Integration of Lidar, Landsat Etm+ and Forest Inventory Data for Regional Forest Mapping

Recent work has established the utility of waveform sampling lidar for predicting forest structural attributes. Nevertheless, serious obstacles to its wide-spread use still exist. They include the lack of waveform sampling lidar sensors capable of measuring forest canopy structure over large extents, and the practical difficulty of developing widely applicable relationships to predict forest stand structure indices (such as aboveground biomass) from measurements of canopy structure. While the advent of advanced devices such as NASA’s LVIS and VCL sensors will allow the collection of larger datasets than previously possible, neither sensor is capable of collecting spatially comprehensive datasets at the regional scales critical for forest management. Therefore, methods to integrate data from these devices with conventional optical remote sensing products such as those from the Landsat Enhanced Thematic Mapper Plus (Landsat ETM+) sensor will play a critical role in the development of lidar remote sensing. In addition, it will be desirable to develop methods to facilitate the use of existing forest inventory datasets, which include substantial information on the height of dominant trees, to interpret lidar measurements of canopy structure. Preliminary results from a new study that incorporates both approaches (Lidar-ETM+ data fusion, incorporating forest inventory data for the interpretation of lidar data) to accomplish wall-towall mapping of forest structure and composition in Oregon and Washington suggest that these approaches are feasible, and that they will lead to more accurate maps of forest structure and composition.