Land-cover mapping in the Nujiang Grand Canyon: integrating spectral, textural, and topographic data in a random forest classifier
The integration of spectral, textural, and topographic information using a random forest classifier for land-cover mapping in the rugged Nujiang Grand Canyon was investigated in this study. Only a few land-cover categories were accurately discriminated using spectral information exclusively, with an overall accuracy of 0.56 and a kappa coefficient of 0.51.