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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #277947

Research Project: QUANTIFYING AND MONITORING NUTRIENT CYCLING, CARBON DYNAMICS AND SOIL PRODUCTIVITY AT FIELD, WATERSHED AND REGIONAL SCALES

Location: Hydrology and Remote Sensing Laboratory

Title: Remote sensing of leaf, canopy and vegetation water contents for satellite climate data records

Author
item Hunt, Earle - Ray
item Ustin, S - University Of California
item Riano, D - University Of California

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 7/2/2012
Publication Date: 4/1/2013
Citation: Hunt, E.R., Ustin, S.L., Riano, D. 2013. Remote sensing of leaf, canopy and vegetation water contents for satellite climate data records. In: Qu, J.J., Powell, A.M., and Sivakumar, M.V.K., editors. Satellite-Based Applications on Climate Change. Springer, New York, NY. p.335-357.

Interpretive Summary:

Technical Abstract: Foliar water content is a dynamic quantity depending on water losses from transpiration and water uptake from the soil. Absorption of shortwave radiation by water is determined by various frequency overtones of fundamental bending and stretching molecular transitions. Leaf water potential and relative water content are important variables for determining water deficit and drought effects; however, these variables may only be indirectly estimated from leaf and canopy spectral reflectances. Indices using different combinations of spectral bands may be used to estimate leaf and canopy water contents within large errors caused by variations of canopy structure and soil surface reflectance. Inversion of radiative transfer models such as PROSPECT and SAIL with artificial neural networks is a promising method for creating global datasets of canopy water content.