A system for estimating water content of conifer forests using hyperspectral remote sensing data




Li, Jing Yang

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Estimation of foliage water content from remote sensing data is critical to wildfire management and monitoring forest health. Several efforts to estimate vegetation water content have relied on empirical relationships and data-specific calibrations. Therefore, the approaches used by these studies are not applicable to larger scales and different species. This work was undertaken to develop systems for retrieving foliage water content of Douglas-fir stands with closed canopy. The canopy structural parameters were constrained by forest dynamic relationships. Sensitivity analysis was used to quantify the influence of foliage water content and other factors (LAI, canopy closure, soil) on canopy reflectance simulated in the spectral range between 400 and 2400 nm. Lookup tables were generated using a forest radiative transfer model. Fuel moisture content (FMC) of Douglas-fir can then be determined from airborne hyperspectral imagery (AVIRIS) by the lookup table method. We achieved an accuracy of R2 of 0.74 for FMC which was assessed through comparisons of the estimated foliage water content with field measurements. A software system. FMAS (Fuel Moisture Content Mapping System), was developed for the estimation of fuel moisture content of Douglas-fir forests. Conclusions and further research issues were discussed.



British Columbia, moisture