Special Section on Advances in Remote Sensing for Monitoring Global Environmental Changes

Remote sensing of fuel moisture content from canopy water indices and normalized dry matter index

[+] Author Affiliations
E. Raymond Hunt

Hydrology and Remote Sensing Laboratory, U.S. Department of Agriculture–Agricultural Research Service, 10300 Baltimore Avenue, Beltsville, Maryland 20705-2325

Lingli Wang, John J. Qu, Xianjun Hao

George Mason University, Department of Geography and Geoinformation Sciences, 4400 University Avenue, Fairfax, Virginia 22030-4444

J. Appl. Remote Sens. 6(1), 061705 (Dec 03, 2012). doi:10.1117/1.JRS.6.061705
History: Received September 17, 2012; Revised November 5, 2012; Accepted November 12, 2012
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Abstract.  Fuel moisture content (FMC), an important variable for predicting the occurrence and spread of wildfire, is the ratio of foliar water content and foliar dry matter content. One approach for the remote sensing of FMC has been to estimate the change in canopy water content over time by using a liquid-water spectral index. Recently, the normalized dry matter index (NDMI) was developed for the remote sensing of dry matter content using high-spectral-resolution data. The ratio of a spectral water index and a dry matter index corresponds to the ratio of foliar water and dry matter contents; therefore, we hypothesized that FMC may be remotely sensed with a spectral water index divided by NDMI. For leaf-scale simulations using the PROSPECT (leaf optical properties spectra) model, all water index/NDMI ratios were significantly related to FMC with a second-order polynomial regression. For canopy-scale simulations using the SAIL (scattering by arbitrarily inclined leaves) model, two water index/NDMI ratios, with numerators of the normalized difference infrared index (NDII) and the normalized difference water index (NDWI), predicted FMC with R2 values of 0.900 and 0.864, respectively. Leaves from three species were dried or stacked to vary FMC; measured NDII/NDMI was best related to FMC. Whereas the planned NASA mission Hyperspectral Infrared Imager (HyspIRI) will have high spectral resolution and very high signal-to-noise properties, the planned 19-day repeat frequency will not be sufficient for monitoring FMC with NDII/NDMI. Because increased fire frequency is expected with climatic change, operational assessment of FMC at large scales may require polar-orbiting environmental sensors with narrow bands to calculate NDMI.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

E. Raymond Hunt, Jr. ; Lingli Wang ; John J. Qu and Xianjun Hao
"Remote sensing of fuel moisture content from canopy water indices and normalized dry matter index", J. Appl. Remote Sens. 6(1), 061705 (Dec 03, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.061705


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