摘要：Back-projecting is an alternative to orthorectification for ALS-imagery fusion. It usually assists in improving forest estimations in mixed forests, by adding species information from optical sensors. In this study, we focused on the within-species advantages obtained. Results showed that estimating relative stem density improved significantly (from R2=0.76 to R2=0.81), as the multispectral signal may incorporate canopy closure-related shadowing conditions at plot-level. As a result, volume prediction also improved (from R2=0.65 to R2=0.69), even though Lorey's height and basal area did not. Hence, monospecific conifer forests assessment may also benefit from ALS-imagery fusion.
关键词：Sensor data fusion ; Lidar ; stem density ; Stand Density Index ; Snag detection ; Forest Health
