Sensitivity Analysis of Multi-Temporal Sentinel-1 SAR Parameters to Crop Height and Canopy Coverage

Nasirzadehdizaji, Rouhollah; Şanlı, Füsun Balık; Abdikan, Saygın; Çakır, Ziyadin; Şekertekin, Aliihsan; Üstüner, Mustafa

doi:10.3390/app9040655

Cited by 160 publications

(86 citation statements)

References 29 publications

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“…The quad-pol Radar Vegetation Index (RVI) proposed by Kim and van Zyl (2009), was modified for dual-pol SAR data (Trudel et al, 2012) as, 4σ 0 HV /(σ 0 HH + σ 0 HV ). Later with Sentinel-1 like dual-pol data (VV-VH), few studies used the alternative formulation as, 4σ 0 VH /(σ 0 VV + σ 0 VH ) (Nasirzadehdizaji et al, 2019;Gururaj et al, 2019). Nevertheless, these studies are driven by the utilization of the cross-polarized component of the received wave.…”

Section: Introductionmentioning

confidence: 99%

Dual polarimetric radar vegetation index for crop growth monitoring using sentinel-1 SAR data

Mandal

Kumar

Ratha

et al. 2020

Remote Sensing of Environment

254

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Sentinel-1 Synthetic Aperture Radar (SAR) data has provided an unprecedented opportunity for crop monitoring due to its high revisit frequency and wide spatial coverage. The dual-pol Sentinel-1 SAR data is being utilized for the European Common Agricultural Policy (CAP) as well as for other national projects, which aim to provide Sentinel derived information to support crop monitoring networks. Among the several earth observation products identified for agriculture monitoring, the vegetation status indicator is one of the critical elements that require minimum end-user expertise. In literature, several experiments usually utilize the backscatter intensities to characterize crops. In this work, we jointly use both the scattered and received wave information to derive a new vegetation index (DpRVI) for Sentinel-1 dual-pol (VV-VH) SAR data. The DpRVI is derived using the degree of polarization

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Section: Introductionmentioning

confidence: 99%

Dual polarimetric radar vegetation index for crop growth monitoring using sentinel-1 SAR data

Mandal

Kumar

Ratha

et al. 2020

Remote Sensing of Environment

254

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“…Time-series backscatter analysis gives very useful information when one crop type in various fields is intended to be observed in terms of the monitoring programs and management practices. The results also indicate that there is relationship between Sentinel-1 SAR backscatter values and crop variables such as crop height and crop coverage during the different phonological stages (Nasirzadehdizaji, 2019).…”

Section: Sar Backscattering Analysismentioning

confidence: 73%

Application of Sentinel-1 Multi-Temporal Data for Crop Monitoring and Mapping

Nasirzadehdizaji

Şanlı

Çakır

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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The Synthetic Aperture Radar (SAR) technique superiority has provided various opportunities in agricultural studies mainly on crop monitoring and management. This has resulted in many different investigations and improvements in crop growth monitoring, crop disaster prediction and providing accurate information to precise farming. In this study, a time-series of Sentinel-1 SAR images were acquired throughout the agricultural season synchronously with the field measurements to investigate the temporal backscatter changes for different crop types. From the backscattering analysis, it was observed that each similar crop type in different test fields due to the distinct methods of irrigation and fertilization has shown different intensity values. However, they all follow a roughly identical backscattering trend during growing stages of the crop and useful information can be extracted, such as estimating irrigation and harvesting time according to the changes made in backscatters. In comparing with ascending orbit in VH and VV polarizations it has indicated that the homogeneity between SAR backscatters is high for each field with the same crop type in descending pass direction with VH polarization. In contrary, high-intensity values are recorded in VV polarization for entire crop types. It is also observed that polarimetric composite images for a different date are useful to roughly identify crop types, and validated with the application of classification methods in the study area. As preliminary results, it is demonstrated that SAR data provide useful information about crops status. Hence, Sentinel-1 SAR data are ideal preference due to its free availability and constant long-term data archive.

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“…Polarimetric indicators derived from S-1 data are not very well investigated over wheat and have shown moderate results for monitoring biophysical parameters compared to VV, VH and the VH/VV [6,7,21]. Nasirzadehdizaji et al [21] found moderate correlations between polarimetric parameters (entropy, anisotropy and alpha decompositions) and wheat height during the early growth stage.…”

Section: Introductionmentioning

confidence: 99%

Use of Sentinel-1 Multi-Configuration and Multi-Temporal Series for Monitoring Parameters of Winter Wheat

Gorrab

Ameline²,

Albergel

et al. 2021

Remote Sensing

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The present study aims to investigate the potential of multi-configuration Sentinel-1 (S-1) synthetic aperture radar (SAR) images for characterizing four wheat parameters: total fresh mass (TFM), total dry mass (TDM), plant heights (He), and water content (WC). Because they are almost independent on the weather conditions, we have chosen to use only SAR. Samples of wheat parameters were collected over seven fields (three irrigated and four rainfed fields) in Southwestern France. We first analyzed the temporal behaviors of wheat parameters (He, TDM, TFM and WC) between February and June 2016. Then, the temporal profiles of the S-1 backscattering coefficients (VV, VH), the difference (VH − VV), the sum of the polarizations (VH + VV) and their cumulative values are analyzed for two orbits (30 and 132) during the wheat-growing season (from January to July 2016). After that, S-1 signals were statistically compared with all crop parameters considering the impact of pass orbit, irrigation and two vegetative periods in order to identify the best S-1 configuration for estimating crop parameters. Interesting S-1 backscattering behaviors were observed with the various wheat parameters after separating irrigation impacts and vegetative periods. For the orbit 30 (mean incidence angle of 33.6°); results show that the best S-1 configurations (with coefficient of determination (R2) > 0.7) were obtained using the VV and VH + VV as a function of the He, TDM and WC, over irrigated fields and during the second vegetative period. For the orbit 132 (mean incidence angle of 43.4°), the highest dynamic sensitivities (R2 > 0.8) were observed for the VV and VH + VV configurations with He, TDM and TFM over irrigated fields during the first vegetative period. Overall, the sensitivity of S-1 data to wheat variables depended on the radar configuration (orbits and polarizations), the vegetative periods and was often better over irrigated fields in comparison with rainfed ones. Significant improvements of the determination coefficients were obtained when the cumulative (VH + VV) index was considered for He (R² > 0.9), TDM (R² > 0.9) and TFM (R² > 0.75) for irrigated fields, all along the crop cycle. The estimate of WC was more limited (R² > 0.6) and remained limited to the second period of the vegetation cycle (from flowering onwards). Whatever parameters were considered, the relative errors never exceeded 23%. This study has shown the importance of considering the agricultural practices (irrigation) and vegetative periods to effectively monitor some wheat parameters with S-1 data.

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Sensitivity Analysis of Multi-Temporal Sentinel-1 SAR Parameters to Crop Height and Canopy Coverage

Cited by 160 publications

References 29 publications

Dual polarimetric radar vegetation index for crop growth monitoring using sentinel-1 SAR data

Dual polarimetric radar vegetation index for crop growth monitoring using sentinel-1 SAR data

Application of Sentinel-1 Multi-Temporal Data for Crop Monitoring and Mapping

Use of Sentinel-1 Multi-Configuration and Multi-Temporal Series for Monitoring Parameters of Winter Wheat

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