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 e vident with point samples or as a layer in a geographic information system. Forest resource information is usually collected by ground inventories usi ng 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 geostatistics 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 h igh-value commercial trees in Pennsylvania. Both procedures capture the sam e trends, but simulated annealing is better than sequential Gaussian simula tion at finding pockets of high-value commercial trees in Pennsylvania. Seq uential Gaussian simulation is better at visualizing large-scale patterns a nd providing a quick solution. Simulated annealing requires more user time and should be used for projects requiring local detail.