ESTIMATING CANOPY WATER-CONTENT OF CHAPARRAL SHRUBS USING OPTICAL METHODS

Predicting fire hazard in fire-prone ecosystems in urbanized landscape s, such as the chaparral systems of California, is critical to risk as sessment and mitigation. Understanding the dynamics of fire spread, to pography and vegetation condition are necessary to increase the accura cy of fire risk assessment. One vital input to fire models is spatial and temporal estimates of canopy water content. However, timely estima tes of such a dynamic ecosystem property cannot be provided for more t han periodic point samples using ground based methods. This study exam ined the potential of three quasiphysical methods for estimating water content using remotely sensed Airborne Visible Infrared Imaging Spect rometer (AVIRIS) data of chaparral systems in the Santa Monica Mountai ns, California. We examined estimates of water content at the leaf, ca nopy, and image level and compared them to each other and to ground-ba sed estimates of plant water content. These methods predicted water co ntent (with R-2 between 0.62 and 0.95) but differ in their ease of use and the need for ancillary data inputs. The prospect for developing r egional estimates for canopy water content at high spatial resolution (20 m) from high resolution optical sensors appears promising. (C)Else vier Science Inc., 1988