4.7 Article

Monitoring wind farms occupying grasslands based on remote-sensing data from China's GF-2 HD satellite-A case study of Jiuquan city, Gansu province, China

Journal

RESOURCES CONSERVATION AND RECYCLING
Volume 121, Issue -, Pages 128-136

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.resconrec.2016.06.026

Keywords

Wind farm; Grassland monitoring; China's GF-2 HD satellite; Gansu province

Funding

  1. National Natural Science Foundation of China [41571105, 31372354]
  2. International Science & Technology Cooperation Program of China [2013DFR30760]
  3. Agricultural Scientific Research Fund of Outstanding Talents, Ministry of Agriculture, China [2015003]
  4. Agricultural and Rural Resource Monitoring Statistics (Grassland Monitoring) Project
  5. Open Fund for the Key Laboratory of Agri-informatics, Ministry of Agriculture, China [2015003]

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Wind power is a clean and renewable resource, and it is rapidly becoming an important component of sustainable development and resource transfer. However, the construction of wind farms impacts the environment and has been the subject of considerable research. In this study, we verified whether China's GF-2 HD satellite (GF-2) could be used to monitor the 10 million kilowatt wind power grassland construction area in Jiuquan City, Gansu Province. Monitoring was performed by comparing the imaging results from the Landsat 8 OLI and China's GF-1 HD satellite (GF-1). We performed an interactive interpretation of the remote sensing images and verified the accuracy of these interpretations using measured field data. We evaluated 354 pieces of wind turbine equipment with an average construction density of 0.31 km(2) per device. The construction of a single wind turbine was found to damage nearly 3000 m(2) of grassland. The average area of grassland damaged by 3 MW and 1.5 MW turbines was 5757 m(2) and 2496 m(2), respectively. Approximately 2.44 km(2) of farmland was occupied by wind power construction and accounted for approximately 2.2% of the study area. Roads covered 60.6% of the farmland occupied by wind power construction. The average difference between the measured and calculated GF-2 image data was 0.09, and the overall interpretation accuracy was approximately 84%. Therefore, the use of comprehensive imaging analyses and GF-2 image data are feasible for monitoring grasslands under construction for wind power. In addition, the impacts of wind farm construction on vegetation destruction and soil erosion are discussed. In this study, grassland wind farms are explored using remote sensing tools to guide decision making with regards to the rational use of grassland resources and their sustainable development. (C) 2016 Elsevier B.V. All rights reserved.

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