Long-Term Impacts of 250 Wind Farms on Surface Temperature and Vegetation in China: A Remote Sensing Analysis
Wind energy is widely considered a clean and renewable resource, yet the environmental impacts of wind farm (WFs) installations, particularly on local climate and ecosystems, remain underexplored on a large scale. This study presents a comprehensive assessment of the long-term effects of 250 WFs acr...
Saved in:
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/17/1/10 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
_version_ | 1841548994518450176 |
---|---|
author | Xiaohui Han Chen Lu Jiao Wang |
author_facet | Xiaohui Han Chen Lu Jiao Wang |
author_sort | Xiaohui Han |
collection | DOAJ |
description | Wind energy is widely considered a clean and renewable resource, yet the environmental impacts of wind farm (WFs) installations, particularly on local climate and ecosystems, remain underexplored on a large scale. This study presents a comprehensive assessment of the long-term effects of 250 WFs across China on land surface temperature (LST) and vegetation using remote sensing data. By comparing inside and outside LST and peak normalized difference vegetation index (NDVI) trends before and after five years of construction, we identified key environmental changes. Results indicated that the WFs significantly increased nighttime LST by 0.20 °C and decreased daytime LST by 0.11 °C, with pronounced seasonal variability during daytime. A total of 75.20% of the WFs negatively impacted vegetation, with no discernible seasonality in this effect. Geographical factors such as latitude, longitude, and elevation showed weak correlations with these impacts. Our findings provide valuable insights into the environmental consequences of wind power development and contribute to more informed planning for sustainable energy generation and climate adaptation strategies. |
format | Article |
id | doaj-art-6743e1de234d49b18f3065d538ea58c0 |
institution | Kabale University |
issn | 2072-4292 |
language | English |
publishDate | 2024-12-01 |
publisher | MDPI AG |
record_format | Article |
series | Remote Sensing |
spelling | doaj-art-6743e1de234d49b18f3065d538ea58c02025-01-10T13:19:56ZengMDPI AGRemote Sensing2072-42922024-12-011711010.3390/rs17010010Long-Term Impacts of 250 Wind Farms on Surface Temperature and Vegetation in China: A Remote Sensing AnalysisXiaohui Han0Chen Lu1Jiao Wang2School of Information Engineering, China University of Geosciences, Beijing 100083, ChinaLand Satellite Remote Sensing Application Center, The Ministry of Natural Resources of the People’s Republic of China, Beijing 100048, ChinaSchool of Information Engineering, China University of Geosciences, Beijing 100083, ChinaWind energy is widely considered a clean and renewable resource, yet the environmental impacts of wind farm (WFs) installations, particularly on local climate and ecosystems, remain underexplored on a large scale. This study presents a comprehensive assessment of the long-term effects of 250 WFs across China on land surface temperature (LST) and vegetation using remote sensing data. By comparing inside and outside LST and peak normalized difference vegetation index (NDVI) trends before and after five years of construction, we identified key environmental changes. Results indicated that the WFs significantly increased nighttime LST by 0.20 °C and decreased daytime LST by 0.11 °C, with pronounced seasonal variability during daytime. A total of 75.20% of the WFs negatively impacted vegetation, with no discernible seasonality in this effect. Geographical factors such as latitude, longitude, and elevation showed weak correlations with these impacts. Our findings provide valuable insights into the environmental consequences of wind power development and contribute to more informed planning for sustainable energy generation and climate adaptation strategies.https://www.mdpi.com/2072-4292/17/1/10wind farmsland surface temperature (LST)vegetation dynamicslong-term environmental impactsremote sensing analysis |
spellingShingle | Xiaohui Han Chen Lu Jiao Wang Long-Term Impacts of 250 Wind Farms on Surface Temperature and Vegetation in China: A Remote Sensing Analysis Remote Sensing wind farms land surface temperature (LST) vegetation dynamics long-term environmental impacts remote sensing analysis |
title | Long-Term Impacts of 250 Wind Farms on Surface Temperature and Vegetation in China: A Remote Sensing Analysis |
title_full | Long-Term Impacts of 250 Wind Farms on Surface Temperature and Vegetation in China: A Remote Sensing Analysis |
title_fullStr | Long-Term Impacts of 250 Wind Farms on Surface Temperature and Vegetation in China: A Remote Sensing Analysis |
title_full_unstemmed | Long-Term Impacts of 250 Wind Farms on Surface Temperature and Vegetation in China: A Remote Sensing Analysis |
title_short | Long-Term Impacts of 250 Wind Farms on Surface Temperature and Vegetation in China: A Remote Sensing Analysis |
title_sort | long term impacts of 250 wind farms on surface temperature and vegetation in china a remote sensing analysis |
topic | wind farms land surface temperature (LST) vegetation dynamics long-term environmental impacts remote sensing analysis |
url | https://www.mdpi.com/2072-4292/17/1/10 |
work_keys_str_mv | AT xiaohuihan longtermimpactsof250windfarmsonsurfacetemperatureandvegetationinchinaaremotesensinganalysis AT chenlu longtermimpactsof250windfarmsonsurfacetemperatureandvegetationinchinaaremotesensinganalysis AT jiaowang longtermimpactsof250windfarmsonsurfacetemperatureandvegetationinchinaaremotesensinganalysis |