Revision as of 02:59, 28 October 2009 by Neteler (moved into own page)
Classification methods in GRASS
|radiometric & geometric|
|Preprocessing||(monitor digitizing)||(using training maps)||(using training maps)|
- - Generates spectral signatures for an image by allowing the user to outline regions of interest.
- The resulting signature file can be used as input for or as a seed signature file for .
- - Generates spectral signatures for land cover types in an image using a clustering algorithm.
- The resulting signature file is used as input for , to generate an unsupervised image classification.
- - Generates statistics for from raster map layer.
- - Generate statistics for from raster map layer.
- - Classifies the cell spectral reflectances in imagery data.
- Classification is based on the spectral signature information generated by either , , or .
- - Performs contextual (image segmentation) image classification using sequential maximum a posteriori (SMAP) estimation.
Further reading classification with GRASS
- Micha Silver: Analyzing acacia tree health in the Arava with GRASS GIS
- Perrygeo: Impervious surface deliniation with GRASS
- Dylan Beaudette: Working with Landsat Data
- Dylan Beaudette: Canopy Quantification via Image Classification