Detecting Wind Farm Impacts on Local Vegetation Growth in Texas and Illinois Using MODIS Vegetation Greenness Measurements

Abstract

This study examines the possible impacts of real-world wind farms (WFs) on vegetation growth using two vegetation indices (VIs), the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), at a~250 m resolution from the MODerate resolution Imaging Spectroradimeter (MODIS) for the period 2003-2014. We focus on two well-studied large WF regions, one in western Texas and the other in northern Illinois. These two regions differ distinctively in terms of land cover, topography, and background climate, allowing us to examine whether the WF impacts on vegetation, if any, vary due to the differences in atmospheric and boundary conditions. We use three methods (spatial coupling analysis, time series analysis, and seasonal cycle analysis) and consider two groups of pixels, wind farm pixels (WFPs) and non-wind-farm pixels (NWFPs), to quantify and attribute such impacts during the pre-and post-turbine periods. Our results indicate that the WFs have insignificant or no detectible impacts on local vegetation growth. At the pixel level, the VI changes demonstrate a random nature and have no spatial coupling with the WF layout. At the regional level, there is no systematic shift in vegetation greenness between the pre-and post-turbine periods. At interannual and seasonal time scales, there are no confident vegetation changes over WFPs relative to NWFPs. These results remain robust when the pre-and post-turbine periods and NWFPs are defined differently. Most importantly, the majority of the VI changes are within the MODIS data uncertainty, suggesting that the WF impacts on vegetation, if any, cannot be separated confidently from the data uncertainty and noise. Overall, there are some small decreases in vegetation greenness over WF regions, but no convincing observational evidence is found for the impacts of operating WFs on vegetation growth.

Impacts of 319 wind farms on surface temperature and vegetation in the United States

“…However, about 40% of our wind farm samples did not decrease vegetation and instead showed a higher peak NDVI. These results supported the possibility of non-detectable (Xia and Zhou 2017) or positive vegetation effects (Xu et al 2019) reported in other studies at an individual wind farm. Although the construction and operation of wind farms posed a negative impact on vegetation for most wind farms, such effects could be mitigated by other local factors.…”

“…The upwind and downwind regions of wind farms could cause different impacts (Meyers and Meneveau 2012), but we did not distinguish them in our analyses. There is evidence for undetectable impacts of wind farms on vegetation growth in west-central Texas (Xia and Zhou 2017). Hence, the impacts of wind farms on local vegetation are complex and variable, which are influenced by human activity, altered local climate, or any other undiscovered local factors.…”

Localized Eco-Climatic Impacts of Onshore Wind Farms: A Review

“…Although in situ data monitoring has the advantages of high data accuracy and distinctive features, it is limited in scale and has a major disadvantage, especially in assessing the ecological and climatic impacts of onshore wind farms in a large-scale context. In situ data monitoring can provide reliable information for the inversion of remotely sensed data, such as inversely assessing near-surface temperatures at different times (Walsh-Thomas et al, 2012; Zhou et al, 2012; Zhou et al, 2013; Harris et al, 2014; Slawsky et al, 2015; Chang et al, 2016; Liu et al, 2021b; Luo et al, 2021; Liu et al, 2022a; Ma et al, 2022; Qin et al, 2022), vegetation indexes (Li et al, 2016; Tang et al, 2017; Xia and Zhou, 2017; Wu et al, 2019; Liu et al, 2022b; Aksoy et al, 2023), landscape patterns (Zhang et al, 2016; Diffendorfer et al, 2019; Guo et al, 2020) and other indicators in order to assess the impacts of onshore wind farms on the localized eco-climate.…”

“…Since the measurement of vegetation growth indicators is based on the inversion of satellite remote sensing data, the accuracy of remote sensing data affects the reliability of the final conclusions. An analysis of NDVI and EVI of onshore wind farms in the USA revealed that the variations of both values are within the uncertainty of MODIS data, so the impact of onshore wind farms on vegetation may be related to the uncertainty and noise in the remote sensing data (Xia and Zhou, 2017).…”

Do wind turbines impact plant community properties in mountain region?

“…2017). Recent studies brought into attention the impact of wind turbines on vegetation on the basis of satellite data analysis (Li et al 2016;Tang et al 2017;Xia and Zhou 2017) or simulations that were conducted for understanding the interplay between wind and vegetation under various scenarios of development (Peringer et al 2016;Fang et al 2018). Even more recently, the influence of wind 4 farms on vegetation structure at local scale was analysed by performing systematic field surveys.…”