site selection were considered and data sets concerning these factors were created by GIS analysis techniques. The Analytical Hierarchy Process (AHP) as a Multiple-Criteria-Decision-Analysis (MCDA) method was applied to derive weights of the selected parameters. To conduct parking demand analysis, the parking suitability map was produced by integrating the GIS with AHP. Then, suitable parking areas were determined in a zoning plan that was based on the highest suitability on the map. Other MCDA techniques including TOPSIS and VIKOR were examined and compared to determine the order of preferences among suitable parking areas. Similar to the traditional AHP method, the same results were obtained in the ranking of parking areas with the other methods. Using GIS with these MCDA techniques appears to be a usable approach for better resource allocation as well as parking site selection.

Evaluation of groundwater vulnerability to pollution using a GIS-based multi-criteria decision analysis

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.

Solid waste management is a global challenge, especially in developing countries due to the rapid increase in population and urbanization where the availability of sanitary landfills is inevitable. Determining suitable landfill sites is a fundamental aspect for new and rapidly growing cities. The current study is aimed at selecting potential landfill sites using GIS-based multi-criteria decision analysis in Dodoma capital city. Fifteen criteria including proximity from built-up areas, surface water, boreholes, sensitive sites including social service areas, episodic water channels, protected areas including historical sites, faults, land use/land cover, geology, soil type, elevation, slopes, airport, roads, and earthquake epicentres were integrated with the help of analytical hierarchy process (AHP). The landfill sites’ suitability map was produced based on the weighted linear combination method and assigned suitability classes as highly suitable, suitable, moderately suitable, less suitable, and unsuitable. The overall suitability results show that 41,177 ha (14.7%) of the study area is determined as highly suitable for landfills site location. The remaining 83,930 ha (30%), 84,305 ha (30.2%), and 53,508 ha (19.1%) of the area are suitable, moderately suitable, and less suitable respectively while 16,683 ha (6%) is under the unsuitable zone. From the highly suitable area, eleven candidate landfill sites were selected and prioritized using the AHP technique. The final results show landfill site 3 (10,361.94 ha), 5 (3717.85 ha), and 2 (3535.86 ha) were found to be the most highly suitable sites with eigenvector weight of 0.147, 0.122, and 0.121 respectively. Landfill sites 8, 7, and 6 were lastly considered. Field observation involving expertise from geology, hydrogeology, geophysical, and environment confirmed the suitability of selected sites. Thus, these techniques can be employed in developing countries to locate suitable landfill sites to minimize health and environmental impacts.