Simulated Annealing With Variogram-Based Optimization to Quantify Spatial Patterns of Trees Extracted From High-Resolution Images

The recognition of spatial patterns of trees from satellite images is important for forestry, horticulture, and wildlife management. As a spatial optimization problem, we used variogram matching as the objective function for simulated tree arrangements and their simulated reproductions. We developed a variogram difference-based spatial simulated annealing (VDBSSA) method and applied it in reproducing alternate simulated tree arrangements in several orchards in India. Regular, linear, and sparse configurations with clearly separated objects could be distinguished. QuickBird 2 panchromatic images (0.6-m resolution) were binarized, followed by generating simulated images of a similar appearance. The performance of VDBSSA for alternate arrangements with the same spatial structure was explained by pattern characteristics. The density of objects inversely influenced the number of possible alternate arrangements. A sparse configuration gave more choices of alternate spatial arrangements than a dense configuration. VDBSSA is valuable for generating a pattern of well identifiable objects from a remote sensing image.