@ARTICLE{Yankiv-Vitkovska_Liubov_Site_2020,
 author={Yankiv-Vitkovska, Liubov and Peresunko, Bohdan and Wyczałek, Ireneusz and Papis, Joanna},
 volume={vol. 69},
 number={No 1},
 pages={97-116},
 journal={Geodesy and Cartography},
 howpublished={online},
 year={2020},
 publisher={Commitee on Geodesy PAS},
 abstract={Renewable energy from solar power plants is becoming more and more popular due to the depletion of raw materials and reduction of dependence on oil and gas and is also harmless to the natural environment. The management and rational use of land resources is currently a pressing problem in the world, including in Ukraine. One of the solutions is the development of technologies for the use of these areas and the establishment of environmentally friendly technologies for reducing air pollution, namely electricity facilities – solar power plants based on the use of photovoltaic panels. Choosing the right location for obtaining solar energy depends on many factors and constraints. Optimal location of solar farms is important to maximize the beneficial features of projects while minimizing the negative. A method of finding places in the vicinity of large cities that could be suitable for installing power plants was developed. The proposed method uses an analytical hierarchical process, analytical network process, Boolean logic and weighted linear combination. It has been implemented in the QGIS program. The method was successfully used for the city of Zaporizhia, but it can be directly implemented in any other region. That is why the presented works constitute a scheme that can be easily used to estimate large areas in order to optimally choose a place for a solar park in the vicinity of large cities. Such a model can be very useful for investors to find potential locations for solar energy before conducting detailed field research.},
 type={Article},
 title={Site selection for solar power plant in Zaporizhia city (Ukraine)},
 URL={http://journals.pan.pl/Content/114483/PDF/art_08.pdf},
 doi={10.24425/gac.2020.131076},
 keywords={AHP, power plants, multicriteria analysis, QGIS},
}