# Tag Info

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NASADEM is a full reprocessing of the SRTM data using state-of-the-art interferometric processing techniques. It also improves accuracy, reduce gaps and improve the quality of the data used to fill gaps (using GDEM v3). More details are described here. The final version is not ready yet, but a provisional version has been released (not officially) and can ...

20

The answer is not as simple as the question may imply. If we had one "best one" we would not need the others, we would just use the best. Horses for courses though, needs matter. Saying that. This blog gives an excellent comparison of 90 m SRTM and 30m ASTER with some reasonable statistics. The winner is... well, actually you have no winner but 90m SRTM ...

16

With Python, you can access raster statistics using the Python GDAL/OGR API. from osgeo import gdal # open raster and choose band to find min, max raster = r'C:\path\to\your\geotiff.tif' gtif = gdal.Open(raster) srcband = gtif.GetRasterBand(1) # Get raster statistics stats = srcband.GetStatistics(True, True) # Print the min, max, mean, stdev based on ...

15

There is a new, 30 meters resolution SRTM DTM coming out. As stated on the NASA JPL official page, The next release is planned for later in 2014, and it is expected to include all of South America plus North America south of the United States. It is incomplete, for now, it has only limited coverage. You can read an article about SRTM coverages here (it'...

14

With bash alone, you can use : gdalinfo -mm input.tif It returns a range of infos within which is the string Computed Min/Max=-425.000,8771.000, for my Eurasian raster. Some cleanup and you get your vertical min/max variables: $zMin=gdalinfo -mm ./input.tif | sed -ne 's/.*Computed Min\/Max=//p'| tr -d ' ' | cut -d "," -f 1 | cut -d . -f 1$zMax=`...

14

To smooth your contours it is the best way to smooth your DEM first. Here are some useful information: What raster smoothing/generalization tools are available? I'm using SAGA GIS for this task. Using SAGA GIS Version 6.2.0 directly: Grid > Filter > Gaussian Filter Or use the QGIS Processing Toolbox and search for gaussian. Warning: Using QGIS 2.18....

14

SRTM tiles (3601 px * 3601 px in this case) have 1-pixel overlaps in between. When you apply transparency (or reduced opacity) to your hillshade layer, such overlapping pixels stand out. You may have observed this also on the original images, if you apply transparency (see below). ..... original SRTM, Pseudo-color + 60% opacity Anyway, you can avoid ...

8

Given your crop.tif raster layer, you can filter its pixels whose elevation is above the threshold (50 m) using gdal_calc.py: gdal_calc.py -A crop.tif --outfile=result.tif --calc="A>=50" --NoDataValue=0 The result.tif will be made of 1 where the condition is satisfied, 0 otherwise. Then, it will be possible to vectorize result.tif using gdal_polygonize....

8

SRTM (Shuttle Radar Topography Mission) was a shuttle mission, no satellite involved. But essentially the satellites do not cross the poles. In a sun-synchronous orbit, which most imaging satellites are in, you get a pattern like: This is great because it means that the orbit can be timed and most parts of the Earth get covered at around noon, getting good ...

8

I answered a similar question here You can download and clip a portion of the SRTM 30m DEM with one command with the elevation Python command line tool. Install it and perform the self check with: $pip install elevation Check if you have all the dependencies installed (mainly GDAL tools):$ eio selfcheck Download and clip a ...

8

The resampling method 'near' or 'nearest' is generally to be considered only for succinct/classified data, it attempts to assign a cell value based on the closest source pixel: This is most commonly integer (int8, int32, int64) types but can be of type float (float32, float64) where each cell represnts classified values and generally values appear more than ...

7

You can download and clip a portion of the SRTM 30m DEM with one command with the elevation Python command line tool. Install it and perform the self check with: $pip install elevation Check if you have all the dependencies installed (mainly GDAL tools):$ eio selfcheck Download and clip a portion of the SRTM 30m DEM giving bounding box as WGS84 ...

7

A few thoughts: A previous answer correctly recommends resampling during display to smooth out the irregularities in the hillshade. This is primarily used for cartographic effect when you are finishing a map. Use the Image Analysis window to run a 5x5 smoothing window over the image Find better elevation data. 10 m NED Data is available for the ...

7

In a nutshell, the ESRI ASCII grid format is human-readable and is text. This means you can open it in a text editor and see the actual values for yourself without needing specialized software. TIFFs are binary and are therefore not human-readable. You'd need some specialized software like GIS to read it. TIFFs are supported by almost all GIS packages though....

