Remote sensing of fuel moisture content from the ratios of canopy water indices with a foliar dry matter index

E. Raymond Hunt Jr.; Lingli Wang; John J. Qu; Xianjun Hao

doi:10.1117/12.930077

24 October 2012 Remote sensing of fuel moisture content from the ratios of canopy water indices with a foliar dry matter index

E. Raymond Hunt Jr., Lingli Wang, John J. Qu, Xianjun Hao

Author Affiliations +

Proceedings Volume 8513, Remote Sensing and Modeling of Ecosystems for Sustainability IX; 851302 (2012) https://doi.org/10.1117/12.930077
Event: SPIE Optical Engineering + Applications, 2012, San Diego, California, United States

Abstract

^{Fuel moisture content (FMC) is an important variable for predicting the occurrence and spread of wildfire. Foliar FMC
was calculated as the ratio of leaf foliar water content (Cw) and dry matter content (Cm). Recently, the normalized dry
matter index (NDMI) was developed for the remote sensing of Cm using high-spectral resolution data. This study
explored the potential for remote sensing of FMC using the ratio of various vegetation water indices with NDMI. For
leaf-scale simulations, all index ratios were significantly related to FMC. For canopy-scale simulations, ratio indices of
the normalized difference infrared index (NDII) and normalized difference water index (NDWI) with NDMI predicted
FMC with R2 values of 0.900 and 0.864, respectively. NDII/NDMI determined from leaf reflectance data had the
highest correlation with FMC. Further investigation needs to be conducted to evaluate the effectiveness of this approach
at canopy scales with airborne remote sensing data.}

Citation Download Citation

E. Raymond Hunt Jr., Lingli Wang, John J. Qu, and Xianjun Hao "Remote sensing of fuel moisture content from the ratios of canopy water indices with a foliar dry matter index", Proc. SPIE 8513, Remote Sensing and Modeling of Ecosystems for Sustainability IX, 851302 (24 October 2012); https://doi.org/10.1117/12.930077

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