Long-term MODIS LST day-time and night-time temperatures, sd and differences at 1 km based on the 2000–2020 time series

Layers include: Land Surface Temperature daytime monthly median value 2000–2017, Land Surface Temperature daytime monthly sd value 2000–2017, Land Surface Temperature daytime monthly day-night difference 2000–2017. Derived using the data.table package and quantile function in R. We derived four standard statistics: (1) lower 2.5% probability (l.025), median (m), upper 97.5% probability (u.975) and standard deviation (sd). Updated long-term values for 2000–2022+ are pending. Includes also long-term trends (trend.logit.ols) which was produced by fitting regression models to de-seasonalized time-series as explained in this <strong>python tutorial</strong>. Basically models are fitted for <strong>each pixel</strong> and the model parameters are saved as images. For more info about the MODIS LST product see: <strong>https://lpdaac.usgs.gov/products/mod11a2v006/</strong>. Antarctica is not included. To access and visualize maps use: OpenLandMap.org If you discover a bug, artifact or inconsistency, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/-/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: clm = theme: climate, lst = variable: land surface temperature, mod11a2.oct.day = determination method: MOD11A2 product, day time values for October, d = median value / sd = standard deviation / u.975 = aggregation/statistics method: 97.5% probability upper quantile, 1km = spatial resolution / block support: 1 km, s0..0cm = vertical reference: land surface, 2000..2017 = time reference: from 2000 to 2017, v1.0 = version number: 1.0,