Predicting landscape structural metrics using aster satellite data - Ozdemir, Ibrahim; Mert, Ahmet; Senturk, Ozdemir (Journal of Environmental Engineering and Landscape Management, 2012)
The aim of this study was to predict landscape structural metrics using the features extracted from the ASTER multispectral satellite imagery with 15 m spatial resolution. The landscape structural metrics were calculated on the basis of forest map polygons generated from 1:15000 scaled aerial photos by photo-interpretation technique. The landscape metrics and corresponding image features that are texture parameters and segmentation polygons were determined for four different landscape extents. A stepwise multiple linear regression analysis was carried out to identify the most significant image-derived predictors of landscape metrics for each extent. The regression models established for the landscape metrics including the Number of Patches (NUMP), Edge Density (ED), Shannon's Diversity Index (SDI) and Patch Richness (PR) performed moderately with adjusted R2 values of 0.50 and 0.53 (P