Potential of fully polarimetric SAR data for crops biophysical parameters retrieval

Yang, Hao; Yang, Xiaodong; Xu, Xingang; Gao, Zhongling; Li, Cunjun; Wang, Jihua; Zhao, Chunjiang

doi:10.1109/agro-geoinformatics.2012.6311620

Cited by 4 publications

(5 citation statements)

References 13 publications

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“…This peak can be explained by the presence of mature pods at the end of the ripening phenological stage. 17,54,55 On DoY 170 (BBCH stage 90-Senescence), the volume scattering mechanism decreases [dot in zone 6 regarding the Cloude-Pottier decomposition, Fig. 7(b)] since the vegetation reaches the senescence phenological stage.…”

Section: Scattering Mechanism Analysismentioning

confidence: 99%

“…This decrease can be explained by a strong decline of the water content of the top vegetation layer (from 60 to 30% 39 ), inducing higher wave penetration into the soil and thus a decrease of the volume scattering. 55 It is interesting to notice that this decrease cannot be perceived on the backscattering coefficient σ°H V temporal profiles, 17 showing that volume scattering is more sensitive to the plant water content than σ°H V . Moreover, from DoY 98 to DoY 184, radar signal is not affected by the TSM.…”

Section: Scattering Mechanism Analysismentioning

confidence: 99%

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Contribution of multitemporal polarimetric synthetic aperture radar data for monitoring winter wheat and rapeseed crops

Betbeder

Fieuzal

Philippets

et al. 2016

J. Appl. Remote Sens

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International audienceThis paper aims to evaluate the contribution of multitemporal polarimetric synthetic aperture radar (SAR) data for winter wheat and rapeseed crops parameters [height, leaf area index, and dry biomass (DB)] estimation, during their whole vegetation cycles in comparison to backscattering coefficients and optical data. Angular sensitivities and dynamics of polarimetric indicators were also analyzed following the growth stages of these two common crop types using, in total, 14 radar images (Radarsat-2), 16 optical images (Formosat-2, Spot-4/5), and numerous ground data. The results of this study show the importance of correcting the angular effect on SAR signals especially for copolarized signals and polarimetric indicators associated to single-bounce scattering mechanisms. The analysis of the temporal dynamic of polarimetric indicators has shown their high potential to detect crop growth changes. Moreover, this study shows the high interest of using SAR parameters (backscattering coefficients and polarimetric indicators) for crop parameters estimation during the whole vegetation cycle instead of optical vegetation index. They particularly revealed their high potential for rapeseed height and DB monitoring [i.e., Shannon entropy polarimetry (r2=0.70) and radar vegetation index (r2=0.80), respectively

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Section: Scattering Mechanism Analysismentioning

confidence: 99%

Section: Scattering Mechanism Analysismentioning

confidence: 99%

Contribution of multitemporal polarimetric synthetic aperture radar data for monitoring winter wheat and rapeseed crops

Betbeder

Fieuzal

Philippets

et al. 2016

J. Appl. Remote Sens

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show abstract

“…To overcome this noise and generate square pixels, multilooking is carried out. In this study 14.15m was the resultant spatial resolution of the multilooked image (Yang et al, 2011).…”

Section: Multilookingmentioning

confidence: 99%

A Simplified Sub-Surface Soil Salinity estimation using Synergy of Sentinel-1 SAR and Sentinel-2 multispectral satellite data, for early stages of wheat crop growth in Rupnagar, Punjab, India

Tripathi

Tiwari

2020

Preprint

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Soil salinity has today become a highly disastrous phenomenon that is responsible for crop failure worldwide and specially in countries with low farmer incomes and food insecurity. Soil salinity is often caused due to water accumulation in fields due to unscientific flood irrigation wherein plants intake the water leaving salts behind. It is, however, the sub-surface soil salinity that affects the plant growth. These salts in sub-surface soil get trapped in root nodules of plants and prevent further water intake. There have been very few studies conducted for sub-surface soil salinity estimation. Hence this study aims to estimate sub-surface soil salinity (at 60 cm depth) for early stage of wheat crop growth in a simplified manner using freely available satellite data, which is a novel feature and prime objective in this study. The study utilizes Sentinel-1 SAR (Synthetic Aperture RADAR) data for backscatter coefficient generation, Sentinel-2 multispectral data for NDSI (Normalised Differential Salinity Index) generation and on ground equipment for direct collection of soil electrical conductivity. The data were collected for two dates in November and December 2019 and one date for January 2020 during the early stage of wheat crop growth. The dates were selected keeping in mind the satellite pass over the study area of Rupnagar on the same day. Ordinary Least Squares regression was used for modelling which gave R2-statistics of 0.99 and 0.958 in training and testing phase and root mean square error of 1.92 in modelling for soil salinity estimation.

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“…To overcome this noise and generate square pixels, multilooking is carried out. In this study, 14.15 m ($14 m) was the resultant spatial resolution of the multilooked image (Yang et al, 2012).…”

Section: Multilookingmentioning

confidence: 99%

A simplified subsurface soil salinity estimation using synergy of SENTINEL‐1 SAR and SENTINEL‐2 multispectral satellite data, for early stages of wheat crop growth in Rupnagar, Punjab, India

Tripathi

Tiwari

2021

Land Degrad Dev

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Soil salinity has become a highly disastrous phenomenon responsible for crop failure worldwide, especially in countries with low farmer incomes and food insecurity. Soil salinity is often due to water accumulation in fields caused by improper flood irrigation whereby plants take up the water leaving salts behind. It is, however, the subsurface soil salinity that affects plant growth. This soil salinity prevents further water intake. There have been very few studies conducted for subsurface soil salinity estimation. Therefore our study aimed to estimate subsurface soil salinity (at 60 cm depth) for the early stage of wheat crop growth in a simplified manner using freely available satellite data, which is a novel feature and prime objective in this study. The study utilises SENTINEL‐1 SAR (synthetic aperture RADAR) data for backscatter coefficient generation, SENTINEL‐2A multispectral data for NDSI (normalised differential salinity index) generation and on‐ground equipment for direct collection of soil electrical conductivity (EC). The data were collected for two dates in November and December 2019 and one date in January 2020 during the early stage of wheat crop growth. The dates were selected keeping in mind the satellite pass over the study area of Rupnagar on the same day. Ordinary least squares regression was used for modelling which gave R2‐statistics of 0.99 and 0.958 in the training and testing phase and root mean square error (RMSE) of 1.92 and mean absolute error (MAE) of 0.78 in modelling for soil salinity estimation.

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Potential of fully polarimetric SAR data for crops biophysical parameters retrieval

Cited by 4 publications

References 13 publications

Contribution of multitemporal polarimetric synthetic aperture radar data for monitoring winter wheat and rapeseed crops

Contribution of multitemporal polarimetric synthetic aperture radar data for monitoring winter wheat and rapeseed crops

A Simplified Sub-Surface Soil Salinity estimation using Synergy of Sentinel-1 SAR and Sentinel-2 multispectral satellite data, for early stages of wheat crop growth in Rupnagar, Punjab, India

A simplified subsurface soil salinity estimation using synergy of SENTINEL‐1 SAR and SENTINEL‐2 multispectral satellite data, for early stages of wheat crop growth in Rupnagar, Punjab, India

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