Tree Crown Size Estimated Using Image Processing: A Biodiversity Index for Sloping Subtropical Broad-Leaved Forests

Forest patches characterized by old trees with large crown sizes are of high biodiversity conservation value because they contain various microhabitats and may preserve the original flora of primeval or ancient forests. Aerial photo estimations of the average tree crown size represent a promising approach for identifying and monitoring such forest patches. Numerous sensors and algorithms have been developed to estimate the crown size in coniferous forests or forests with relatively low topographic variations; however, methods for estimating the crown size in steep broad-leaved forests in tropical or temperate regions are still required. We propose a method of estimating the size of tree crowns to obtain the "crown size index (CSI)," which can be used as a candidate biodiversity index for steep broad-leaved forest patches. We applied this method to a subtropical broad-leaved forest in southwestern Japan. In the first step, gray values from aerial imagery are converted to relative values, and then the crown size is subjected to a granulometric estimation. Regression of the CSI from the diameter at breast height of the canopy layer trees presented R-2 values as high as 0.67. Resampling tests revealed that monochrome aerial images resampled with spatial resolutions ranging from 0.40 m to 1.20 m produced results with relatively high accuracy (R-2 >= .55). These results suggest that the proposed method has the potential for use as a cost-effective method of evaluating the biodiversity of broad-leaved forest patches in hilly or mountainous regions using images from various high-resolution sensors.