Assessment of forest disturbance and soil erosion in wind farm project using satellite observations 

Highlights

• A novel method was proposed to map forest disturbances from wind farm construction.
• The average forest disturbance intensity of wind farms is 4.3 ha/MW.
• Road construction is the primary factor causing forest disturbances.
• Reduced vegetation cover by wind power development exacerbates soil erosion.

Abstract
The construction of wind farms, involving road construction and wind turbine installation, severely disrupts natural landscapes. Wind energy expansion in global forested areas has unclear impacts on local forests and ecosystem services. Due to a lack of information on internal road distribution and deployment dates, few studies have assessed forest disturbances caused by wind farms. Environmental issues like vegetation destruction and soil erosion may be overlooked. To address this, we integrated multi-source spaceborne observations to identify deployment dates and road distributions of forest wind farms and mapped related forest disturbances and soil erosion changes. Six global locations were tested, showing over 80 % accuracy. Disturbance intensity ranged from 1.5 to 6.5 ha/MW, with the normalized difference vegetation index decreasing by 0.03 to 0.33 in disturbed forest regions. The average soil erosion increase per unit area due to road construction ranged from 24.74 to 274.33 t/hm⁻¹ a⁻¹, while wind turbine construction caused an average soil erosion increase ranging from 26.52 to 26.52 to 263.46 t/hm⁻¹ a⁻¹. Road construction is the primary cause of forest disturbance, with greater soil erosion increases in mountainous than in plain forests. This method enhances monitoring and understanding of wind farms’ environmental impacts.

Graphical abstract

Zilong Xia, Shanchuan Guoa, Xingang Zhang, Xiaoquan Pan, Hong Fang, Peijun Du, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, and Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Yingjie Li, Natural Capital Project, Woods Institute for the Environment, Stanford University, Stanford, California
Ruishan Chen, School of Design, Shanghai Jiaotong University, China

Resources, Conservation and Recycling, Volume 212, January 2025, 107934
doi: 10.1016/j.resconrec.2024.107934