Estimating Canopy Water Content of Chaparral Shrubs Using Optical Methods

Predicting fire hazard in fire-prone ecosystems in urbanized landscapes, such as the chaparral systems of California, is critical to risk assessment and mitigation. Understanding the dynamics of fire spread, topography and vegetation condition are necessary to increase the accuracy of fire risk assessment. One vital input to fire models is spatial and temporal estimates of canopy water content. However, timely estimates of such a dynamic ecosystem property cannot be provided for more than periodic point samples using ground based methods. This study examined the potential of three quasiphysical methods for estimating water content using remotely sensed Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data of chaparral systems in the Santa Monica Mountains, California. We examined estimates of water content at the leaf, canopy, and image level and compared them to each other and to ground-based estimates of plant water content. These methods predicted water content (with R2 between 0.62 and 0.95) but differ in their ease of use and the need for ancillary data inputs. The prospect for developing regional estimates for canopy water content at high spatial resolution (20 m) from high resolution optical sensors appears promising.