108 lines
4.5 KiB
Markdown
108 lines
4.5 KiB
Markdown
|
Reading Geospatial Raster files with GDAL {#tutorial_raster_io_gdal}
|
||
|
=========================================
|
||
|
|
||
|
@tableofcontents
|
||
|
|
||
|
@prev_tutorial{tutorial_trackbar}
|
||
|
@next_tutorial{tutorial_video_input_psnr_ssim}
|
||
|
|
||
|
| | |
|
||
|
| -: | :- |
|
||
|
| Original author | Marvin Smith |
|
||
|
| Compatibility | OpenCV >= 3.0 |
|
||
|
|
||
|
Geospatial raster data is a heavily used product in Geographic Information Systems and
|
||
|
Photogrammetry. Raster data typically can represent imagery and Digital Elevation Models (DEM). The
|
||
|
standard library for loading GIS imagery is the Geographic Data Abstraction Library [(GDAL)](http://www.gdal.org). In this
|
||
|
example, we will show techniques for loading GIS raster formats using native OpenCV functions. In
|
||
|
addition, we will show some an example of how OpenCV can use this data for novel and interesting
|
||
|
purposes.
|
||
|
|
||
|
Goals
|
||
|
-----
|
||
|
|
||
|
The primary objectives for this tutorial:
|
||
|
|
||
|
- How to use OpenCV [imread](@ref imread) to load satellite imagery.
|
||
|
- How to use OpenCV [imread](@ref imread) to load SRTM Digital Elevation Models
|
||
|
- Given the corner coordinates of both the image and DEM, correlate the elevation data to the
|
||
|
image to find elevations for each pixel.
|
||
|
- Show a basic, easy-to-implement example of a terrain heat map.
|
||
|
- Show a basic use of DEM data coupled with ortho-rectified imagery.
|
||
|
|
||
|
To implement these goals, the following code takes a Digital Elevation Model as well as a GeoTiff
|
||
|
image of San Francisco as input. 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 be affected should the water level
|
||
|
of the bay rise 10, 50, and 100 meters.
|
||
|
|
||
|
Code
|
||
|
----
|
||
|
|
||
|
@include cpp/tutorial_code/imgcodecs/GDAL_IO/gdal-image.cpp
|
||
|
|
||
|
How to Read Raster Data using GDAL
|
||
|
----------------------------------
|
||
|
|
||
|
This demonstration uses the default OpenCV imread function. The primary difference is that in order
|
||
|
to force GDAL to load the image, you must use the appropriate flag.
|
||
|
@snippet cpp/tutorial_code/imgcodecs/GDAL_IO/gdal-image.cpp load1
|
||
|
When loading digital elevation models, the actual numeric value of each pixel is essential and
|
||
|
cannot be scaled or truncated. For example, with image data a pixel represented as a double with a
|
||
|
value of 1 has an equal appearance to a pixel which is represented as an unsigned character with a
|
||
|
value of 255. With terrain data, the pixel value represents the elevation in meters. In order to
|
||
|
ensure that OpenCV preserves the native value, use the GDAL flag in imread with the ANYDEPTH flag.
|
||
|
@snippet cpp/tutorial_code/imgcodecs/GDAL_IO/gdal-image.cpp load2
|
||
|
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() using an assert or other mechanism. NASA or DOD specification documents
|
||
|
can provide the input types for various elevation models. The major types, SRTM and DTED, are both
|
||
|
signed shorts.
|
||
|
|
||
|
Notes
|
||
|
-----
|
||
|
|
||
|
### Lat/Lon (Geographic) Coordinates should normally be avoided
|
||
|
|
||
|
The Geographic Coordinate System is a spherical coordinate system, meaning that using them with
|
||
|
Cartesian mathematics is technically incorrect. This demo uses them to increase the readability and
|
||
|
is accurate enough to make the point. A better coordinate system would be Universal Transverse
|
||
|
Mercator.
|
||
|
|
||
|
### Finding the corner coordinates
|
||
|
|
||
|
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 the projection information, you can use the [USGS
|
||
|
EarthExplorer](http://http://earthexplorer.usgs.gov).
|
||
|
@code{.bash}
|
||
|
\f$> gdalinfo N37W123.hgt
|
||
|
|
||
|
Driver: SRTMHGT/SRTMHGT File Format
|
||
|
Files: N37W123.hgt
|
||
|
Size is 3601, 3601
|
||
|
Coordinate System is:
|
||
|
GEOGCS["WGS 84",
|
||
|
DATUM["WGS_1984",
|
||
|
|
||
|
... more output ...
|
||
|
|
||
|
Corner Coordinates:
|
||
|
Upper Left (-123.0001389, 38.0001389) (123d 0' 0.50"W, 38d 0' 0.50"N)
|
||
|
Lower Left (-123.0001389, 36.9998611) (123d 0' 0.50"W, 36d59'59.50"N)
|
||
|
Upper Right (-121.9998611, 38.0001389) (121d59'59.50"W, 38d 0' 0.50"N)
|
||
|
Lower Right (-121.9998611, 36.9998611) (121d59'59.50"W, 36d59'59.50"N)
|
||
|
Center (-122.5000000, 37.5000000) (122d30' 0.00"W, 37d30' 0.00"N)
|
||
|
|
||
|
... more output ...
|
||
|
@endcode
|
||
|
Results
|
||
|
-------
|
||
|
|
||
|
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)
|
||
|
|
||
|
![Input Image](images/gdal_output.jpg)
|
||
|
|
||
|
![Heat Map](images/gdal_heat-map.jpg)
|
||
|
|
||
|
![Heat Map Overlay](images/gdal_flood-zone.jpg)
|