Synergetic use of optical and microwave remote sensing data using models and specific features with respect to the sugar beet crop

Leeuwen, H.J.C. van; Clevers, J.G.P.W.; Rijckenberg, G.J.

doi:10.1109/igarss.1994.399276

Cited by 5 publications

(6 citation statements)

References 4 publications

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“…According to the model, the total backscatter at a co-polarised channel qq (σ°q q ), is the incoherent sum of the contribution from the vegetation (σ°v eg ) and the soil (σ°s oil ), and the two way attenuation of the vegetation layer (τ 2 ). For a given incidence angle, the co-polarised backscatter can be given by: The water cloud model has been modified and implemented differently by various authors [108][109][110][111] and despite its inconsistency during model implementation, it has found widespread use among the radar modelling community [112] with varying results. Dabrowska-Zielinska et al [113] found the soil moisture contribution to the backscattering coefficient to be predominant over that from the vegetation for C-band, θ = 23 o , while for L-band θ = 35 o , the backscattering coefficient was more sensitive to the vegetation contribution.…”

Section: Soil Moisture Retrieval Using Semi-empirical Scattering Modelsmentioning

confidence: 99%

Soil Moisture Retrieval from Active Spaceborne Microwave Observations: An Evaluation of Current Techniques

2009

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Abstract:The importance of land surface-atmosphere interactions, principally the effects of soil moisture, on hydrological, meteorological, and ecological processes has gained widespread recognition over recent decades. Its high spatial and temporal variability however, makes soil moisture a difficult parameter to measure and monitor effectively using traditional methods. Microwave remote sensing technology has demonstrated the potential to map and monitor relative soil moisture changes over large areas at regular intervals in time and also the opportunity of measuring, through inverse modelling, absolute soil moisture values. This ability has been demonstrated under a variety of topographic and land cover conditions using both active and passive microwave instruments. The purpose of this paper is to review the current status of soil moisture determination from active microwave remote sensing systems and to highlight the key areas of research that will have to be addressed to achieve routine use of the proposed retrieval approaches.

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Section: Soil Moisture Retrieval Using Semi-empirical Scattering Modelsmentioning

confidence: 99%

Soil Moisture Retrieval from Active Spaceborne Microwave Observations: An Evaluation of Current Techniques

2009

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“…The WCM has been used in many studies (Prévot et al 1993;van Leeuwen et al 1994;Champion 1996;Graham and Harris 2003;Maity et al 2004). However, the application of this model is limited to bare soil areas as the effects of soil surface roughness are not considered in it.…”

Section: Soil Moisture Estimation Models In Vegetated Areasmentioning

confidence: 99%

Accuracy Assessment of IWCM Soil Moisture Estimation Model in Different Frequency and Polarization Bands

Khabazan

Hosseini

Saradjian

et al. 2015

J Indian Soc Remote Sens

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Radar backscattering coefficient has high dependence to dielectric constant of soil and many efforts have been done in the past to estimate soil moisture using Synthetic Aperture Radar (SAR). Soil moisture estimation in vegetated areas has some limitations and difficulties due to the effects of vegetation cover and soil surface roughness on radar backscattering coefficient. One of the widely used soil moisture estimation models in vegetated areas is Water Cloud Model (WCM) which has been improved and known as Improved Water Cloud Model (IWCM) recently. One way of improving soil moisture estimation accuracy in vegetated areas is to use optimum frequency and polarization band so as to minimize the effects of soil surface roughness and vegetation cover on radar back scattering coefficient. In this research, the accuracies of IWCM in different frequencies and polarizations have been assessed. The results showed that the IWCM has its highest accuracy in L-band, HV polarization mode. Also, by using the IWCM, sensitivities of radar waves to moisture of 0-3, 3-6 and 0-6 cm soil depths have been studied. The results demonstrated that radar waves have more sensitivity to the moisture content of 0-3 cm soil depth.

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“…Texture measures have been demonstrated to be of utmost importance for the analysis of SAR images (Soares et al, 1997;Fukuda and Hirosawa, 1999;Simard et al, 2000). The synergistic use of optical and radar remote sensing holds new opportunities for land cover classification (Clevers et al, 2000;Kuplich et al, 2000) since the latter provides additional data on vegetation structure and on areas frequently covered by clouds (Leeuwen et al, 1994).…”

Section: Information Sourcesmentioning

confidence: 99%

Selection of imagery data and classifiers for mapping Brazilian semideciduous Atlantic forests

Carvalho

Clevers

Skidmore³

et al. 2004

International Journal of Applied Earth Observation and Geoinfor

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Synergetic use of optical and microwave remote sensing data using models and specific features with respect to the sugar beet crop

Cited by 5 publications

References 4 publications

Soil Moisture Retrieval from Active Spaceborne Microwave Observations: An Evaluation of Current Techniques

Soil Moisture Retrieval from Active Spaceborne Microwave Observations: An Evaluation of Current Techniques

Accuracy Assessment of IWCM Soil Moisture Estimation Model in Different Frequency and Polarization Bands

Selection of imagery data and classifiers for mapping Brazilian semideciduous Atlantic forests

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