Integration of Lidar and Landsat Etm+ Data

Lidar data provide accurate measurements of forest canopy structure in the vertical plane however current lidar sensors have limited coverage in the horizontal plane. Landsat data provide extensive coverage of generalized forest structural classes in the horizontal plane but are relatively insensitive to variation in forest canopy height. It would therefore be desirable to integrate lidar and Landsat data to improve the measurement, mapping, and monitoring of forest structural attributes. We tested five aspatial and spatial methods for predicting canopy height, as measured by an airborne lidar system (Aeroscan), from Landsat ETM+ data: regression, kriging, cokriging, and kriging and cokriging of regression residuals. Our 200 km study area in western Oregon encompassed Oregon State University’s McDonald-Dunn Research Forest, which is broadly representative of the age and structural classes common in the region. We sampled our continuous lidar coverage in eight systematic patterns to determine which lidar sampling strategy would optimize lidar-Landsat integration: transects sampled at 2000, 1000, 500 and 250 m frequencies, and points sampled at these same spatial frequencies. The aspatial regression model results, regardless of sampling strategy, preserved actual vegetation pattern, but underestimated taller canopies and overestimated shorter canopies. The spatial models, kriging and cokriging, produced less biased results than regression but poorly reproduced vegetation pattern. The integrated models that kriged or cokriged regression residuals were preferable to either the aspatial or spatial models alone, because they preserved the vegetation pattern like regression yet improved estimation accuracies above those predicted from the regression models alone. We concluded that in our study landscape, an integrated modeling strategy is most suitable for estimating and mapping canopy height at locations unsampled by lidar, and that a 250 m point sampling strategy would be more useful for lidar-Landsat ETM+ integration than sparser transect sampling strategies planned for satellite missions.