A soil moisture algorithm using tilted Bragg approximation
In this paper, we present a soil moisture algorithm theoretically derived using the tilted Bragg proximation.
Engineering topics
Publications and source records attributed to Zyl, J. van.
In this paper, we present a soil moisture algorithm theoretically derived using the tilted Bragg proximation.
Most of the emphasis in active remote sensing of soil moisture has focused on higher resolution SAR data. We critically examine the existing soil moisture algorithms, and compare the performance of the different algorithms.
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In this paper, we examine the relationship between polarimetric parameters and soil moisture. For example, the co-polarization ratio is independent of surface roughness to the first order of the small perturbation approximation. As surface roughness increases, it can be shown that the co-polarization ratio depends on the surface slope under the tilted Bragg approximation. The coupling of the surface roughness to the co-polarization ratio is theoretically investigated. An algorithm to compensate the surface slope effect will be discussed. We will also study other polarimetric parameters such as the average alpha angle and eigenvalues to understand their relationship with soil moisture.
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It is important to monitor forests in order to understand the impacts of global climate changes on terrestrial ecosystems. To characterize the forest changes, it is useful to parameterize a forest using several parameters.
This paper provides a set of analytic equations that can be used to estimate system performance or to assist in the design of a system in that individual sources of height error can be balanced to minimize cost and maximize efficient use of resources.
This paper examines the relationship between the phase measured by a radar polarimeter and a radar interferometer.
Radar remote sensing instruments acquire data useful for geophysical investigations by measuring electromagnetic interactions with natural objects.
Quantitative results are to be provided (in the full paper) for two synthetic aperture radar (SAR) data missions from a space shuttle using the SIR-C/X-SAR in April and October 1994.
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In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne synthetic-aperture radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity structure and moisture characteristics.
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