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- <title>Image processing in GRASS GIS</title>
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- <h2>Image processing in GRASS GIS</h2>
- <h3>Image data in general</h3>
- In GRASS, image data are identical to <a href="rasterintro.html">raster data</a>.
- However, a couple of commands are explicitly dedicated to image
- processing. The geographic boundaries of the raster/imagery file are
- described by the north, south, east, and west fields. These values
- describe the lines which bound the map at its edges. These lines do
- NOT pass through the center of the grid cells at the edge of the map,
- but along the edge of the map itself.
- <P>
- As a general rule in GRASS:
- <ol>
- <li> Raster/imagery output maps have their bounds and resolution equal
- to those of the current region.
- <li> Raster/imagery input maps are automatically cropped/padded and
- rescaled (using nearest-neighbor resampling) to match the current
- region.
- </ol>
- <h3>Raster import</h3>
- The module <a href="r.in.gdal.html">r.in.gdal</a> offers a common
- interface for many different raster and satellite image
- formats. Additionally, it also offers options such as on-the-fly
- location creation or extension of the default region to match the
- extent of the imported raster map. For special cases, other import
- modules are available. Always the full map is imported. Imagery data
- can be group (e.g. channel-wise) with <a href="i.group.html">i.group</a>.
- <P>
- For importing scanned maps, the user will need to create a
- x,y-location, scan the map in the desired resolution and save it into
- an appropriate raster format (e.g. tiff, jpeg, png, pbm) and then use
- <a href="r.in.gdal.html">r.in.gdal</a> to import it. Based on
- reference points the scanned map can be rectified to obtain geocoded
- data.
- <h3>Image processing operations</h3>
- GRASS raster/imagery map processing is always performed in the current
- region settings (see <a href="g.region.html">g.region</a>), i.e. the
- current region extent and current raster resolution is used. If the
- resolution differs from that of the input raster map(s), on-the-fly
- resampling is performed (nearest neighbor resampling). If this is not
- desired, the input map(s) has/have to be resampled beforehand with one
- of the dedicated modules.
- <h3>Geocoding of imagery data</h3>
- GRASS is able to geocode raster and image data of various types:
- <ul>
- <li>unreferenced scanned maps by defining four corner points
- (<a href="i.group.html">i.group</a>, <a href="i.target.html">i.target</a>,
- <a href="i.points.html">i.points</a>, <a href="i.rectify.html">i.rectify</a>)</li>
- <li>unreferenced satellite data from optical and Radar sensors by
- defining a certain number of ground control points
- (<a href="i.group.html">i.group</a>, <a href="i.target.html">i.target</a>,
- <a href="i.points.html">i.points</a>, <a href="i.rectify.html">i.rectify</a>)</li>
- <!--
- <li>orthophoto based on DEM: <a href="i.ortho.photo.html">i.ortho.photo</a></li>
- <li>digital handheld camera geocoding: modified procedure for
- <a href="i.ortho.photo.html">i.ortho.photo</a></li>
- -->
- </ul>
- <h3>Visualizing (true) color composites</h3>
- To quickly combine the first three channels to a near natural color
- image, the GRASS command <a href="d.rgb.html">d.rgb</a> can be used or
- the graphical GIS manager (<a href="gis.m.html">gis.m</a>). It assigns
- each channel to a color which is then mixed while displayed. With a
- bit more work of tuning the grey scales of the channels, nearly
- perfect colors can be achieved. Channel histograms can be shown with
- <a href="d.histogram.html">d.histogram</a>.
- <h3>Calculation of vegetation indices</h3>
- An example for indices derived from multispectral data is the NDVI
- (normalized difference vegetation index). To study the vegetation
- status with NDVI, the Red and the Near Infrared channels (NIR) are
- taken as used as input for simple map algebra in the GRASS command
- <a href="r.mapcalc.html">r.mapcalc</a>
- (<tt>ndvi = 1.0 * (nir - red)/(nir + red)</tt>). With
- <a href="r.colors.html">r.colors</a> an optimized "ndvi" color table
- can be assigned afterward. Also other vegetation indices can be
- generated likewise.
- <h3>Calibration of thermal channel</h3>
- The encoded digital numbers of a thermal infrared channel can be
- transformed to degree Celsius (or other temperature units) which
- represent the temperature of the observed land surface. This requires
- a few algebraic steps with <a href="r.mapcalc.html">r.mapcalc</a>
- which are outlined in the literature to apply gain and bias values
- from the image metadata.
- <h3>Image classification</h3>
- Single and multispectral data can be classified to user defined land
- use/land cover classes. In case of a single channel, segmentation will
- be used.
- GRASS supports the following methods:
- <ul>
- <li> Radiometric classification:
- <ul>
- <li> Unsupervised classification (<a href="i.cluster.html">i.cluster</A>,
- <a href="i.maxlik.html">i.maxlik</A>) using the Maximum Likelihood
- classification method</li>
- <li> Supervised classification (<a href="i.gensig.html">i.gensig</A>
- or <a href="i.class.html">i.class</A>, <a href="i.maxlik.html">i.maxlik</A>)
- using the Maximum Likelihood classification method</li>
- </ul>
- <li> Combined radiometric/geometric (segmentation based) supervised
- classification (<A HREF="i.gensigset.html">i.gensigset</A>,
- <a href="i.smap.html">i.smap</a>)
- </ul>
- Kappa statistic can be calculated to validate the results
- (<a href="r.kappa.html">r.kappa</a>).
- <h3>Image fusion</h3>
- In case of using multispectral data, improvements of the resolution
- can be gained by merging the panchromatic channel with color
- channels. GRASS provides the HIS (<a href="i.rgb.his.html">i.rgb.his</a>,
- <a href="i.his.rgb.html">i.his.rgb</a>) and the Brovey transform
- (<a href="i.fusion.brovey.html">i.fusion.brovey</a>) methods.
- <h3>Time series processing</h3>
- GRASS also offers support for time series processing (<a
- href="r.series.html">r.series</a>). Statistics can be derived from a
- set of coregistered input maps such as multitemporal satellite
- data. The common univariate statistics and also linear regression can
- be calculated.
- <h3>See also</h3>
- <ul>
- <li>The GRASS 4
- <em><A HREF="http://grass.itc.it/gdp/imagery/grass4_image_processing.pdf">Image
- Processing manual</A></EM>
- <li><a href=rasterintro.html>Introduction to GRASS 2D raster map processing</a></li>
- <li><a href=raster3dintro.html>Introduction to GRASS 3D raster map (voxel) processing</a></li>
- <li><a href=vectorintro.html>Introduction to GRASS vector map processing</a></li>
- </ul>
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- <a href="index.html">Main index</a> - <a href="imagery.html">imagery index</a> -
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- <P>© 2008 <a href="http://grass.osgeo.org">GRASS Development Team</a></P>
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