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Proceedings Paper

Remote sensing of canopy water content: scaling from leaf data to MODIS
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Paper Abstract

The water in green vegetation is detectable using reflectances in the near infrared and shortwave infrared. Canopy water content is estimated from the product of leaf water content and leaf area index (LAI). The Normalized Difference Infrared Index [NDII = (R850 - R1650)/(R850 + R1650)] was found to be strongly related to canopy water content using various moderate resolution sensors (Landsat TM, ASTER, AWiFS) during the SMEX02, SMEX04, SMEX05, and OTTER experiments. With the high temporal resolution of MODIS, changes in canopy water content may perhaps be used to estimate plant water stress and wild-fire potential. However, the low spatial resolution of MODIS does not allow the relationship between NDII and canopy water content to be determined experimentally. The objective of this study is to validate the expected relationship of canopy water content with NDII by the standard LAI data product from MODIS; the quotient is the expected leaf water content which will vary by land-cover type. Maximum NDII for 2000-2007 was calculated from the MODIS standard surface reflectance data products and compared to maximum MODIS LAI for the same years. Mean leaf water content from MODIS was not significantly different from leaf data for most land cover types. However the large standard deviations indicated that canopy water content from NDII is not currently accurate for monitoring the incipient stages of plant water stress.

Paper Details

Date Published: 20 August 2009
PDF: 9 pages
Proc. SPIE 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI, 745409 (20 August 2009); doi: 10.1117/12.825401
Show Author Affiliations
E. Raymond Hunt Jr., USDA Agricultural Research Service (United States)
John J. Qu, George Mason Univ. (United States)
Xianjun Hao, George Mason Univ. (United States)
Lingli Wang, George Mason Univ. (United States)

Published in SPIE Proceedings Vol. 7454:
Remote Sensing and Modeling of Ecosystems for Sustainability VI
Wei Gao; Thomas J. Jackson, Editor(s)

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