Fuel Moisture - Wildland Fuel Fundamentals and Applications - page 79

empirically to estimate FMCs for other fuel components (Schroeder and Buck
1970 ). Simulation modeling also provides an indirect way to estimate FMCs where
computer programs are used to simulate fuel moisture dynamics from weather and
fuel inputs (Nelson 2001 ). In fact, many fire managers use simulated FMCs from
the National Fire Danger Rating System (NFDRS) models to estimate local FMCs
for their fuels although the simulation of dead fuel FMCs is much better than live
fuel FMCs (Anderson 1976 ). And, in recent years, several studies have found useful
empirical relations between FMC and satellite-derived variables in several ecosys-
tems (Paltridge and Mitchell 1990 ; Chladil and Nunez 1995 ; Chuvieco and Martin
1994 ). Dead fuel FMC estimation from remotely sensed data is complex for two
reasons: (1) dead fuels are under the vegetation canopy and, therefore, cannot be
directly sensed remotely, and (2) dead fuels do not show changes in green coloration
from water variations and, consequently, are less sensitive to changes in reflectance.
For this reason, FMCs for grasslands was more effectively estimated with higher
precision than other fuels because FMC variations in grasslands have a greater in-
fluence on those variables that affect plant reflectance (such as chlorophyll content
or leaf area index; Paltridge and Mitchell 1990 ; Hardy et al. 1999 ).
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