NDLI: Passive microwave remote sensing of soil moisture, evapotranspiration, and vegetation properties during a growing season of cotton

Content Provider	IEEE Xplore Digital Library
Author	Tien, K.-J.C. Judge, J. Jacobs, J.M.
Copyright Year	2004
Description	Author affiliation: Dept. of Agric. & Biol. Eng., Florida Univ., Gainesville, FL, USA (Tien, K.-J.C.; Judge, J.)
Abstract	For accurate prediction of weather and near-term climate, root-zone soil moisture is one of the most crucial components driving the surface hydrological processes. The microwave brightness at low frequencies is very sensitive to soil moisture in the top few centimeters in most vegetated surfaces. The first Microwave Water and Energy Balance Experiment (MicroWEX-1) was conducted to gain better understanding of the interactions among microwave brightness, moisture, and energy fluxes at the land surface for a growing season of cotton. During the experiment, we observed the microwave brightness temperatures at 6.7 GHz and micrometeorological parameters. In this paper, we describe the polarization dependence of observed brightness temperatures; explore the relation of the brightness temperatures changes in soil moisture, ET, and vegetation properties during the growing season. We found that vertically polarized (V-pol) brightness temperatures were less sensitive to the changes in biomass and soil moisture than horizontally polarized (H-pol) temperatures. During the early glowing season, the brightness temperatures were polarization dependent and the temperatures became polarization independent as the biomass increased above 1 kg/m/sup 2/.
Starting Page	2795
Ending Page	2798
File Size	443936
Page Count	4
File Format	PDF
ISBN	0780387422
DOI	10.1109/IGARSS.2004.1369883
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-09-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Passive microwave remote sensing Soil moisture Vegetation Cotton Brightness temperature Polarization Land surface Biomass Temperature sensors Weather forecasting
Content Type	Text
Resource Type	Article

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