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Remote Sens. 2018, 10(1), 87; https://doi.org/10.3390/rs10010087

Estimating Live Fuel Moisture from MODIS Satellite Data for Wildfire Danger Assessment in Southern California USA

1
APEC Climate Center, 12 Centum 7-ro, Haeundae-gu, Busan 48058, Korea
2
Center of Excellence in Earth Systems Modeling and Observations, Chapman University, Orange, CA 92866, USA
3
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
*
Author to whom correspondence should be addressed.
Received: 15 November 2017 / Revised: 3 January 2018 / Accepted: 7 January 2018 / Published: 10 January 2018
(This article belongs to the Special Issue Advances in Remote Sensing-based Disaster Monitoring and Assessment)
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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. View Full-Text
Keywords: wildfire; satellite vegetation indices; live fuel moisture; empirical model function; Southern California; chaparral ecosystem wildfire; satellite vegetation indices; live fuel moisture; empirical model function; Southern California; chaparral ecosystem
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Myoung, B.; Kim, S.H.; Nghiem, S.V.; Jia, S.; Whitney, K.; Kafatos, M.C. Estimating Live Fuel Moisture from MODIS Satellite Data for Wildfire Danger Assessment in Southern California USA. Remote Sens. 2018, 10, 87.

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