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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Remote Sensing of Canopy Water Content: Scaling from Leaf Data to MODIS

Authors
item Hunt, Earle
item Qu, John - GEORGE MASON UNIVERSITY
item Hao, Xianjun - GEORGE MASON UNIVERSITY
item Wang, Lingli - GEORGE MASON UNIVERSITY

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: March 27, 2009
Publication Date: August 3, 2009
Citation: Hunt Jr, E.R., Qu, J.J., Hao, X., Wang, L. 2009. Remote sensing of canopy water content: Scaling from leaf data to MODIS [abstract]. International Society of Optical Engineering, Photonics Technical Program. p. 223.

Technical 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 = (R0.8 – R1.6)/(R0.8 + R1.6)] 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 aggregated by land cover type. However the large standard deviations indicated that canopy water content from NDII was not sufficiently accurate enough for monitoring the incipient stages of plant water stress.

Last Modified: 7/30/2014
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