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0

The Raster -> Terrain Analysis menu entry is from the core Raster Terrain Analysis plugin, which is installed by default. You can deactivate it in the plugin installer. It is described here: http://docs.qgis.org/2.0/en/docs/user_manual/plugins/plugins_raster_terrain.html and a short tutorial is here: ...


0

Slope is rise / run. Compute rise and compute run and you have your answer. It is simple to compute the distance between geographic coordinates. This will introduce less resampling error as compared to conversion to UTM, etc.


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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 ...


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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 ...


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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. ...


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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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Apparently Rasterlite 1.1g version (released on 2013-05-05) (https://www.gaia-gis.it/fossil/librasterlite/index) is no longer maintained. This version cannot handle with the example above, it has not been implemented. Fortunately, Rasterlite2 version 1.0.0-rc0 (released on 2014-07-30) is much more powerful and can handle Int16 DEM GeoTiff images with ...


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"No enhancement" means that the colour range is from 0 to infinity (or 32768, depending on the datatype). QGIS usually scales between 2% and 98%, which might lead to an almost unicoloured rendering, when your data is within the first 2%.


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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 ...


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, ...


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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. ...


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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 ...


0

If you don't want/have a server side map rendering engine, I'd convert the image to a tileset with a convenient palette. For example you can use gdal2tiles.py script but it needs as a source an image with the palette applied so your source wouldn't be a DEM but a regular RGB image (height values have to be mapped to colors). This step can be done with ...


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: ...


1

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


0

Your problem is completely unrelated to your question's title. The JS interpreter doesn't even reach the line where you add the image layer because of an earlier "Uncaught TypeError: Cannot read property 'proj' of null" exception in the following line: var extent = new OpenLayers.Bounds(16120,2409591,484824,2814500).transform(inProj,outProj) This is ...


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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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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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You can do this using GRASS, providing your DEMs are integer (a restrictive limitation). You need the r.statistics tool and also r.mapcalc (for RMSE).


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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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Yes you can however; if you resample from smaller cell size to a larger cell size can result in the loss of data. If you resample from larger cell size to a smaller does not increase the resolution, it just creates more cells.


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Try both and compare. Either will be a compromise on your higher resolution dataset. Hence, there is not 'proper' solution. Just be sure to detail the process you undertook so your work is repeatable.



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