Polarimetric Sar Model for Soil Moisture Estimation Over Vineyards at C-Band

Ballester-Berman, J. David; Vicente-Guijalba, Fernando; López-Sánchez, Juan M.

doi:10.2528/pier13071702

Cited by 21 publications

(22 citation statements)

References 43 publications

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“…The SAR signal at L-band is sensitive to soil moisture in spite of the increment of vegetation; therefore, L-band is more suitable for soil moisture retrieval than C-band [30,32]. However, most orbiting sensors operate at higher frequencies, and the SAR signal at L-band is still affected by vegetation, which should also be corrected [33][34][35]. Thus, it is still necessary to conduct research at high frequencies.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery

et al. 2015

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Accurate soil moisture retrieval of a large area in high resolution is significant for plateau pasture. The object of this paper is to investigate the estimation of volumetric soil moisture in vegetated areas of plateau pasture using fully polarimetric C-band RADARSAT-2 SAR (Synthetic Aperture Radar) images. Based on the water cloud model, Chen model, and Dubois model, we proposed two developed algorithms for soil moisture retrieval and validated their performance using experimental data. We eliminated the effect of vegetation cover by using the water cloud model and minimized the effect of soil surface roughness by solving the Dubois equations. Two experimental campaigns were conducted in the Qinghai Lake watershed, northeastern Tibetan Plateau in September 2012 and May 2013, respectively, with simultaneous satellite overpass. Compared with the developed Chen model, the predicted soil moisture given by the developed Dubois model agreed better with field measurements in terms of accuracy and stability. The RMSE, R 2 , and RPD value of the developed Dubois model were (5.4, 0.8, 1.6) and (3.05, 0.78, 1.74) for the two experiments, respectively. Validation results indicated that the developed Dubois model, needing a minimum of prior information, satisfied the requirement for soil moisture inversion in the study region.

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Section: Introductionmentioning

confidence: 99%

Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery

et al. 2015

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“…It is very similar to the approach by [36] in that it explicitly estimates the variable large-scale roughness ψ, here associated with the hummocky terrain sketched in Fig. 3.…”

Section: ) Mtv Decompositionmentioning

confidence: 77%

“…However, attributing the volume component to vegetation scattering is difficult in the presence of higher-order surface scattering, as the higher-order contribution that is not included in the X-Bragg model is polarimetrically indistinguishable from vegetation scattering in the framework by [36] (see Sec. IV-A2).…”

Section: ) Mtv Decompositionmentioning

confidence: 99%

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Fine-Scale SAR Soil Moisture Estimation in the Subarctic Tundra

Zwieback¹,

Berg²

2018

Preprint

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In the subarctic tundra, soil moisture information can benefit permafrost monitoring and ecological studies, but fine-scale remote sensing approaches are lacking. We explore the suitability of C-band SAR, paying attention to two challenges soil moisture retrieval faces. First, the microtopography and the heterogeneous organic soils impart unique microwave scattering properties, even in absence of noteworthy shrub cover. Empirically, we find the polarimetric response is highly random (entropies > 0.7). The randomness limits the applicability of purely polarimetric approaches to soil moisture estimation, as it causes a tailor-made decomposition to break down. For comparison, the L-band scattering response is more surface-like, also in terms of its angular characteristics. The second challenge concerns the large spatial but small temporal variability of soil moisture observed at our site. Accordingly, the Radarsat-2 C-band backscatter has a limited dynamic range (∼2 dB). However, contrary to polarimetric indicators, it shows a clear surface soil moisture signal. To account for the small dynamic range while retaining a 100 m spatial resolution, we embed an empirical time-series model in a Bayesian framework. This framework adaptively pools information from neighboring grid cells, thus increasing the precision. The retrieved soil moisture index achieves correlations of 0.3-0.5 with in-situ data at 5cm depth and, upon calibration, RMSEs of < 0.04 m 3 m −3 . As this approach is applicable to Sentinel-1 data, it can potentially provide frequent soil moisture estimates across large regions. In the long term, L-band data hold greater promise for operational retrievals.

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“…With its all-weather and all-time capabilities, the Synthetic Aperture Radar (SAR) has great potentials, such as in geology, forestry, agriculture and oceanography [1][2][3][4][5][6]. As a special mode, the bistatic SAR (BiSAR) systems have been attracting scientists' interests in the last few years, and a lot of BiSAR experiments have been carried out.…”

Section: Introductionmentioning

confidence: 99%

A Modified Synchronization Method for Bistatic Sar

Shao¹,

Liu²,

Chen³

et al. 2014

PIER C

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Abstract-It is a common synchronization approach of the bistatic Synthetic Aperture Radar (BiSAR) with spaceborne/stationary configuration that obtains synchronization information from a direct signal. An easy and effective synchronization method is using the direct signal as a match filter to compress the echo for range compression. This method requires a high signal-to-noise ratio (SNR) of the direct signal, because the low SNR of the direct signal affects the synchronization result. Furthermore, it affects the imaging quality and bistatic-InSAR (BiInSAR) result seriously. Two factors affect the SNR of the direct signal: low gain and saturation. The transmitter and receiver antenna beam patterns cause the received direct signal's power variance during the exposure time. The requirement of high gain and no saturation cannot be satisfied simultaneously during the exposure time when the receiver sub-system does not have automatic gain control (AGC). In this paper, a modified synchronization approach is proposed. The proposed method not only tolerates the low gain and saturation, but also does not require the parameters of the transmitted signal, such as FM chirp rate, bandwidth and transmitted pulse length. The proposed method makes the gain design of the synchronization channel easy. The experiment results verifies the effectiveness of the proposed approach.

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Polarimetric Sar Model for Soil Moisture Estimation Over Vineyards at C-Band

Cited by 21 publications

References 43 publications

Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery

Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery

Fine-Scale SAR Soil Moisture Estimation in the Subarctic Tundra

A Modified Synchronization Method for Bistatic Sar

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