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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: The impact of radar incidence angle on soil moisture retrieval skill

Authors
item Crow, Wade
item Wagner, Wolfgang -
item Naeimi, Vahid -

Submitted to: Geoscience and Remote Sensing Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 20, 2009
Publication Date: July 15, 2010
Citation: Crow, W.T., Wagner, W., Naeimi, V. 2010. The impact of radar incidence angle on soil moisture retrieval skill. Geoscience and Remote Sensing Letters. 7(3):501-505.

Interpretive Summary: Estimates of surface soil moisture obtained from satellite sensors can potentially contribute to a wide range of important agricultural applications including fertilizer application, productivity forecasts, long-term precipitation forecast and irrigation scheduling. However, several important open design questions exist that must be settled before an optimal satellite system can be deployed. For active radar satellite systems, an important issue is the impact of incidence angle (i.e. the angle between the satellite line-of-site and a line perpendicular to the land surface) and whether accurate retrieval requires low incidence angle (i.e. satellite sensors that look straight down). To date, this question has not been definitively answered. This paper applies a novel approach to addressing the issue and argues that – in contrast to theoretical predictions – low incidence angle are not strictly required for radar sensors to accurately capture temporal variations in soil moisture. Such information will aid in the design and deployment of next-generation satellite sensors and enhance the impact of these sensors on agricultural applications.

Technical Abstract: The impact of measurement incidence angle on the accuracy of radar-based surface soil moisture retrievals is largely unknown due to discrepancies in theoretical backscatter models as well as limitations in the availability of sufficiently-extensive ground-based soil moisture observations for validation purposes. Here, we apply an evaluation technique for remotely-sensed surface soil moisture retrievals that does not require ground-based soil moisture observations to examine the sensitivity of retrieval skill in surface soil moisture retrievals to variations in incidence angle. Past results with the approach have shown that it is capable of detecting relative variations in the anomaly correlation between remotely-sensed surface soil moisture retrievals and ground-truth measurements. Application of the evaluation approach to the TU-Wien European Remote Sensing (ERS) scatterometer soil moisture data set over two regional-scale (~10002 km2) domains in the Southern United States indicates a relative reduction in correlation-based skill of between 20% and 30% when moving between the lowest (<26 degrees) and highest ERS (>50 degrees) incidence angle ranges. This relatively modest sensitivity to incidence angle is consistent with soil moisture retrieval noise predictions made using the TU-Wien WARP 5 backscatter model. However, the coupling of a bare soil backscatter model with the so-called ''vegetation water cloud'' model is shown to overestimate the impact of incidence angle variations on soil moisture retrieval skill.

Last Modified: 9/1/2014
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