Nationwide geospatial dataset of environmental covariates at 1km resolution in Mexico (2015-2020)

<p><strong>Package of 39 covariates, a combination of topographic, climatic, and vegetation derived variables with pixel sizes of 1000 m for the period of 2015&nbsp;to 2020&nbsp;from google earth engine (GEE) to assemble a nationwide geospatial dataset of Mexico.</strong><br> <strong>Datasets included WorldClim V1; a set of bioclimatic variables derived from the monthly temperature and rainfall&nbsp;<a href="https://www.zotero.org/google-docs/?tmZL4M">(Hijmans, 2005)</a>; time-series analysis of Landsat images from the Hansen Global Forest Change v1.8 (2000-2020) dataset&nbsp;<a href="https://www.zotero.org/google-docs/?jGj5Rn">(Hansen et al., 2013)</a>; 4-day composite dataset from Moderate Resolution Imaging Spectro-radiometer (MODIS) sensors with fraction of photosynthetic active radiation and leaf area index at 500-m resolution&nbsp;<a href="https://www.zotero.org/google-docs/?t45qy3">(Myneni,&nbsp; Ranga et al., 2015)</a>&nbsp;and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Emissivity Database (2000-2008)&nbsp;<a href="https://www.zotero.org/google-docs/?8bVVc9">(Hulley et al., 2009, 2012, 2015; Hulley &amp; Hook, 2008, 2009, 2011; NASA JPL, 2014)</a>. All covariates were resampled to 1000 m. The resampling was done with conventional bilinear interpolation as implemented in GEE.</strong></p>