Sequential Gaussian simulation vs. simulated annealing for locating pockets of high-value commercial trees in Pennsylvania

A continuous map of a forest resource is useful to visualize patterns not evident with point samples or as a layer in a geographic information system. Forest resource information is usually collected by ground inventories using point sampling, aerial photography, or remote sensing. Point sampling is expensive and time consuming. Less expensive aerial photography and remote sensing cannot provide the required detail. The tools of geo-statistics can provide estimates at unsampled locations to create a continuous map of the forest resource. Two sequential simulation techniques, sequential Gaussian simulation and simulated annealing, are compared for locating pockets of high-value commercial trees in Pennsylvania. Both procedures capture the same trends, but simulated annealing is better than sequential Gaussian simulation at finding pockets of high-value commercial trees in Pennsylvania. Sequential Gaussian simulation is better at visualizing large-scale patterns and providing a quick solution. Simulated annealing requires more user time and should be used for projects requiring local detail.