Impacts of wind turbines on vegetation and soil cover: a case study of Urla, Cesme, and Karaburun Peninsulas, Turkey

Aksoy T., Cetin M., Cabuk S. N. , ŞENYEL KÜRKÇÜOĞLU M. A. , Ozturk G. B. , Cabuk A.

CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2022
  • Doi Number: 10.1007/s10098-022-02387-x
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Agricultural & Environmental Science Database, Aqualine, CAB Abstracts, Compendex, Environment Index, Greenfile, INSPEC, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Wind power plant, Vegetation change, Land degradation, CORINE, NDVI, ENERGY DEVELOPMENT, POWER DEVELOPMENT, FARMS
  • Middle East Technical University Affiliated: Yes


The study presents a GIS- and RS-based diagnostic model to determine the changes in the existing vegetation in the Urla, Cesme, and Karaburun peninsulas, Turkey, between 2002 and 2017 after the installation of 239 wind power plants (WPP). The vegetation changes in 7 CORINE land cover classes within the 0-1 km (facility zone) and 1-2 km (control zone) buffer zones were detected in relation with the slope and aspect groups using NDVI analysis. The highest amount of negative change in broad-leaved forests, coniferous forests, and land principally occupied by agriculture, with significant areas of natural vegetation, was detected in the 3-5% slope group, while pasture lands, sclerophyllous vegetation and transitional woodland-shrubs showed the highest degradation in 1-2% slope areas. Negative changes in complex cultivation patterns were found to be on the flat surfaces. Except for the pasture lands and sclerophyllous vegetation classes, the highest degradations were observed on north-facing aspects. In all land cover classes, the most degraded areas were found to be within the facility zone. The results and the proposed model are expected to facilitate planning and decision-making processes for locations with similar landscape characteristics.