ArcGis Unsupervised Classification of satellite image
Performs unsupervised classification on a series of input raster bands using the Iso Cluster and Maximum Likelihood Classification tools.
Usage
•This tool combines the functionalities of the Iso Cluster and Maximum Likelihood Classification tools. It outputs a classified raster. It optionally outputs a signature file.
•When a multiband raster is specified as one of the Input raster bands (in_raster_bands in Python), all the bands will be used.
To process a selection of bands from a multiband raster, you can first create a new raster dataset composed of those particular bands with the Composite Bands tool, and use the result in the list of the Input raster bands (in_raster_bands in Python).
•The resulting signature file from this tool can be used as the input for another classification tool, such as Maximum Likelihood Classification, for greater control over the classification parameters.
•The minimum valid value for the number of classes is two. There is no maximum number of clusters. In general, more clusters require more iterations.
•To provide the sufficient statistics necessary to generate a signature file for a future classification, each cluster should contain enough cells to accurately represent the cluster. The value entered for the minimum class size should be approximately 10 times larger than the number of layers in the input raster bands.
Unsupervised , Classification , satellite , ArcGIS