Monitoring forest health by remote sensing of canopy chlorophyll: first results from a pilot project in Norway

摘要

Variation in canopy chlorophyll mass per area is a well-suited candidate for tracking temporal changes in forest health. In the current project, we try to apply remote sensing techniques for measuring this. Within a 6 km~2 forest test area dominated by Norway spruce (Picea abies) we have data from three spatial levels: ground, airborne and satellites. On ground we have data on LAI and chlorophyll concentrations from 16 sample plots. The airborne level, comprising LiDAR and hyperspectral data, is used for modelling of LAI and chlorophyll concentrations, and for up-scaling to the entire area. We try to model LAI using LiDAR, and chlorophyll concentrations using the hyperspectral data. Up-scaled data for LAI are correlated to SPOT satellite data. If it turns out that up-scaled estimates are correlated to satellite data, this might form a basis for developing a new forest health monitoring system in Norway and elsewhere.