Codes and Datasets for “A global assessment of the effects of solar farms on albedo, vegetation, and land surface temperature using remote sensing"

<b>Codes and Datasets for “A global assessment of the effects of solar farms on albedo, vegetation, and land surface temperature using remote sensing"</b>Contacts: Zhengjie Xu ([e-mail]); Yan Li* ([e-mail])*Correspondance: Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.<b>Abstract:</b>This document describes the codes and datasets for“A global assessment of the effects of solar farms on albedo, vegetation, and land surface temperature using remote sensing”(Xu et al. 2023 Solar Energy). The data include MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), albedo data, monthly air temperature and precipitation data from TERRACLIMATE, monthly solar radiation data from ERA5 and the Solar Farm(SF) database from Solar Wiki (wiki-solar.org). Please read this document for more details. The codes and datasets can be used freely under the CCY4.0 License. Users should cite the original paper of Xu et al. (2023) and the dataset (DOI: https://doi.org/10.6084/m9.figshare.24152766) when using it.<b>References</b>Xu, Z., Li, Y., Qin, Y., &amp; Bach, E. (2024). A global assessment of the effects of solar farms on albedo, vegetation, and land surface temperature using remote sensing. Solar Energy, 268, 112198. https://doi.org/10.1016/j.solener.2023.112198