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This does seem to be related an existing QGIS bug report http://hub.qgis.org/issues/4304 You could try using gdalinfo to find the list of supported formats like: gdalinfo --formats Which on this PC gives me: Supported Formats: VRT (rw+v): Virtual Raster GTiff (rw+vs): GeoTIFF NITF (rw+vs): National Imagery Transmission Format RPFTOC (rovs): ...


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Not sure if this will suffice but; If you have 3D analyst you can interpolate your temperature raster independently then drape it over the DEM and visualize in 3D in ArcScene. This way you could analyze the heat data in relation to elevation. Alternatively, you could generate a hillshade raster from your DEM and either overlay the hillshade model over your ...


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This is how I would do it: Convert your line to a raster (Polyline to Raster) Convert the raster to points (Raster to Point) Add Z value from the raster to the points (Extract Values to Points). A new field named RASTERVALU with the raster Z value is added. Turn the points into a feature layer and select the point with the minimum Z field value using for ...


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I am slowly working on a gdal app that calculates viewshed with an eye on performance. It is still in development, and no where near done, but it may be useful. It'd actually be nice to have some input, as I just did it for fun. You can find it on my github account(see below). The nearest neighbor sampling is pretty much a joke, but it's fast. Linear is ...


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You could drape your geological polygons on the elevation surface you created to make them 3D. Two ways in 3D Analyst are Interpolate Shape and Add Surface Information. For an explanation of both see: http://resources.arcgis.com/en/help/main/10.1/index.html#//00q80000005m000000


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Here is a good one (one of the authors is a regular user on GIS SE). Evans, Jeffrey S.; Hudak, Andrew T. 2007. A multiscale curvature algorithm for classifying discrete return LiDAR in forested environments. IEEE Transactions on Geoscience and Remote Sensing. 45(4): 1029-1038. Look on Table II (page 1034). The authors used lidar ground returns ...


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Be wary of stating, out the gate, that something is producing "wrong" results. The phenomena of slope percent approaching infinity as slope degrees approach 90 is well known. You could just truncate slopes > 100 == 100. ESRI actually provides a very nice description on how slope is calculated. You could try the calculation in degrees to make sure that ...


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I had to do something rather like this for my masters thesis, but with much fewer observer and target points. I'm not aware of a reasonable way to create a complete raster of "visible area," at least not one that wouldn't take a long time. Repeatedly running Viewshed, once for each centroid of the raster's cells, would certainly work... but as you've, ...


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I would use this approach: Add flood deep to DTM to create a new surface raster (use Plus (3D Analyst) tool). Drape the flood raster to the new surface.


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You need to use the DTM as the base height for your flood depth raster and calculate a new height by adding the flood depths raster value to the dtm base height as a vertical offset. bearing in mind that water is flat (waves aside), you could also use a flat plane and calculate the flood limits as a height above sea level and set the height of the plane ...


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This is a very common error when using ArcHydro, although the exact text and in which function it appears might differ slightly. You should check out the answer and comments in this question. But in short, what is most likely to solve your problem is to store all data and your project on C:/ instead of a network drive.


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My solution, based on the one from @wwnick reads the raster dimensions from the file itself, and covers the whole image by making the edge tiles smaller if needed: import os, sys from osgeo import gdal dset = gdal.Open(sys.argv[1]) width = dset.RasterXSize height = dset.RasterYSize print width, 'x', height tilesize = 5000 for i in range(0, width, ...


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In ArcGIS you can use the Viewshed tool (Spatial Analyst Tools > Surface). The Viewshed lets you calculate the surface locations visible to a set of points or lines (see the documentation).


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Usually terrain models derived from remote sensors will have their initial accuracy evaluated using blind control methods. For example with LIDAR, the remotely sensed measurements are often compared to survey-grade control points (the blind control) taken on the ground in various land covers (woods, open areas, etc) to assess the penetration and accuracy of ...


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Some literature on this topic: COLOSIMO, G., CRESPI, M., DE VENDICTIS, L., JACOBSEN, K. (2009). Accuracy evaluation of SRTM and ASTER DSMs. In Proceedings of the 29th EARSeL Symposium, Chania, Greece. GOROKHOVICH, Y., & VOUSTIANIOUK, A. (2006). Accuracy assessment of the processed SRTM-based elevation data by CGIAR using field data ...



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