Abstract
The goal of the research reported here is to assess the capability of satellite vegetation indices from the Moderate Resolution Imaging Spectroradiometer onboard both Terra and Aqua satellites, in order to replicate live fuel moisture content of Southern California chaparral ecosystems. We compared seasonal and interannual characteristics of in-situ live fuel moisture with satellite vegetation indices that were averaged over different radial extents around each live fuel moisture observation site. The highest correlations are found using the Aqua Enhanced Vegetation Index for a radius of 10 km, independently verifying the validity of in-situ live fuel moisture measurements over a large extent around each in-situ site. With this optimally averaged Enhanced Vegetation Index, we developed an empirical model function of live fuel moisture. Trends in the wet-to-dry phase of vegetation are well captured by the empirical model function on interannual time-scales, indicating a promising method to monitor fire danger levels by combining satellite, in-situ, and model results during the transition before active fire seasons. An example map of Enhanced Vegetation Index-derived live fuel moisture for the Colby Fire shows a complex spatial pattern of significant live fuel moisture reduction along an extensive wildland-urban interface, and illustrates a key advantage in using satellites across the large extent of wildland areas in Southern California.
Highlights
Wildfires in Southern California (SoCal) are part of the natural cycle under Mediterranean climatic conditions
We investigated other vegetation indices (VIs) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) land surface reflectance products (MOD09A1) for the same sites, including normalized difference water index (NDWI), normalized difference infrared index (NDII), and visible atmospherically resistant index (VARI) [23]
MODIS enhanced vegetation index (EVI) was developed to enhance the sensitivity to a wider range of vegetation conditions and to improve vegetation monitoring through a decoupling of the canopy background signal and a reduction in atmospheric influences
Summary
Wildfires in Southern California (SoCal) are part of the natural cycle under Mediterranean climatic conditions. Excessive urban growth in SoCal significantly increases the wildland-urban interface, and seriously compounds wildfire hazards, resulting in loss of human life and property [1,2]. The United States Forest Service (USFS) has developed and utilized the National Fire Danger Rating System (NFDRS) [3], for which vegetation moisture is a key input. While the moisture content of dead vegetation in NFDRS can be rather obtained from weather-dependent models since dead fuels are dependent on atmospheric variability [4], estimating the moisture content of live vegetation is more complicated because it depends on physiological properties that may significantly vary among different plant species [5].
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