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114 lines
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ReStructuredText
114 lines
4.6 KiB
ReStructuredText
.. _Raster_IO_GDAL:
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Reading Geospatial Raster files with GDAL
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*****************************************
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Geospatial raster data is a heavily used product in Geographic Information
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Systems and Photogrammetry. Raster data typically can represent imagery
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and Digital Elevation Models (DEM). The standard library for loading
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GIS imagery is the Geographic Data Abstraction Library (GDAL). In this example, we
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will show techniques for loading GIS raster formats using native OpenCV functions.
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In addition, we will show some an example of how OpenCV can use this data for
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novel and interesting purposes.
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Goals
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=====
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The primary objectives for this tutorial:
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.. container:: enumeratevisibleitemswithsquare
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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 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 image of San Francisco as input.
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The image and DEM data is processed and generates a terrain heat map of the image as well as labels areas of the city which would
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be affected should the water level of the bay rise 10, 50, and 100 meters.
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Code
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====
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.. literalinclude:: ../../../../samples/cpp/tutorial_code/HighGUI/GDAL_IO/gdal-image.cpp
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:language: cpp
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:linenos:
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:tab-width: 4
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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 :ocv:func:`imread` function. The primary difference is that in order to force GDAL to load the
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image, you must use the appropriate flag.
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.. code-block:: cpp
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cv::Mat image = cv::imread( argv[1], cv::IMREAD_LOAD_GDAL );
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When loading digital elevation models, the actual numeric value of each pixel is essential
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and cannot be scaled or truncated. For example, with image data a pixel represented as a double with a value of 1 has
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an equal appearance to a pixel which is represented as an unsigned character with a value of 255.
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With terrain data, the pixel value represents the elevation in meters. In order to ensure that OpenCV preserves the native value,
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use the GDAL flag in imread with the ANYDEPTH flag.
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.. code-block:: cpp
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cv::Mat dem = cv::imread( argv[2], cv::IMREAD_LOAD_GDAL | cv::IMREAD_ANYDEPTH );
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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 ``Mat::type()`` or ``Mat::depth()``
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using an assert or other mechanism. NASA or DOD specification documents can provide the input types for various
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elevation models. The major types, SRTM and DTED, are both 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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---------------------------------------------------------
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The Geodetic Coordinate System is a spherical coordinate system, meaning that using them with Cartesian mathematics is technically incorrect. This
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demo uses them to increase the readability and is accurate enough to make the point. A better coordinate system would be Universal Transverse Mercator.
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Finding the corner coordinates
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------------------------------
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One easy method to find the corner coordinates of an image is to use the command-line tool ``gdalinfo``. For imagery which is ortho-rectified and contains
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the projection information, you can use the `USGS EarthExplorer <http://http://earthexplorer.usgs.gov>`_.
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.. code-block:: bash
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$> 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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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 the SRTM file located at the USGS here. `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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.. image:: images/output.jpg
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.. image:: images/heat-map.jpg
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.. image:: images/flood-zone.jpg
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