Speaker
Description
The ESA BIOMASS mission provides spaceborne P-band fully polarimetric SAR observations primarily designed to characterize forests and their contribution to the carbon cycle [1]. Although it is not its primary goal, these observations also offer an opportunity to explore agricultural applications, for which the sensitivity and usefulness of P-band remain insufficiently understood. Radar responses to crop development depend on wavelength, polarization, and vegetation structure [2], while previous airborne studies demonstrate the relevance of multifrequency polarimetry, including P-band observations, to agricultural classification [3]. The approximately 70 cm wavelength of BIOMASS motivates investigation of tall and dense crops, where sensitivity at shorter wavelengths can become limited as vegetation develops. However, the information available from P-band observations, and the conditions under which soil contributions or ambiguous vegetation responses limit its interpretation, require further assessment.
This work investigates these questions using sugarcane in the Cauca Valley, Colombia. Sugarcane is a suitable case study because of its substantial height, dense canopy, and long cultivation cycle. Previous research using X-, C-, and L-band observations established both the potential of SAR for sugarcane monitoring and the dependence of its sensitivity on observation configuration and crop conditions [4]. The area of interest in the Cauca Valley is ideal for such a study because cultivation and harvesting occur throughout the year, providing fields at different developmental stages within individual satellite acquisitions. Regarding field and external data, in the framework of the EU-funded DINOSAR project [5], which integrates optical, infrared, and SAR observations to support agricultural monitoring, information such as field boundaries and in-situ measured biophysical variables (fresh biomass, stalk height, etc.) of the sugarcane are available for some dates.
Building on the initial investigation presented at EUSAR 2026 [6], this contribution brings together preliminary evidence of crop sensitivity and an ongoing extension to a broader BIOMASS dataset and a deeper analysis of polarimetric responses. The initial results show differences in total backscattered power and individual polarization channels across fields with different crop ages. Polarization ratios, the radar vegetation index, and the magnitude and phase of the co-polar correlation provide additional contrasts. The observed relationships suggest sensitivity to crop development but also reveal substantial variability among fields at similar estimated ages, particularly in later stages. These findings motivate an assessment of both the information content and the ambiguity of P-band signatures.
The extended investigation targets all available BIOMASS acquisitions over the study area up to the workshop in November 2026. Existing sugarcane field boundaries provide consistent spatial units for extracting polarimetric features and comparing observations. The analysis framework addresses differences among fields within individual acquisitions and changes within the same fields across available dates. Sentinel-1 time series provide complementary temporal context through estimated wide-coverage season-start dates and signatures associated with harvesting, following SAR-based approaches to harvest monitoring [7]. These estimates serve as indirect references for interpreting BIOMASS responses, with their uncertainty explicitly recognized. Crop age provides a developmental context without implying identical vegetation conditions among fields of similar age.
The central objective is to assess which P-band features provide interpretable information about crop development and whether their combined behavior supports discrimination among broad conditions such as early regrowth, developed vegetation, and recently harvested fields. The ongoing analysis examines the consistency of these relationships across fields and acquisitions, with particular attention to contrasting signatures at similar estimated crop ages. Acquisition spacing and the availability of external references also form part of the assessment, since sensitivity to crop conditions alone does not establish the ability to monitor individual management events.
Preliminary findings demonstrate observable agricultural signatures in BIOMASS data and support further investigation of a mission whose primary objectives concern forests. This contribution uses this evidence to explore the scope for crop-status discrimination, the complementary role of Sentinel-1, and the circumstances in which P-band observations remain difficult to interpret. Its emphasis is on establishing the potential and practical limits of BIOMASS for crop studies through an expanding sugarcane case study.
References
[1] K. Scipal et al., “BIOMASS: ESA’s P-band SAR mission,” Proceedings of the IEEE, 2026.
[2] H. Joerg, M. Pardini, I. Hajnsek, and K. P. Papathanassiou, “Sensitivity of SAR Tomography to the Phenological Cycle of Agricultural Crops at X-, C-, and L-band,” IEEE JSTARS, vol. 11, no. 9, pp. 3014–3029, 2018.
[3] D. H. Hoekman and M. A. M. Vissers, “A new polarimetric classification approach evaluated for agricultural crops,” IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 12, pp. 2881–2889, 2003.
[4] N. Baghdadi, N. Boyer, P. Todoroff, M. El Hajj, and A. Bégué, “Potential of SAR sensors TerraSAR-X, ASAR/ENVISAT and PALSAR/ALOS for monitoring sugarcane crops on Reunion Island,” Remote Sensing of Environment, vol. 113, no. 8, pp. 1724–1738, 2009.
[5] DINOSAR, “Diagnostic that Integrates Optical, infrared and Synthetic Aperture Radar data,” EU-funded project, Grant Agreement 101129646, 2024–2026.
[6] J. M. Lopez-Sanchez, V. Cazcarra-Bes, A. Mestre-Quereda, C. Mosquera, and C. Van der Sande, “Initial Analysis on the Sensitivity of BIOMASS P-band Quad-Pol SAR Images to Agricultural Crops,” EUSAR 2026.
[7] O. Kavats, D. Khramov, K. Sergieieva, and V. Vasyliev, “Monitoring Harvesting by Time Series of Sentinel-1 SAR Data,” Remote Sensing, vol. 11, no. 21, article 2496, 2019.