I have tried several methods including unsupervised classification, supervised classification, random-forest classification, and spectral indices methods to estimate the amount of impervious surface in Midwest US town from Landsat 8 Image.
The results did not converge reasonably. The core problem seems to be the case of mixed-pixels in the training shapefile which overestimate the impervious surface. I also suspect spectral confusion in which certain land-use features such as soil are wrongly mapped as impervious because of spectral similarity of these features.
I am using ArcGIS 10.3 and ENVI for processing the imagery.
How can I use a training data (polygon or point shapefile) that only contains pure-pixels, so that I don't overestimate Imperviousness?
I would prefer to work on ArcGIS 10.3.