Potential of Estimating Soil Moisture Under Vegetation Cover by Means of PolSAR

Hajnsek, Irena; Jagdhuber, Thomas; Schön, Helmut; Papathanassiou, Konstantinos

doi:10.1109/tgrs.2008.2009642

Cited by 271 publications

(230 citation statements)

References 26 publications

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“…Multiple polarization SAR allows for the simultaneous acquisition of backscattering information with two or four polarimetric modes and provides great potential for soil moisture inversion. By decomposing the polarimetric response, the corresponding contributions of vegetation cover and soil surface can be separated [40,41]. The soil moisture content can be estimated via the polarimetric parameters representing the soil surface characteristics [42].…”

Section: Study Areamentioning

confidence: 99%

The Potential Use of Multi-Band SAR Data for Soil Moisture Retrieval over Bare Agricultural Areas: Hebei, China

et al. 2015

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Abstract:The potential use of TerraSAR-X and Radarsat-2 data for soil moisture retrieval over bare agricultural areas was investigated using both empirical and semi-empirical approaches. For the empirical approach, the Support Vector Regression (SVR) model was used with two cases: (1) using only one C-band or X-band image; and (2) using a pair of C-band and X-band images jointly. For the semi-empirical approach, the modified Dubois model based on C-band and X-band SAR data was developed to estimate soil moisture content. The experiments were implemented over two bare agricultural areas, and in-situ measurements were carried out to assess the methods. The results showed that the TerraSAR-X and Radarsat-2 are suitable remote sensing tools for the estimation of surface soil moisture, with an accuracy of about 3 vol % (root mean square error, RMSE) over bare agricultural areas. Compared with the results obtained by Radarsat-2 data, TerraSAR-X data gives a slight improvement in estimating soil moisture. The accuracy of the soil moisture estimation was improved further when the two bands SAR data were used (RMSE of about 2.2 vol %) instead of only one. Moreover, the modified Dubois model showed comparable accuracy to the empirical model independent of the surface roughness.

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Section: Study Areamentioning

confidence: 99%

The Potential Use of Multi-Band SAR Data for Soil Moisture Retrieval over Bare Agricultural Areas: Hebei, China

et al. 2015

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“…In recent years, the advantages provided by polarimetric SAR (PolSAR) data for agricultural monitoring have been extensively studied for applications such as crop-type classification and mapping [16,17], crop phenology monitoring [18,19], productivity assessment based on the sensitivity of polarimetric parameters to indicators of crop conditions [20], and for the retrieval of soil moisture content underneath agricultural crops [21].…”

Section: Background and Rationalementioning

confidence: 99%

Temporal Polarimetric Behavior of Oilseed Rape (Brassica napus L.) at C-Band for Early Season Sowing Date Monitoring

Yang

Chen

et al. 2014

Remote Sensing

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Spatial monitoring of the sowing date plays an important role in crop yield estimation at the regional scale. The feasibility of using polarimetric synthetic aperture radar (SAR) data for early season monitoring of the sowing dates of oilseed rape (Brassica napus L.) fields is explored in this paper. Polarimetric SAR responses of six parameters, relying on polarization decomposition methods, were investigated as a function of days after sowing (DAS) during the entire growing season, by means of five consecutive Radarsat-2 images. A near-continuous temporal evolution of these parameters was observed, based on 88 oilseed rape fields. It provided a solid basis for determining the suitable temporal window and the best polarimetric parameters for sowing date monitoring. A high sensitivity of all polarimetric parameters to the DAS at different growing stages was shown. Simple linear models could be calibrated to estimate sowing dates at early growth OPEN ACCESS

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“…The proposed coherent similarity measure (17) is applied to fully polarimetric images acquired by the airborne E-SAR system of the German Aerospace Center (DLR) in the frame of the AgriSAR project [28]. PolInSAR data sets with 30-and 0-m spatial baseline configurations were collected over the Görmin test site, located in northern Germany, during a whole vegetation growth period, between two acquisition dates on April 19 [ Fig.…”

Section: Resultsmentioning

confidence: 99%

A New Coherent Similarity Measure for Temporal Multichannel Scene Characterization

Erten¹,

Reigber

Ferro-Famil

et al. 2012

IEEE Trans. Geosci. Remote Sensing

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Abstract-This paper proposes a new method for a measure of coherent similarity between temporal multichannel synthetic aperture radar (SAR) images and its implementation to change detection application. The method is based on mutual information (MI) from information theory. The MI measures the amount of information in common between coherent temporal multichannel SAR acquisitions. In order to develop an algorithm for all kinds of SAR images, such as interferometric SAR, polarimetric-interferometric SAR (PolInSAR), and partial PolIn-SAR, first, the joint density function of temporal multichannel images based on their second-order statistics has been derived. Then, the derived joint density function is used to calculate an analytical expression for the MI between temporal images, which is assumed to be maximal if the temporal images are identical. Although, in this paper, a new coherent similarity measure has analytically been derived for temporal polarimetric SAR images based on complex Wishart process in time, since the mathematical formulation is general, it can equally well be implemented into any kind of multivariate remote sensing data, such as multispectral optical and interferometric images after small continuation. This derived quantity has been implemented for change detection application whose aim is to characterize the temporal behavior of the acquisitions. A comparison between the proposed and the other well-known change detection methods by means of scene characterization is shown, describing the advantages due to the fact that the proposed change detector involves almost every facet of applied change detection.

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Potential of Estimating Soil Moisture Under Vegetation Cover by Means of PolSAR

Cited by 271 publications

References 26 publications

The Potential Use of Multi-Band SAR Data for Soil Moisture Retrieval over Bare Agricultural Areas: Hebei, China

The Potential Use of Multi-Band SAR Data for Soil Moisture Retrieval over Bare Agricultural Areas: Hebei, China

Temporal Polarimetric Behavior of Oilseed Rape (Brassica napus L.) at C-Band for Early Season Sowing Date Monitoring

A New Coherent Similarity Measure for Temporal Multichannel Scene Characterization

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