Hi, I am trying to (re-) organize some of our climate data based on continuously updated daily time series in the TGRASS framework which I plan to update in chron-jobs.
My question is, is there a recommended approach for updating existing (aggregated) time series. I see mainly two different scenarios, 1) new maps may be added at the end of (aggregated) time series (e.g. monthly temperature for new month aggregated from daily temperature raster) and 2) existing maps may be replaced for datasets which have been modified (e.g. updated MODIS tiles) after a time series has been created. Am I right that 1) would require a) to simply to register new raw data (e.g. new days with temperature data) while I b) would have to create a temporary time series which I use for aggregating, for so being able to register the new aggregated maps to the monthly time series? In order to avoid naming conflicts I would also have to use temporary names, which I then can rename according to target series, since new maps created with t.rast.aggregate will start with 0 again? Btw. is there a possibility to use e.g. start dates instead of the sequence 0,1,2 ... (this would also make map names more intuitive)? In any case I would like to avoid to update many years when I get new data only for a few new month or weeks. So I am grateful for any hint in this direction. For 2) changes can happen across the entire time series and for single time periods (single days or weeks). In this case I would have to unregister outdated maps first and then proceed like in 2. Only that - for aggregated time series - I would have to do so for every time period of a space time data set which contains underlying modified data, right? I hope my problem / aim is understandable and my approach is to some degree reasonable. However, I wished there was a more elegant / efficient solution for that? Thanks in advance. Stefan _______________________________________________ grass-user mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-user
