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Post classification comparison is applied to generate transition maps.
The post classification comparison of statistics suggests transformation from dense forest to agriculture class.
After ensuring satisfactory accuracy value for each classified image a detail post classification change detection analysis was executed.
Both pre-classification and post classification change detection approach was used to assess the change result from 1980 to 2010.
We applied a post classification method and tested the gain, loss, and net change of natural and anthropic ecosystems in the study area with a cross tabulation matrix.
Then, we analyzed the spatial variation and expansion of urban land changes across the entire metropolitan area through post classification change detection and a variety of GIS-based operations.
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Subsequently post-classification change detection is performed on urban footprint level.
Post-classification differencing identified regions of cropland that had been converted to CRP.
Post-classification and compound classification were evaluated for their performances in the "from to" change results.
Change detection maps are derived in a post-classification change detection.
The second method involved aggregating the data post-classification by resampling with a majority filter.
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