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103 lines
4.3 KiB
103 lines
4.3 KiB
10 years ago
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Reading Geospatial Raster files with GDAL {#tutorial_raster_io_gdal}
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=========================================
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Geospatial raster data is a heavily used product in Geographic Information Systems and
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Photogrammetry. Raster data typically can represent imagery and Digital Elevation Models (DEM). The
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standard library for loading GIS imagery is the Geographic Data Abstraction Library (GDAL). In this
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example, we will show techniques for loading GIS raster formats using native OpenCV functions. In
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addition, we will show some an example of how OpenCV can use this data for novel and interesting
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purposes.
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Goals
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-----
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The primary objectives for this tutorial:
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- How to use OpenCV imread to load satellite imagery.
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- How to use OpenCV imread to load SRTM Digital Elevation Models
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- Given the corner coordinates of both the image and DEM, correllate the elevation data to the
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image to find elevations for each pixel.
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- Show a basic, easy-to-implement example of a terrain heat map.
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- Show a basic use of DEM data coupled with ortho-rectified imagery.
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To implement these goals, the following code takes a Digital Elevation Model as well as a GeoTiff
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image of San Francisco as input. The image and DEM data is processed and generates a terrain heat
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map of the image as well as labels areas of the city which would be affected should the water level
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of the bay rise 10, 50, and 100 meters.
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Code
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----
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@includelineno cpp/tutorial_code/HighGUI/GDAL_IO/gdal-image.cpp
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How to Read Raster Data using GDAL
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----------------------------------
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This demonstration uses the default OpenCV imread function. The primary difference is that in order
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to force GDAL to load the image, you must use the appropriate flag.
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@code{.cpp}
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cv::Mat image = cv::imread( argv[1], cv::IMREAD_LOAD_GDAL );
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@endcode
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When loading digital elevation models, the actual numeric value of each pixel is essential and
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cannot be scaled or truncated. For example, with image data a pixel represented as a double with a
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value of 1 has an equal appearance to a pixel which is represented as an unsigned character with a
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value of 255. With terrain data, the pixel value represents the elevation in meters. In order to
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ensure that OpenCV preserves the native value, use the GDAL flag in imread with the ANYDEPTH flag.
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@code{.cpp}
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cv::Mat dem = cv::imread( argv[2], cv::IMREAD_LOAD_GDAL | cv::IMREAD_ANYDEPTH );
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@endcode
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If you know beforehand the type of DEM model you are loading, then it may be a safe bet to test the
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Mat::type() or Mat::depth() using an assert or other mechanism. NASA or DOD specification documents
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can provide the input types for various elevation models. The major types, SRTM and DTED, are both
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signed shorts.
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Notes
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-----
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### Lat/Lon (Geodetic) Coordinates should normally be avoided
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The Geodetic Coordinate System is a spherical coordinate system, meaning that using them with
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Cartesian mathematics is technically incorrect. This demo uses them to increase the readability and
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is accurate enough to make the point. A better coordinate system would be Universal Transverse
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Mercator.
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### Finding the corner coordinates
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One easy method to find the corner coordinates of an image is to use the command-line tool gdalinfo.
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For imagery which is ortho-rectified and contains the projection information, you can use the [USGS
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EarthExplorer](http://http://earthexplorer.usgs.gov).
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@code{.bash}
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\f$> gdalinfo N37W123.hgt
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Driver: SRTMHGT/SRTMHGT File Format
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Files: N37W123.hgt
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Size is 3601, 3601
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Coordinate System is:
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GEOGCS["WGS 84",
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DATUM["WGS_1984",
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... more output ...
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Corner Coordinates:
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Upper Left (-123.0001389, 38.0001389) (123d 0' 0.50"W, 38d 0' 0.50"N)
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Lower Left (-123.0001389, 36.9998611) (123d 0' 0.50"W, 36d59'59.50"N)
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Upper Right (-121.9998611, 38.0001389) (121d59'59.50"W, 38d 0' 0.50"N)
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Lower Right (-121.9998611, 36.9998611) (121d59'59.50"W, 36d59'59.50"N)
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Center (-122.5000000, 37.5000000) (122d30' 0.00"W, 37d30' 0.00"N)
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... more output ...
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@endcode
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Results
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-------
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Below is the output of the program. Use the first image as the input. For the DEM model, download
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the SRTM file located at the USGS here.
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[<http://dds.cr.usgs.gov/srtm/version2_1/SRTM1/Region_04/N37W123.hgt.zip>](http://dds.cr.usgs.gov/srtm/version2_1/SRTM1/Region_04/N37W123.hgt.zip)
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