A preliminary investigation of the potential of an all-weather satellite to discriminate dual-purpose crops

Context The application of optical satellite data for crop management is not uncommon in Australia. However, considerable cloud cover during winter or wet season limits the utility of optical satellite data for monitoring winter dual-purpose crops. Synthetic aperture radar (SAR) overcomes this shortcoming of optical remote sensing by self-emitting microwave energy that penetrates clouds. However, using satellite-based SAR for dual-purpose crop management in Australia is under-explored because of low knowledge and skills in interpreting SAR data. Aims This study aimed to employ foundational and easy-to-interpret SAR methods evaluating the potential of Sentinel-1 SAR for discriminating between wheat and canola fields in a mixed cropping system. Methods We used field-measured canola and wheat biomass data and Sentinel-1 ground range detected imagery to explore the correlation between wheat and canola biomass and backscattering coefficients by using maps, Wilcoxon’s rank-sum test, and Spearman’s rank correlation test. Key results The cross-polarised backscatter was positively linearly correlated with canola biomass (R = 0.74, P = 4.8e–05), whereas the wheat biomass negatively correlated with the backscatter associated with the co-polarisation channel (R = −0.44, P = 0.046). Conclusions Publicly available free-to-use Sentinel-1 SAR tracks wheat and canola productivity. Implications By using earth observation satellites, SAR can be used alone or combined with optical data to map crop types, phenology, and productivity reliably. This could guide the timing of management inputs such as crop irrigation and applying pesticides and fertilisers.

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Publication Details

Journal
Crop and Pasture Science
Published
2025-11-05
DOI
https://doi.org/10.1071/cp24225
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

A preliminary investigation of the potential of an all-weather satellite to discriminate dual-purpose crops

Johannes N. Theron, Shawn McGrath, Richard A. Crabbe, Ana Horta
Crop and Pasture Science
Remote Sensing in Agriculture
article

A preliminary investigation of the potential of an all-weather satellite to discriminate dual-purpose crops

Johannes N. Theron, Shawn McGrath, Richard A. Crabbe, Ana Horta
article en

Abstract

Context The application of optical satellite data for crop management is not uncommon in Australia. However, considerable cloud cover during winter or wet season limits the utility of optical satellite data for monitoring winter dual-purpose crops. Synthetic aperture radar (SAR) overcomes this shortcoming of optical remote sensing by self-emitting microwave energy that penetrates clouds. However, using satellite-based SAR for dual-purpose crop management in Australia is under-explored because of low knowledge and skills in interpreting SAR data. Aims This study aimed to employ foundational and easy-to-interpret SAR methods evaluating the potential of Sentinel-1 SAR for discriminating between wheat and canola fields in a mixed cropping system. Methods We used field-measured canola and wheat biomass data and Sentinel-1 ground range detected imagery to explore the correlation between wheat and canola biomass and backscattering coefficients by using maps, Wilcoxon’s rank-sum test, and Spearman’s rank correlation test. Key results The cross-polarised backscatter was positively linearly correlated with canola biomass (R = 0.74, P = 4.8e–05), whereas the wheat biomass negatively correlated with the backscatter associated with the co-polarisation channel (R = −0.44, P = 0.046). Conclusions Publicly available free-to-use Sentinel-1 SAR tracks wheat and canola productivity. Implications By using earth observation satellites, SAR can be used alone or combined with optical data to map crop types, phenology, and productivity reliably. This could guide the timing of management inputs such as crop irrigation and applying pesticides and fertilisers.

Crop and Pasture ScienceVol. 76(11)
Charles Sturt University (AU), Charles Darwin University (AU)
Openalex Percentile: Top 68%
Remote Sensing in Agriculture
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A preliminary investigation of the potential of an all-weather satellite to discriminate dual-purpose crops — Johannes N. Theron, Shawn McGrath, et al. · Crop and Pasture Science (2025) | TGRS Research Map | TGRS