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Tom Patterson, the lead cartographer at the U.S. National Parks Service has some excellent tutorials on working with DEM data to make beautiful shaded reliefs. Park of his workflow involves using Natural Scene Designer and Adobe Photoshop. For my own workflow I like to use GDAL to resample the size of the DEM before rendering a shaded relief. This often ...


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You can create a DEM with higher resolution than the original one, just like with any other raster data. The question is, if you really get better informations from those interpolated values. I often do this for "cosmetic" reasons only, e.g. for obtaining a nicer hillshade layer with a less "blocky" appearance in the map. Load your DEM In the layer ...


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This answer comes with a hefty health warning as you are essentially faking an improvement of resolution. There are a few approaches you could use to fake 10m DEM out of a 30m original. Here's a couple: You could simply use the raster calculator and set the resolution. This is the simplest and crudest approach but possibly the most honest. Essentially ...


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If you understand the limitations of interpolation of your input DEM there are a number of ways you can do this in QGIS. One is with gdalwarp: Raster -> Projections -> Warp Resize it by multiplying Width and Height with 3 to convert 30m to 10m cells. The choice of resampling method will have a huge impact on your result. The most used algorithm for DEMs ...


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Technically not. 30 m is the resolution of the DEM that you have and you cannot derive a higher resolution (10m DEM) DEM from that. Inversely, you can derive a 30m DEM from a 10m DEM.


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if you want the software that focus on generate high resolution DEM files, follow this a few guidelines. there is two scenario you can focus on it; if you want more high resolution DEM from 0.5m to 10m you can using stereo imagery or photogrammetry process by using specialized software like (Socet Set / Socet GXP) LPS for ERDAS with commercial satellite ...


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Update Satellite imagery Digital Elevation model ( DEM ) generic term for altitude grid Digital Terrain Model ( DTM ) ground elevation model Digital Surface Model ( DSM ) ground + cover elevation model Digital Height Model ( DHM ) cover elevation model


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Contour interval is a single number that defines the number of vertical units between contours. You can't have 10, 5, 2 unless you have different sets of contours. If it's 5, each line represents 5 vertical feet of change between lines. You can of course highlight 10m contours on an interval of 2 (every fifth) or 5 (every other). Contour lines are an ...


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First forget about QGIS when playing with 3D, QGIS is not really there yet. If extracting vertices is enough or the lines are isolines (contours - constant elevation) then it is possible to use approach with free tools as explained here: How to import a 3D DXF file into QGIS with z information as attribute value? The problem is when the lines in DXF have ...


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A tool that can do this (among others) is the Sky-View Factor Based Visualization (http://iaps.zrc-sazu.si/en/svf#v). Calculate several parameters of a terrain. Is damn good.


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For any surface analysis involving hydrology, TopoToRaster is preferred over TIN as it has Drainage Enforcement. As @Martin noted, 5m contour interval is unlikely to be dense enough to create or track sub-meter features. That said the vertical contour interval is less important than the distance between contours in X,Y dimension. The general guideline for ...


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The Hillshade tool inherits cell sizes from the raster layer it is based on. If you are able to recreate this DEM using a smaller cell size, the resulting hillshade should also have smaller cells.


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In QGIS you can use the Interpolation plugin (I think it is installed by default, if not it is a standard plugin installed through Plugin Manager) found in Raster -> Interpolation. With that plugin you can take your vector layer of points and turn them into either a TIN or a surface model. You can either pull the elevation from a field in an attribute ...


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gdal + convert based workflow There is a gdal + convert solution which gives good visual results. The trouble with this solution is that convert destroys geographic informations which you then have to restore. It increase the number of action to run. # Basic crop gdal_translate -projwin 67 35.92 99 5 ../data/noaa/ETOPO1_Ice_g_geotiff.tif crop_xl.tmp.tif # ...


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Currently SCIMAP does work directly with QGIS. You can do the calculations within SAGA-GIS using the version available on www.scimap.org.uk and then export the grids and shapefiles from there to QGIS to analysis and cartographic presentation.


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Another source for google may be Zonum. Here you can generate points with elevation data and then generate interpolated surface. For USA you may try National Map Viewer If you want to develop google api app yourself just modify the following file with your Google Map Api Key see image -- and save the file as html and open in browser that's all. ...


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For my case (hillshade and my computer), I had to use --calc="(A/3+B/3+C/3)" to get a correct average results. (A+B+C)/3 fails because gdal_calc limit the equation to a [0-255] range. (A+B+C)/3 will first calculate A+B+C modulo 256, then divide this value (in range [0-255]) by 3, giving a low value and dark output. For more on gdal_calc operators, see ...


