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Open AccessArticle

Determining Optimal Solar Power Plant Locations Based on Remote Sensing and GIS Methods: A Case Study from Croatia

1
State Geodetic Administration, Gruška 20, 10000 Zagreb, Croatia
2
Faculty of Geodesy, University of Zagreb, Kačićeva 26, 10000 Zagreb, Croatia
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(12), 1481; https://doi.org/10.3390/rs11121481
Received: 19 May 2019 / Revised: 14 June 2019 / Accepted: 18 June 2019 / Published: 22 June 2019
In the last few years, the world has been turning to the exploitation of renewable energy sources due to increased awareness of environmental protection and increased consumption of fossil fuels. In this research, by applying geographic information systems and integrating them with multi-criteria decision making methods, an area suitable for the construction and exploitation of renewable energy sources is determined. The research uses not only climate, spatial, environmental, and geomorphological parameters but also socioeconomic parameters, population, unemployment, and number of tourist nights as well as electricity consumption. By applying spatial analysis, rasters of all parameters were created using GRASS GIS software. Using the analytic hierarchy process, the calculated rasters are assigned with weight coefficients, and the sum of all those rasters gives the final raster of optimal locations for the construction of solar power plants in Croatia. To test the accuracy of the obtained results, sensitivity analysis was performed using different weight coefficients of the parameters. From the sensitivity analysis results, as well as a histogram and statistical indicators of the three rasters, it is apparent that raster F1 gives the best results. The most decisive parameters in determining the optimal solar plant locations that result from this research are GHI, land cover, and distance to the electricity network. View Full-Text
Keywords: AHP; GIS; remote sensing; solar energy AHP; GIS; remote sensing; solar energy
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MDPI and ACS Style

Gašparović, I.; Gašparović, M. Determining Optimal Solar Power Plant Locations Based on Remote Sensing and GIS Methods: A Case Study from Croatia. Remote Sens. 2019, 11, 1481.

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