Deriving land surface parameters from three different vegetated sites with the ELBARA 1.4-GHz passive microwave radiometer

Richard A. M. De Jeu; Thomas Holmes; Manfred Owe

doi:10.1117/12.512494

24 February 2004 Deriving land surface parameters from three different vegetated sites with the ELBARA 1.4-GHz passive microwave radiometer

Richard A. M. De Jeu, Thomas Holmes, Manfred Owe

Author Affiliations +

Proceedings Volume 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V; (2004) https://doi.org/10.1117/12.512494
Event: Remote Sensing, 2003, Barcelona, Spain

Abstract

A methodology was recently developed to estimate the land surface parameters soil moisture, soil temperature and vegetation optical depth on a global scale by using passive microwave remote sensing. This methodology is general, in a way that it does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes, and can be used with microwave observations at different wavelengths. However, several algorithms in this approach are somewhat empirical, and the vegetation component in this methodology is still difficult to understand and interpret. A follow up field experiment was planned for April 2003 to address some of these issues. The experiment was conducted at a controlled meteorological field site in Wageningen (The Netherlands). Three different plots, a bare soil, a soil with short grass (reference site), and a site with growing grass vegetation were selected. Several hydro-meteorological parameters were monitored extensively at each site, including the radiobrightness temperatures from the ELBARA 1.4 GHz passive microwave radiometer. This paper gives a description of this field experiment and will demonstrate several effects of vegetation on the radiobrightness temperature.

Citation Download Citation

Richard A. M. De Jeu, Thomas Holmes, and Manfred Owe "Deriving land surface parameters from three different vegetated sites with the ELBARA 1.4-GHz passive microwave radiometer", Proc. SPIE 5232, Remote Sensing for Agriculture, Ecosystems, and Hydrology V, (24 February 2004); https://doi.org/10.1117/12.512494

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