EXTRACTING FOREST CANOPY CHARACTERISTICS FROM REMOTE SENSING IMAGERY: IMPLICATIONS FOR SENTINEL-2 MISSION

摘要

Systematic quantification and monitoring of forest biophysical and biochemical variables is required to assess the response of ecosystems to climate change. Remote sensing has been introduced as a time and cost-efficient way to carry out large scale monitoring of vegetation parameters. Red-Edge Position (REP) is a hyperspectrally detectable parameter which is sensitive to vegetation Chl. In the current study, REP was modelled for the Norway spruce forest canopy resampled to HyMap and Sentinel-2 spectral resolution as well as calculated from the real HyMap and Sentinel-2 simulated data. Different REP extraction methods (4PLI, PF, LE, 4PLIH and 4PLIS) were assessed. The study showed the way for effective utilization of the forthcoming hyper and superspectral remote sensing sensors from orbit to monitor vegetation attributes.