Re: [GRASS-user] Basin DEM advice needed

[Micha Silver]

Hi Rich A couple of thoughts, below On 03/10/2019 01:22, Rich Shepard wrote: Attached are two maps using 1m LiDAR data. The annotated map, basin-elevations.png, was drawn by individually applying d.rast to each of the 70 maps covering the basin. Sharp breaks can be seen where the data cross quads or flights didn't match up smoothly. Can you first zoom in closely to one of the discontinuity areas between two tiles and examine the actual values on both sides of the "break". As Ken pointed out, it might be just a coloring problem, and NOT really a discontinuous step in elevation values. The un-annotated map, nehalem-dem-patched.png, displays the results of running r.patch on all 70 maps. Topographically it's quite different from the individual maps; almost flat when the north, east, and south edges should have elevations similar to the other map. I think I should apply r.resamp.stats to aggregate the 1m resolution to 5m. I'd like your thoughts on this. I would NOT use resampling to try to overcome discontinuity in the tiles. That won't solve the problem, just smear it out a bit. If there really are breaks in the data, then (you won't like this...) back to the data provider to clarify why there are these breaks in elevation. If the region is too large to keep data at 1 m, then you can decide to down-sample to a lower resolution to make the data more manageable. Also, if there are sliver gaps between the tiles, then you'll want to run r.fill.nulls to get these gaps filled by interpolation. In order to save time, I suggest to recursively set the region to a very small area surrounding each gap, run the r.fill.nulls and patch the filled area back into the original. Then move on to the next gap. This will be much faster than trying to do r.fill.nulls on the whole region. When finished, don't forget to go back to the full region. I assume that I should resample each individual map, then re-run r.patch on the coarser maps because r.slope.aspect and r.info need a single map as input. Would this be an appropriate process? I'm completely open to all suggestions and recommendations. I think the best approach would be creating a VRT, outside of GRASS, using the gdalbuildvrt utility: Dump the list of your 70 rasters into a text file. Use the -input_file_list parameter to gdalbuildvrt, and you'll have one virtual raster for import into GRASS. You can reference it with r.external (to avoid importing and duplicating the disk space required). Then do whatever hydrological analysis you need with that. Best, Micha Regards, Rich _______________________________________________ grass-user mailing list grass-user@lists.osgeo.org https://lists.osgeo.org/mailman/listinfo/grass-user -- Micha Silver Ben Gurion Univ. Sde Boker, Remote Sensing Lab +972-523-665918

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