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Scientific publications
DINOSAR: Integration of Copernicus Optical and Radar Satellite Images for Sugarcane Monitoring in the Cauca Valley
Citation: Mestre-Quereda, A., Lopez-Sanchez, J. M., Luo, J., Villarroya-Carpio, A., Mosquera, C., Lozano, J., Quinones, J., van der Sande, C., Idrovo, A., Skarli, A., Pelgrum, H., Zalite, K., van Bergen, P., Verhoek, A., Hoekman, D., Vissers, M., Kooij, B., & Noort, M. (2025). DINOSAR: Integration of Copernicus Optical and Radar Satellite Images for Sugarcane Monitoring in the Cauca Valley. ESA Living Planet Symposium, Wien, Austria. Zenodo. https://doi.org/10.5281/zenodo.20748975
Abstract: Earth Observation satellites collecting both optical and SAR imagery deliver frequent, essential data for monitoring crops throughout the growing season. The integrated approach is being initially tested for sugarcane monitoring in the Cauca Valley (Colombia), but it is planned to extend it to other crop types and geographic area. Within the DINOSAR Project, we introduce an innovative approach that integrates data from both sensor types. The method uses Dynamical System’s Theory to optimally fuse radar, optical, and auxiliary data. It also enables the incorporation of in-situ measurements and crop growth models, resulting in more accurate and reliable crop monitoring. The integration methodology is designed to help farmers enhance productivity while lowering costs related to fertilization, pesticide use, and water consumption, ultimately reducing environmental impact.
Integrating Synthetic Aperture Radar Data into a Monitoring Tool for Sugarcane in the Cauca Valley, Colombia
Citation: Mestre-Quereda, A., Lopez-Sanchez, J. M., Martinez-Marin, T., Cazcarra-Bes, V., Mosquera, C., Lozano, J., Quinones, J., Pelgrum, H., Skarli, A., van der Sande, C., Idrovo, A., Hoekman, D., & Vissers, M. (2026, June 17). Integrating Synthetic Aperture Radar Data into a Monitoring Tool for Sugarcane in the Cauca Valley, Colombia. Proceedings of the 16th European Conference on Synthetic Aperture Radar (EUSAR2026). European Conference on Synthetic Aperture Radar (EUSAR), Baden-Baden (Germany). https://doi.org/10.5281/zenodo.20734802
Abstract: A methodology to integrate SAR data with optical imagery to implement a reliable monitoring system for sugarcane under all weather conditions has been developed in the framework of the EU-funded DINOSAR project. An extensive field campaign was conducted to collect key biophysical parameters, e.g., stem count, plant height, and fresh biomass, for developing a model that establishes the relationship between these sugarcane traits and radar observables (backscatter and coherence). Building upon this model and the available models based on optical imagery, an integrated algorithm based on dynamical systems theory has been formulated and tested. This method synergistically combines SAR and optical data streams to generate a robust and accurate information source for sugarcane decision-support tools. Results of vegetation biomass estimation along a whole year demonstrate that such an integration approach outperforms methods based only on regressions (machine learning) or on only one type of input data (SAR or optical).
Initial Analysis on the Sensitivity of BIOMASS P-band Quad-Pol SAR Images to Agricultural Crops
Citation: Lopez-Sanchez, J. M., Cazcarra-Bes, V., Mestre-Quereda, A., Mosquera, C., & van der Sande, C. (2026, June 17). Initial Analysis on the Sensitivity of BIOMASS P-band Quad-Pol SAR Images to Agricultural Crops. Proceedings of the 16th European Conference on Synthetic Aperture Radar (EUSAR2026). European Conference on Synthetic Aperture Radar (EUSAR), Baden-Baden (Germany). https://doi.org/10.5281/zenodo.20733721
Abstract: P-band quad-pol images acquired by the recently launched BIOMASS mission over a region in Colombia (mostly dedicated to sugarcane cultivation) has been used to check the potential sensitivity of such data to the crop status and growth. The analysis of these images demonstrates certain relationship between the radar response (in terms of scattering mechanisms) and the stage in the growing season. Typical polarimetric features, such as the backscattering coefficient at different channels, the correlation and the ratio between the co-polar channels, and a radar vegetation index, have been computed to interpret the response of sugarcane at P-band. Results suggest that P-band quad-pol data from the BIOMASS mission is well suited for monitoring the growth of this crop type.
A Dynamical Framework that Integrates Optical and SAR Imagery for Sugarcane Monitoring in the Cauca Valley
Citation: Mestre-Quereda, A., Martinez-Marin, T., Lopez-Sanchez, J. M., Mosquera, C., Pelgrum, H., Skarli, A., Hoekman, D., & van der Sande, C. (2026). A Dynamical Framework that Integrates Optical and SAR Imagery for Sugarcane Monitoring in the Cauca Valley. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/JSTARS.2026.3694476
Abstract: In this work, we present a novel dynamical framework for crop monitoring that integrates SAR and optical satellite imagery. The proposed methodology employs two-dimensional state transitions to explicitly model the expected temporal evolution of crops. By combining such crop modeling with multi-sensor observations, including dual-polarimetric (VV and VH) radar images gathered by Sentinel-1 and optical imagery from Sentinel-2, the developed framework produces robust and consistent estimations using the well-established Kalman Filter. Specifically, the approach is applied to retrieve the biomass values of sugarcane crops located in the Cauca Valley (Colombia), over a full growing season (from summer 2024 to summer 2025). An intensive field campaign was carried out, so that ground-truth measurements in a large number of points, located in multiple fields, were available to develop and validate the proposed integration algorithm. Results show that biomass is accurately estimated especially when all available observations, both SAR and optical, are employed.