Suitable map analysis for wind energy projects using remote sensing and GIS: a case study in Turkey

Environ Monit Assess. 2019 Jun 24;191(7):459. doi: 10.1007/s10661-019-7551-8.

Abstract

The aim of the study is to create a suitable map for wind energy projects in a rural area. The primary goal here is to show a methodology using automatic object extraction of the target classes of buildings, vegetation, and ground. The secondary goal is to identify the potential effects for wind turbine sites based on four criteria: Wind speed, Slope, Building, and Vegetation using the fuzzy analytical hierarchy process (FAHP). This paper discusses two important situations for wind energy projects. The first strategy is to just determine the best suitable site locations of wind turbines, while the second strategy determines the locations of wind turbines with minimal negative effects on the rural area. The proposed approach is tested using the data obtained from a multi-sensor system in Evrencik, Turkey. In preliminary phases of renewable energy projects, successful results are dependent on evaluating the potential site's suitability with criteria such as social, environmental, physical, and economic conditions. Furthermore, an accuracy analysis is performed on the automatically extracted target classes for the study area, yielding a value of 89% in the remote sensing section of the study. Moreover, for the GIS section of the study, suitable and unsuitable areas are identified, and the suitability levels of the remaining areas are determined for the two strategies. According to the results, 11% of the areas are found to have high, moderate, and low suitability levels, and 89% are unsuitable for the first strategy, whereas these rates are, respectively, 2% and 98% for the second strategy.

Keywords: FAHP; LiDAR; Rule-based classification; Wind energy.

MeSH terms

  • Environmental Monitoring
  • Geographic Information Systems*
  • Geographic Mapping*
  • Physical Phenomena
  • Remote Sensing Technology / methods*
  • Turkey
  • Wind*