7

This is a fairly common problem to run into. My guess is that your SRTM data are still in geographical coordinates and has not been reprojected. As such, the elevation units are being measured in metres while the xy-units are in degrees. You need to use the z-conversion factor to convert the xy-units and z-units so that they are the same. The common approach ...

7

This is by no means an answer to your specific problem but an explanation of elevation data and vertical accuracy. Also, this all wouldn't fit in a comment. Only a select number (depending of area of lidar coverage) of elevation control points are used when checking the vertical accuracy of lidar data. I wouldn't expect all elevation markers to match ...

7

You need to extract the slope first from the DEM using the Raster -> Terrain Analysis -> Slope OR Raster -> Analysis -> DEM (Terrain Models). Then use the slope raster to extract the lakes or sea where the slope = 0 Using Raster Calculator, it will be like this: "Slope@1" = 0 Where "Slope@1" is the raster name. So The general form is "...

6

GDAL can read/write these raster formats with the SRTMHGT driver. This means you can view the raster with QGIS, ArcGIS, or use GDAL utilities like gdallocationinfo to get values from a point, e.g.: Convert DMS to DD: Lat: 50°24'58.888"N = 50 + (24 / 60) + (58.888 / 3600) = 50.4163577778 Long: 14°55'11.377"E = 14 + (55 / 60) + (11.377 / 3600) = 14....

6

Chris, Your confusion stems from the distinction between the image represented by image 1 (a true color image) and the DEM you downloaded. The two are very different things and this distinction is one of the very great things about raster analysis in geospatial science! Image 1 is a high-resolution true color satellite image or aerial photograph such as ...

6

I have tested the plugin and it is working fine in my machine. One common way to download (SRTM among other) data is searching it in Earth Explorer site. All the information about how to use the site is in their Help page. If you want to download just that image, you can do it from the Download link provided in the following page: https://...

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If the stats have already been calculated: gdalinfo input.tif If they haven't been calculated yet, do: gdal_translate -stats input.tif output.tif gdalinfo output.tif

5

I have a tremendous respect for GRASS and the r.tarraflow algorithm and I'm sure that given enough effort, you would be able to make it work for this application. But as an alternative, I develop a cross-platform free and open-source GIS called Whitebox Geospatial Analysis Tools (download here). Here is an example for how to use it for hydrological ...

5

SRTM data are distributed in a few common formats including *.hgt files, the DTED format, and the more common *.tif file format. Both of these are raster formats and the elevation values are stored directly in each pixel of the raster grid. You see the 'Z' value in the image below that displays as you move your cursor across the image. Each pixel contains an ...

5

Here was my problem: No way the SRTM data is that messed up. The SRTM data IS that messed up. The warping above is actually in the DEMs in the SRTM3 dataset (downloaded from http://dds.cr.usgs.gov). After examining DEMs from the improved SRTM4 dataset (available here) I found that most of these "gaps" were filled by interpolation but other issues (...

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You might try the USGS SRTM FTP site. I can assure you that each of the tiles you list as examples are there in their proper .hgt format and there are no suspicious files in the associated zip file. And here is the tile S35E147, buffered with the surrounding eight tiles as well:

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In the text there is basically an error in that there should be another sub heading between the SRTM data download section and the imagery download section. We provide a methodology for obtaining SRTM data, but you are left to your own initiative to find local imagery data. I will update the text to address this.

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Now, the answer from the developers of the tool, who kindly allowed me to forward the answer here. I translate and do my best to reproduce what I learnt from Dr. Conrad: The only expected input-dataset is the DEM. The tool runs an interative procedure which works with relative relief-position. The same procedure is used to calculate - the vertical distance ...

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As "@user two seven two three nine" says, it depends on what you are trying to do. For the geosciences, there are a number of relevant papers in "Elevation Models for Geoscience", Geological Society of London Special Publication 345. A direct comparison can be found in: Crippen RE, Global topographical exploration and analysis with the SRTM and ASTER ...

4

I suppose that it is the result of r.shaded.relief. Have you set the correct resolution of your region of work (resolution of the SRTM layer, Res: 59.74514451 here) ? Resolution of the SRTM layer: Resolution of the region: Elevation; r.shaded.relief without grainy surface with the correct resolution

4

I recently wrote an SRTM download tool that works from the free and open-source GIS, Whitebox Geospatial Analysis Tools (which can be downloaded here). The user simply specifies the range of lat/long values for their area of interest and the tool will download all of the .hgt tiles from the FTP site, mosaic the tiles into one seamless raster, and then fill ...

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