Characterizing terrestrial ecosystems and productivity from remote sensing data

Predictive relationships were studied between the leaf area index (LAI) of temperate coniferous forests and the canopy of reflective properties as sensed by satellites. Also, the relationship was examined between this sensible variable, LAI, and functional properties such as net primary productivity (NPP) and nitrogen mineralization. Leaf surface area is a locus of many important material and energy exchanges. If LAI can be reasonably estimated from remote sensing measurements, then it could be used with models to predict evapotranspiration, radiation interception, precipitation interception, and other ecosystem processes over large areas. Nineteen mature closed canopy forest stands were measured for leaf area index distributed along a temperature moisture gradient across Oregon. The LAI varies from 15.4 to 0.6. Infrared radiation is strongly scattered by leaves so that it penetrates deeply and its reflectance is proportional to LAI. Red radiation is strongly absorbed by chlorophyll and its reflectance is inversely related to LAI, becoming asymptotic at LAI values of about 3. The ratio of infrared to red radiation compensates for irradiance variations across this transect.