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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.