Automated Landcover Classification using unsupervised classification methods

Author: Owen Smith, IESA, University of North Georgia

alcc_arcpy(landsat_dir, out_dir, soil_brightness): Runtime: ~2:15 minutes

• landsat_dir 'str': Input landsat data directory.
• out_dir 'str': Directory where all outputs will be saved.
• soil_brightness=0.5 'int': Soil brightness factor for SAVI calculation.

Final output out_dir/ALCC.tif

Classification values still need tweaked.

Plans to implement scikit learn clustering with numpy arrays to replace arcgis unsupervised isocluster.

alcc_foss:

• WIP

Citations:

• Gašparović, M., Zrinjski, M., & Gudelj, M. (2019). Automatic cost-effective method for land cover classification (ALCC). Computers, Environment and Urban Systems, 76, 1-10.