Soil Surface Moisture From EnviSat RA-2: From Modelling Towards Implementation
This paper presents the current status of ongoing research into the extraction of soil surface moisture data from Radar Altimeter backscatter. One of the motivations for this work is to facilitate comparisons with GRACE data over specific targets such as
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Soil Surface Moisture From EnviSat RA-2: From Modelling Towards Implementation S.M.S. Bramer and P.A.M. Berry
Abstract This paper presents the current status of ongoing research into the extraction of soil surface moisture data from Radar Altimeter backscatter. One of the motivations for this work is to facilitate comparisons with GRACE data over specific targets such as the Okavango Delta. Natural land targets for the monitoring of Radar Altimeter backscatter have previously been identified and modelled, utilising data provided by the ERS-1 Geodetic and 35-day Missions. These spatial models have been employed for cross-calibration between ERS-1/2 ice and ocean mode sigma0. The inherent variability of all but a few desert regions meant that the original techniques could not be used beyond these calibration zones. A new automated technique has made it possible to develop models of wetter regions with the aim of taking these models as close to “dry earth” conditions as possible. In parallel with this process a semi-empirical model of Radar Altimeter backscatter, which makes use of engineering and scientific parameters, has been developed and is undergoing final calibration. The use of the spatial models in conjunction with the new semi-empirical backscatter model will enable predictions of soil surface moisture levels using values provided by EnviSat RA-2 backscatter.
27.1 Introduction This paper discusses recent developments in the understanding of behaviour of overland radar altimeter sigma0 in response to surface moisture. The automated creation of spatial “dry earth” sigma0 models is discussed together with a new semi-empirical model. Synergistically, the two allow the creation of surface roughness maps together with prediction of sigma0 response to surface moisture.
27.2 Data The radar altimeter data used in this study have been reprocessed using a rule-based expert system (Berry et al., 1997) to optimise the recovery of the rangeto-surface. This works by selecting one of eleven retracking algorithms based on the waveform characteristics. The system has been under development for several years and has been tuned for ERS-1/2, Envisat, TOPEX and Jason-1. The ERS-1 Geodetic Mission data-set has been used for the creation of spatial sigma0 models, together with data from the ERS-2 35-day mission (Capp, 2001). A number of cycles of Envisat 35-day data (Benveniste et al., 2002) have been used to illustrate global sigma0 variation.
27.3 Sigma0 Variation from Envisat Ku Band S.M.S. Bramer () EAPRS Lab, De Montfort University, Leicester LE1 9BH, UK e-mail: [email protected]
As a first step in the illustration of the use of sigma0 in the recovery of soil moisture signals, Fig. 27.1
S.P. Mertikas (ed.), Gravity, Geoid and Earth Observation, International Association of Geodesy Symposia 135, DOI 10.1007/978-3-642-10634-7_27, © Springer-Verlag Berlin Heidelberg 2010
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Fig. 27.1 Envisat sigma0 (dB) cycle 22 (December 2003)
Fig. 27.2 Envisat sigma0 (dB) cycle 28 (June 2004)
S.M.S. Bramer and P.A.M. Berry
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