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My preference is nationalmap.gov, they even have a new bulk download tool that simplifies the process of downloading all the tiles quite a bit.


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I personally prefer http://datagateway.nrcs.usda.gov/ however the max resolution you can download at one time is statewide and I would assume those will be quite large but it is organized well.


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My favorite source of DEM data is at viewfinderpanoramas.org It has STRM data that has been massaged in various ways. I think that should be good enough resolution for what you require.


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If you happen to use QGIS, install the Raster Interpolation plugin, which lets you to extract DEM elevation data and assign it to point layers. Since I think you deal with polygons, you could first generate centroids* (or a representative point for each polygon) for those polygons and use the points to pick elevation data from the DEM. Finally, join your ...


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If you go to the Earth Explorer web site you can download several DEMs. For Nepal they have the 30m AsterGDEM and the 90m Void Filled SRTM. The 1 arc second (30m) SRTM is not available yet (12/12/2014) but I believe it should be ready in the near future


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Theres SRTM data available. See https://en.wikipedia.org/wiki/Shuttle_Radar_Topography_Mission for more information. Note that SRTM hat a ground resolution of approx. 30 or 90 meters ( 1 and 3 arc-seconds, respectively). That is probably the highest-resolution free dataset available. For more detailed DEMs you should contact local Nepali ...


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This code can be used to create a "Hill slope" DEM of just about any number of rows and columns: # Building a fake hillslope # hisllop is 5 rows by 6 columns x <- seq(-15, 15, by=0.01) z <- 1/(1+1.5^-x) plot(z) z <- 150 - (1-z)*5 plot(z) # Doing it by hand - DELETE if needed - JUST HERE AS AN EXAMPLE!!! elev <- c(mean(z[0:500]), ...


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1) Since version 1.10, you can use ogr2ogr (GDAL) to agjust/"georeference" a shapefile with control points or GCPs (as Spatial adjustment in ArcGIS, look at How to georeference a vector layer with control points? or Add ability to transform vectors based on GCPs in ogr2ogr) Example ogr2ogr -gcp 5 -135 0 0 \ -gcp 283 -135 1000 0 \ -gcp 5 278 0 ...


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I can't comment so I'll answer with how I would approach this in ArcMap. Perhaps you could make a similar workflow. Use the extract by mask tool on your DEM with your road lines as the mask. You now have a raster version of the roads with their elevations. Use the slope tool on that to calculate the slopes along your road raster. I did a quick try on ...


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As I messed this up in the comments and cannot edit it now, I'll try again here. You have two options: Split your roads no finer than the resolution of your DEM. As it is now, you have multiple samples (10m apart) for a single pixel (30m x 30m). The more samples per pixel, the greater the relative jump between pixels. Take 2 pixels, 30m x 30m, 1m height ...


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The problem is due to the presence of non-ascii characters in the path of the output file, so you just change the path name to something else that contains ordinary characters (e.g. UTF-8) and try again.


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I am late here, but this question was my entry into the forum as I was researching the same question. I think that the original poster may want to calculate for each cell the height above the first stream cell that would be reached by water flowing from the cell. So the 'nearest stream' is calculated along the downslope flow path, not euclidian distance. ...


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That's a two step process rasterize the building layer to create a raster with the building height information use field calculator to sum up the DEM and building height Note that the two rasters have to be in the same CRS before you can add them up in the field calculator.


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The way I have done this in the past is to convert buildings, forested areas, etc. to a raster (rasterize the polygon using the height column for the raster value, using the same pixel resolution as the DEM). Then merge the two rasters (DEM and rasterized buildings). This will add the building height to the DEM. One thing to note is that you will probably ...


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You can use the Con (Spatial Analyst) tool to calculate the area of specified elevation values. In this example, I stated that I wanted all elevation values of a floating point DEM > 400 = 1, else = 0. The black and yellow image is the result (Figure 1). Then, simply open the attribute table and look at the count next to the Value = 1 row (Figure 2). ...


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If your elevation raster is integer, Build Raster Attribute Table. Then, select the rows in the table of interest, and look at the Statistics for the Count field (right-click 'Count' -> Statistics). The SUM value is the number of pixels selected. Multiply this value by the area of one pixel (raster layer properties -> Source tab -> cell size). Repeat with no ...


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In newer QGIS versions (I tested it only in QGIS 2.6) you can set the resolution when you save a raster via "save as" (quite similiar with ArcMap)


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Actually, it is not granted that you will be able to recover some information from the shadowed areas. However, I once dealt successfully with (cloud) shadows in a hyperspectral image. The aim was simple land cover classification. Here's what I did. I'm not sure how this would work with Landsat images, but since it is very simple you should give it a try. ...


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I believe this code solves the problem, although it is a bit ugly. It creates a binary raster with 1 values for each null cell in my HAND raster. I then used a cursor to retrieve the count field for the binary raster's table and compare that to the count from the previous iteration in a while loop. The loop ends when the count stops changing (it may be that ...


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ArcGIS for Maritime: Bathymetry is a new component of the ArcGIS for Maritime platform available with the ArcGIS 10.1 for Desktop release. The software is developed for management and analysis of bathymetric data. Digital Coast is an excellent resource for such data. Not only is digital coast an excellent data resource it is also an excellent training ...


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This is actually an exceedingly complex problem and not one that you're likely going to be able to solve using conventional ArcGIS tools. To do this, you'll need to develop for each depression in your landscape the relation between depth and volume, i.e. the depth vs volume curve, which will be uniquely defined for each depression based on it's form. To ...


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3D is not (yet) implemented in QGIS, but you can store the height in an attribute table field and create a 3D output manually with ogr2ogr -z_field fieldname outside QGIS. See Is it possible to create 3D dxf with OGR? for an example. This is rather 2.5D, because all vertices of a line must have the same elevation (as contours have). In QGIS, you could use ...


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Design a flat raster surface for each height then run the Cut Fill tool. This will also give you volumes if needed. The Cut Fill tool summarizes the areas and volumes of change from a cut-and-fill operation. By taking surfaces of a given location at two different time periods, it identifies regions of surface material removal, surface material ...



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