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6

Each of the outputs that you described (slope, aspect, and curvature) are terrain attributes that are naturally described as rational numbers. As such, you would expect that the outputs of these tools would be floating point rasters even if the input DEM uses integer level data to characterize elevations. And no, it does not corrupt your analysis. The only ...


4

The question (as clarified in a comment) asks how to remove local slope to calculate relative ruggedness. There is a simple way to do this. It relies on computing the slope using the same local data as the ruggedness (which usually is a 3 by 3 square neighborhood). I recall verifying that ArcGIS computes slope (s) and aspect in exactly this manner: ...


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Depending on your image type you can use Esri Raster Mosaic dataset - have your tiles and mosaic too without any (much) extra storage. The mosaic dataset works like a VRT file where the rasters are referenced but not imported so the table in the database stores the path and location of the tiles; overviews are a good idea but they don't take up much space. ...


3

DEMs and Hillshades are two different things. DEMs are surfaces with elevation information. Hillshades are a visual representation of a shaded relief and the values are not dependent on the elevation itself but of the aspect and angle illumination, as you noticed from 0 to 254. If you'd like to represent a map with elevation data but using the visualization ...


2

If you're comfortable building software from source and are on a Unix flavor or OSX, you can go from .las to DEM using PDAL and points2grid. If you're on Windows, I have no idea if you'll be able to get points2grid to build, but you could try. Both PDAL and points2grid have C++ APIs that you could integrate into your own C++ application. You can also use ...


1

This is what the ArcGIS help says about How Slope Works: If there is a cell location in the neighborhood with a NoData z-value, the z-value of the center cell will be assigned to the location. At the edge of the raster, at least three cells (outside the raster's extent) will contain NoData as their z-values. These cells will be assigned the center ...


1

I've done some work of this manner. Archaeologists love their giant DEMs for some reason... I don't have anything formal but can lend some insight from experience. I found it was nice to have something that covered the whole area but it doesn't need to be at the highest resolution you've got. For example, a mosaic of the DEMs for the whole area at 1/3 ...


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DEM = digital elevation model DTM = digital terrain (topography?) model DSM = digital surface model Sort of the same thing - distinctions can be made if considering just terrain or also objects on that terrain. See What is the difference between DEM, DSM and DTM? As for Grid Format, as mkennedy says, my guess would be the native raster format Esri uses. ...


1

The units of the graph and how to change them depend on which axis you're looking at. First, the horizontal units are the same as your current map projection. If you are using a Geographic coordinate system, the units will be degrees. If you're using a standard UTM projection, the units will be meters. The only way to change this use a different projection, ...


1

Use ogrinfo as a handy debugging tool. I see: $ ogrinfo OLEX-LAT-190952014.vrt INFO: Open of `OLEX-LAT-190952014.vrt' using driver `VRT' successful. 1: layer0ERROR 1: Failed to find layer 'layer0' on datasource 'OLEX-LAT-190952014.short.csv'. (Point) According to the documentation, SrcLayer is optional, but should be defined (unless in SrcSQL). Add ...


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The problem is solved using the good gdal commands: gdalwarp -ot Int16 -s_srs "EPSG:2154" -t_srs "EPSG:4326" -dstnodata -32762 -r cubicspline -multi -co "TILED=YES" -co "COMPRESS=DEFLATE" -co "ZLEVEL=6" *.asc outFolder/gray.tif gdal_retile.py -v -r bilinear -levels 3 -ps 2048 2048 -ot Int16 -co "TILED=YES" -co "COMPRESS=DEFLATE" -co "ZLEVEL=6" -targetDir ...


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I calculated the rmse by importing the excel sheet in matlab...thank you all,I'm still on the process by adapting new procedures.


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You can do this in R. Here's a script that reads in your DEMs, calculates your stats, plots your results and then writes to csv (if you really want to plot in a spreadsheet). Remember to add your own file locations and you may need to tweak the RMSE, I didn't check that. install.packages("raster") install.packages("e1071") library(raster) library(e1071) # ...



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