RADARSAT-2 Polarimetric SAR Response to Crop Biomass for Agricultural Production Monitoring

Wiseman, Grant; McNairn, Heather; Homayouni, Saeid; Shang, Jiali

doi:10.1109/jstars.2014.2322311

Cited by 183 publications

(137 citation statements)

References 43 publications

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“…Fieuzal et al [27] investigated the temporal signatures of the radar backscattering intensity over rapeseed and wheat, and found that the signal dynamic depended on the crops and their associated phenological stages. Recently Wiseman et al [28] were able to detect when wheat entered the milking stage, a useful indicator for the timing of harvest, when investigating RADARSAT-2 polarimetric SAR responses of 21 parameters on canola, corn, soybean, and spring wheat crops over a six-week period for a site in western Canada.…”

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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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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“…These results also highlighted the different sensitivity of these parameters to rape biomass, LAI, and stem height. The good performance of several polarimetric parameters has also been reported for canola stem height and LAI inversion in the literature [1,2]. To determine the most effective empirical inversion models for the inversion of the three growth parameters, we compared the performance of the linear, logarithmic, quadratic, power, and exponential models through an analysis of their coefficients of determination and their physical relationship with scattering mechanisms.…”

Section: Discussionmentioning

confidence: 99%

“…To understand the sensitivity of polarisation information to rape biomass, LAI, and stem height, we extracted 27 polarisation parameters from SLC SAR datasets in the literature [1,2] and analysed their evolution as a function of DAS. From these analyses, we found that many C-band polarisation observables were significantly correlated with rape biomass, LAI, and stem height.…”

Section: Discussionmentioning

confidence: 99%

“…To reduce the influence of uncontrolled factors on polarimetric parameters for the same DAS, mean values of all of the fields with the same DAS were calculated to analyse dynamic changes in the 27 polarimetric parameters. The shape and aspect of rape changed substantially during its growth cycle, which results in changes in its polarimetric scattering and biomass [2]. Thus, the entire growth cycle of rape was divided into five stages according to their Biologische Bundesanstalt Bundessortenamt und CHemische Industrie (BBCH) [25], SAR data acquisition date, and DAS.…”

Section: Temporal Polarimetric Response Of Rapementioning

confidence: 99%

“…Its planting area has increased in recent years; therefore, the importance of this crop to global markets is clearly increasing, and as such, there has been much interest in accurately monitoring its growth and estimating yields. Crop yield is a critical indicator of national food security and food trade [2]. Forecasting yield is not a trivial task, especially given that the global population is expected to reach about 9 billion in 2050 [3,4].…”

Section: Introductionmentioning

confidence: 99%

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Rape (Brassica napus L.) Growth Monitoring and Mapping Based on Radarsat-2 Time-Series Data

Zhang

Chen

et al. 2018

Remote Sensing

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Abstract:In this study, 27 polarimetric parameters were extracted from Radarsat-2 polarimetric synthetic aperture radar (SAR) at each growth stage of the rape crop. The sensitivity to growth parameters such as stem height, leaf area index (LAI), and biomass were investigated as a function of days after sowing. Based on the sensitivity analysis, five empirical regression models were compared to determine the best model for stem height, LAI, and biomass inversion. Of these five models, quadratic models had higher R 2 values than other models in most cases of growth parameter inversions, but when these results were related to physical scattering mechanisms, the inversion results produced overestimation in the performance of some parameters. By contrast, linear and logarithmic models, which had lower R 2 values than the quadratic models, had stable performance for growth parameter inversions, particularly in terms of their performance at each growth stage. The best biomass inversion performance was acquired by the volume component of a quadratic model, with an R 2 value of 0.854 and root mean square error (RMSE) of 109.93 g m −2 . The best LAI inversion was also acquired by a quadratic model, but used the radar vegetation index (Cloude), with an R 2 value of 0.8706 and RMSE of 0.56 m 2 m −2 . Stem height was acquired by scattering angle alpha (α) using a logarithmic model, with an R 2 of 0.926 value and RMSE of 11.09 cm. The performances of these models were also analysed for biomass estimation at the second growth stage (P2), third growth stage (P3), and fourth growth stage (P4). The results showed that the models built at the P3 stage had better substitutability with the models built during all of the growth stages. From the mapping results, we conclude that a model built at the P3 stage can be used for rape biomass inversion, with 90% of estimation errors being less than 100 g m −2 .

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Trends in Satellite Time Series Processing for Vegetation Phenology Monitoring

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VERRELST

2024

Multitemporal Earth Observation Image Analysis

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RADARSAT-2 Polarimetric SAR Response to Crop Biomass for Agricultural Production Monitoring

Cited by 183 publications

References 43 publications

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

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

Rape (Brassica napus L.) Growth Monitoring and Mapping Based on Radarsat-2 Time-Series Data

Trends in Satellite Time Series Processing for Vegetation Phenology Monitoring

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