QGIS-based weighted linear combination plugin for landfill site selection: a case study in Tokat Province, Turkey.

Proper disposal of solid waste is crucial for the protection of natural resources and human health. However, increasing population and changes in consumption habits have led to a global increase in solid waste production. Therefore, a site selection process for solid waste management that takes into account environmental, economic, and social factors is needed. The number of open-source GIS (geographic information system) software programs used in site selection analysis is increasing day by day. QGIS software is an open-source GIS software developed by free software developers, with its popularity increasing with each new version and allowing for the development of plugins with the Python programming language. The shareability of plugins developed with QGIS software brings together open-source GIS users around the world for common goals. In this study, a plugin called "LANDFILL SITE SELECTION (LFSS)" was developed in the QGIS software environment for solid waste landfill site selection and a suitability map was created for solid waste landfill site selection in Tokat, Turkey, using this plugin. For this purpose, 14 evaluation criteria and 8 exclusion criteria were selected, the importance levels of criteria and sub-criteria were determined using the AHP method, and a solid waste landfill site selection suitability map was created using the developed plugin.

A GIS-based multi-criteria decision-making method for the selection of potential municipal solid waste disposal sites in Mersin, Turkey.

Due to rapid urbanization and the resulting rapid population increases, an important problem for cities today is the elimination of solid waste or finding suitable places for waste storage. Municipal solid waste disposal (MSWD) site selection is one of the most important steps in urban waste management. Many criteria political, economic, social, and technological should be considered in this process. Geographic information systems (GIS) and multi-criteria decision-making (MCDM) are tools that are superior to traditional methods in the planning phase of site selection studies. In this study, suitable MSWD sites were determined in Mersin (a Turkish province) based on GIS and the analytic hierarchy process, an MCDM method. Unsuitable areas in the study were removed at the beginning of the analysis. Eleven evaluation criteria were selected: elevation, slope, permeability, distance from lineaments, groundwater level, distance from rivers and water surfaces, distance from roads, distance from settlements, distance from protected areas, and land cover. Considering the evaluation and exclusion criteria, 19.12% of the study area was deemed suitable, and 80.88% was determined unsuitable for an MSWD site. An MSWD suitability map was created as a result of the study. The outcomes indicate that 80,377 ha and 83,022 ha of the study area were classified as high and very high suitability, respectively. Based on these results, we evaluate whether the locations of existing solid waste landfills are appropriate and propose alternative solid waste landfills for each district.

Geographic information system-based investment system for photovoltaic power plants location analysis in Turkey.

The motivation of this research, development, demonstration, deployment, and diffusion (RD3&D) study is to present the progress of designing the GIS-based location selection module of autonomous investment decision support system and its experimental application for photovoltaic power plants (PVPPs) in Antalya, Burdur, and Isparta planning region Turkey. The other motivation of this RD3&D study is to start investigating in combinations the applicability and usability of weighted linear combination with 4 subjective weighting approaches (rank sum weight method (RS), inverse or reciprocal weights method (RR), rank order centroid (ROC), point allocation (PA)) for 5 main criteria, 14 sub-criteria, and 79 value ranges. The results show that 38.48% of the planning region is unsuitable, 61.52% is suitable. Only 2.07% of this region is very highly suitable according to RS. 7.13%, 9.22%, and 5.58% are respectively very highly suitable according to RR, ROC, and PA. Similarities between RS, RR, ROC, and PA methods are presented such as RS-RR: 0.7834, RS-ROC: 0.8510, and RS-PA: 0.6384 with covariance and correlation analysis. A backward-looking performance verification and validation analysis is also performed with 7 PVPPs for only 4 decisive success factors (capacity factor, annual energy/land use, project cost/capacity, project cost/energy). This study is thus able to evaluate the optimal locations for future investments, as well as the suitability conditions of the available investments. This study will contribute to provide some useful recommendations for decision makers to identify and assess the hotspots which are suitable for PVPPs in the planning region.