Most existing methods are based on a simple thresholding approach. Terrain classification involves essential tasks in geomorphology, landscape investigation, regional planning, and hazard prediction. (2011) and Stumpf and (4) F = MI norm ⋅ WV norm a ⋅ MI norm + (1 − a) ⋅ WV norm TA B L E 4 Variable abbreviations of features used in terrain classification (e.g., Ang_SR stands for the angular second moment of the surface roughness) Feature used for classification Prefix abbreviation of features.
The GLCM, proposed byHaralick, Shanmugam, and Dinstein (1973), has commonly been used for texture feature calculation to characterize the image texture by analyzing combinations of gray-level occurrences that consider relationships of two neighboring pixels.Shruthi et al. The topographic feature selection was based on the computed result of Section 3.1, namely, TR, SR, elevation, ECV, ShR, and AC.Texture information derived from the gray-level co-occurrence matrix (GLCM) can improve the classification accuracy (Shruthi et al., 2011). ous studies(Drǎguţ & Blaschke, 2006 Drǎguţ & Eisank, 2012 Eisank, Smith, & Hillier, 2014 Stumpf & Kerle, 2011 Tarolli & Dalla Fontana, 2009), it was shown that natural objects are differentiated by LSPs, which can be used in terrain extraction and classification.
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