Integration of satellite imagery and forest inventory in mapping dominant and associated species at a regional scale
|Authors:||Yangjian Zhang, Hong S. He, William D. Dijak, Jian Yang, Stephen R. Shifley, Brian J. Palik|
|Station:||Northern Research Station|
|Source:||Environmental Management. 44: 312-323.|
To achieve the overall objective of restoring natural environment and sustainable resource usability, each forest management practice effect needs to be predicted using a simulation model. Previous simulation efforts were typically confined to public land. Comprehensive forest management practices entail incorporating interactions between public and private land. To make inclusion of private land into management planning feasible at the regional scale, this study uses a new method of combining Forest Inventory and Analysis (FIA) data with remotely sensed forest group data to retrieve detailed species composition and age information for the Missouri Ozark Highlands. Remote sensed forest group and land form data inferred from topography were integrated to produce distinct combinations (ecotypes). Forest types and size classes were assigned to ecotypes based on their proportions in the FIA data. Then tree species and tree age determined from FIA subplots stratified by forest type and size class were assigned to pixels for the entire study area.