Before processing tens of thousands of Landsat8 TIRS bands, a script tests the workflow described below, for 74 scenes, that correspond to one WRS2 tile.
The script takes as inputs: <Landsat8Pool> path to directory with Landsat scenes <ScenePattern> regex pattern to match a set of Landsat scene identifiers <LandCover> land cover map <grassdb> path to the GRASS GIS data base <Location> name for the GRASS GIS Location <TargetMapset> name for the GRASS GIS Mapset to host maps to build a time series <WindowSize> an odd integer, parameter for a split-window algorithm (SW) Part 1 of the workflow derives Land Surface Temperature maps by: 1. Creating the target Location 2. Linking pseudo GRASS raster maps to Landsat8 GeoTIFF files 3. Exporting a TGIS-compliant list of maps and timestamps 4. Importing a land cover map required for the SW algorithm 5. Estimating Land Surface Temperature (LST) maps for given scenes (i.landsat8.swlst) 6. Creating a dedicated Mapset for LST maps 7. Copying LST maps in the "LST" Mapset 8. Removing initial LST maps from individual scene Mapsets With a somewhat strong CPU, producing one LST map (7771 rows by 7651 columns = 59455921 cells), takes ~34 minutes. For 74 Landsat8 input scenes, first trials took about 42 hours, running grass-7.3.svn inside a docker container, albeit assigned one CPU. Part 2 concerns building Time Series by: 1. Creating and LST Spatio-Temporal Raster Dara Set (STRDS) 2. Registering LST maps in TGIS' data base 3. Smoothing the LST STRDS via Local Weighted Regression (r.series.lwr) 4. Timestamping Local-Weight-Regression derived maps 5. Creating an STRDS for LWR maps 6. Registering LWR maps in TGIS' data base Part 2 took about 130 minutes including all steps. Obviously, step 3 is practically the consumer. Overall it took about 44 hours to build an LWR Smoothed LST STRDS. After proofing the concept, good use of the cluster concerns steps 2, 5, 7 and 8 (of Part 1). Processes that can/should run in parallel, in an (admittedly heterogeneous) cluster that consists of 912 cores. Final concern is if multi-threading applies to r.series.lwr (step 3 of Part 2). Thank you, Nikos
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