The present study also shows that higher classification
accuracies were achieved for certain vegetation classes like teak
forest, degraded forest, open mixed forest, grassland, habitation,
and water bodies. This may be ascribed to distinct spectral
behavior of these forest types, making them easily separable,
which helped in achieving better accuracies compared to other
classes. However, the sal mixed forest and dense mixed forest
classes showed lower accuracies because the pixels of these
classes were intermixed with each other. They were also not
spectrally as homogenous as other classes like teak forest, open
mixed forest and degraded mixed forests.