Long-term MODIS LST day-time and night-time temperatures, sd and differences at 1 km based on the 2000–2020 time series (Q6689033)

Layers include: Land Surface Temperature daytime monthly median value 20002017,Land Surface Temperature daytime monthly sd value 20002017,Land Surface Temperature daytime monthly day-night difference 20002017. 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 20002022+ 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 python tutorial. Basically models are fitted for each pixel and the model parameters are saved as images. For more info about the MODIS LST product see: https://lpdaac.usgs.gov/products/mod11a2v006/. 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 creationoption 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/statisticsmethod: 97.5% probabilityupper 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,