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Gdal_calc's numpy seems to have more operators : + addition - subtraction / division * multiplication = equals to < less than > larger than ! not equal to ? if clause M maximum of two values m minimum of two values B bit level operator I haven't found clear and proper examples for how the exotic operators should be used. If you have ...


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This are the settings of my vector layer: g.region -p vector=CT_ISOBATAS_5m_ETRS89@froga projection: 1 (UTM) zone: 30 datum: etrs89 ellipsoid: grs80 north: 4818925.16988824 south: 4791485.92527958 west: 486512.5000001 east: 601274.08203047 nsres: 1.00011826 ewres: 1.00010965 rows: ...


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What are your region settings? I tried this set of commands, and succeeded to create a DEM with negative values, with no problems: # Set region to low resoution GRASS 7.0.0 (ITM):~ > g.region -p res=5 # The contour vector GRASS 7.0.0 (ITM):~ > v.db.select test_ctours cat|elev 1|-100 2|-80 3|-60 4|-40 5|-20 # Create rasterized contours GRASS 7.0.0 ...


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The linked source mention "change its fusion mode to < Multiply >", so the operation to do is not a simple average of input hillshades (for this, see also How to average gdal_hillshades?). It's something else. Yet, let's create the 3 different-sunlight-directions hillshades : gdaldem hillshade input.tif hillshades_A.tmp.tif -s 111120 -z 5 -az 315 -alt 60 ...


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Using the Contour plugin. Generate isolines and/or filled contours a set of data points.


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There are many possible solutions, but a convenient and accessible way will be to use an appropriate projection. What properties must it have? It should be conformal (or very nearly so throughout the region of interest). This means there is no relative scale distortion as the bearing is varied around any fixed point but--necessarily--there will be ...


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The Google Elevation API is not accurate enough at a Building level. You can test it out by using going to http://www.daftlogic.com/sandbox-google-maps-find-altitude.htm Just search for 1 World Trade Center, New York, NY 10007 and then click around, and you'll see that the heights that you get aren't really for the top of a building


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Alternatively, a DEM with global coverage that might suit you is the SRTM 1 second DEM. This was recently released and has a resolution of about 30 metres. Read about it at http://www2.jpl.nasa.gov/srtm/ and download load it (free) at http://earthexplorer.usgs.gov/.


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Assuming you have created surfaces from your surveys; this is a simple cut and fill operation, however you will need either a Spatial Analyst or the 3D Analyst extension to do this. (Calculates the volume change between two surfaces.) I beleive out of the 2 extensions, Spatial Analyst is pretty much essential however the 3D analyst will allow you to also ...


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Nutshell Each set of 3 images below should be read such as "grey (band) + opacity (band) = transparent result". You can test these processes within minutes via the associated github hosted makefile. Process #3 is the one which I recommend, with a threshold between 170 (keeps strong shadows) and 220 (keeps all shadows). Process 3 provides the strongest ...


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I can think of two options. Mosaic the two rasters to a new raster dataset, using the Mosaic to New Raster tool or the Workspace to Raster Dataset tool. If you do, you need to choose a single cell size, which means you'll be downsampling the 5-meter DEM or upsampling the 30-meter DEM. (You should add some metadata to the mosaicked raster to explain what ...


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You wanna, huh? I would point out that, if your terrain dips below sea-level, negative values do represent real elevation values. You did not state if you wanted to set these values to a uniform value (eg., 0) or to NoData. Removing data is different than recoding it. This can easily be accomplished in the raster calculator using a Con or SetNull. To set ...


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This is an alternative using the function cut to assign elevation values into classes of elevation, making possible to discretize colors in the map (color per class of elevation). #Generate reproducible example library(raster) f = system.file("external/test.grd", package="raster") #path to raster file DEM = raster(f) #import raster file DEM = ...


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You can use the reclassify function in the raster package to reclassify the DEM. The general idea is to generate a reclass matrix which provides the instructions on how to reclassify the continuous DEM elevation values. require(rgdal) require(raster) # Read DEM and convert to raster layer object dem = raster("C:/temp/dem.tif") # Generate a reclass ...


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I guess that your fish fence polygon covers several DEM grid cells. Normally you would extract DEM grid values to a point layer with a plugin tool like Point sampling tool. If you polygons are very small in relation to the DEM cells you could use the centroid of the polygon as a new point layer doing the Point sampling plugin tool on that point layer. With ...


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My advice is that you specify the output location. Something like this: output = "C:\yourfolder\yourgdb.gdb\DEM_park" Because it is not clear to me where is your DEM going, check your environment settings. EDIT: Oh, I see it now. You created a tif. GDB's cannot store tif format rasters, so of course it is not there at the default gdb. Then your output ...



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