GlobEO is a company hosted in Toulouse, created in 2018 by Stéphane Mermoz who was a member of the CESBIO radar remote sensing team from 2011 to 2018.
GlobEO develops services in the field of environmental monitoring using Earth observation data, primarily derived from Sentinel satellite images of the European Copernicus program, which are continuously acquired worldwide.
The company’s activities can be summarized in three main areas:
1. GlobEO assists countries in adapting their agricultural and forestry policies in response to climate change. It supports the development of decision-making tools that include a portfolio of tailored management solutions for policymakers. These solutions are created by analyzing past agricultural and forestry yields and projecting future yields through modeling in a changing climate.
2. GlobEO offers training services on the use of satellite imagery for environmental monitoring.
3. GlobEO participates in various research and development projects.
Publications
Boitard, S., Mialon, A., Mermoz, S., Rodríguez-Fernández, N. J., Richaume, P., Salazar-Neira, J. C., … & Kerr, Y. H. (2024). Above ground biomass dataset from SMOS L band vegetation optical depth and reference maps. Earth System Science Data Discussions, 2024, 1-28. https://doi.org/10.5194/essd-2024-184
Mermoz, S., Prieto, J. D., Planells, M., Morin, D., Koleck, T., Mouret, F., … & Féret, J. B. (2024). Sub-Monthly Assessment of Temperate Forest Clear-Cuts in Mainland France. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/JSTARS.2024.3429012
Morin, D., Planells, M., Mermoz, S., & Mouret, F. (2023). Estimation of forest height and biomass from open-access multi-sensor satellite imagery and GEDI Lidar data: high-resolution maps of metropolitan France. arXiv preprint arXiv:2310.14662. https://doi.org/10.48550/arXiv.2310.14662
Salazar-Neira, J. C., Mialon, A., Richaume, P., Mermoz, S., Kerr, Y. H., Bouvet, A., … & Rodríguez-Fernández, N. J. (2023). Above-ground biomass estimation based on multi-angular l-band measurements of brightness temperatures. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 5813-5827. https://doi.org/10.1109/JSTARS.2023.3285288
Doblas, J., Lima, L., Mermoz, S., Bouvet, A., Reiche, J., Watanabe, M., … & Shimabukuro, Y. (2022). Inter-comparison of optical and SAR-based forest disturbance warning systems in the Amazon shows the potential of combined SAR-optical monitoring. Int. J. Remote Sens. https://doi.org/10.1080/01431161.2022.2157684
Bousquet, E., Mialon, A., Rodriguez-Fernandez, N., Mermoz, S., & Kerr, Y. (2022). Monitoring post-fire recovery of various vegetation biomes using multi-wavelength satellite remote sensing. Biogeosciences, 19(13), 3317-3336. https://doi.org/10.5194/bg-19-3317-2022
Morin, D., Planells, M., Baghdadi, N., Bouvet, A., Fayad, I., Le Toan, T., … & Villard, L. (2022). Improving heterogeneous forest height maps by integrating GEDI-based forest height information in a multi-sensor mapping process. Remote Sensing, 14(9), 2079. https://doi.org/10.3390/rs14092079
Marie, G., Luyssaert, B. S., Dardel, C., Le Toan, T., Bouvet, A., Mermoz, S., … & Peylin, P. (2022). Constraining a land cover map with satellite-based aboveground biomass estimates over Africa. Geoscientific Model Development, 15(6), 2599-2617. https://doi.org/10.5194/gmd-15-2599-2022
Mermoz, S., Bouvet, A., Koleck, T., Ballère, M., & Le Toan, T. (2021). Continuous detection of forest loss in Vietnam, Laos, and Cambodia using Sentinel-1 data. Remote Sensing, 13(23), 4877. https://doi.org/10.3390/rs13234877
Le Toan, T., Huu, N., Simioni, M., Phan, H., Arai, H., Mermoz, S., … & Espagne, E. (2021). Agriculture in Viet Nam under the impact of climate change. Climate change in Viet Nam. Impacts and adaptation. A COP26 assessment report of the GEMMES Viet Nam project. https://hal.inrae.fr/hal-03456472
Ballère, M., Bouvet, A., Mermoz, S., Le Toan, T., Koleck, T., Bedeau, C., … & Lardeux, C. (2021). SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery. Remote Sensing of Environment, 252, 112159. https://doi.org/10.1016/j.rse.2020.112159
Mialon, A., Rodríguez-Fernández, N. J., Santoro, M., Saatchi, S., Mermoz, S., Bousquet, E., & Kerr, Y. H. (2020). Evaluation of the sensitivity of SMOS L-VOD to forest above-ground biomass at global scale. Remote Sensing, 12(9), 1450. https://doi.org/10.3390/rs12091450
Soto-Navarro, C., Ravilious, C., Arnell, A., De Lamo, X., Harfoot, M., Hill, S. L. L., … & Kapos, V. (2020). Mapping co-benefits for carbon storage and biodiversity to inform conservation policy and action. Philosophical Transactions of the Royal Society B, 375(1794), 20190128. https://doi.org/10.1098/rstb.2019.0128
Hirschmugl, M., Deutscher, J., Sobe, C., Bouvet, A., Mermoz, S., & Schardt, M. (2020). Use of SAR and optical time series for tropical Forest disturbance mapping. Remote Sens. 12, 727. https://doi.org/10.3390/rs12040727
Réjou-Méchain, M., Barbier, N., Couteron, P., Ploton, P., Vincent, G., Herold, M., … & Pélissier, R. (2019). Upscaling forest biomass from field to satellite measurements: sources of errors and ways to reduce them. Surveys in Geophysics, 40, 881-911. https://doi.org/10.1007/s10712-019-09532-0
Morin, D., Planells, M., Guyon, D., Villard, L., Mermoz, S., Bouvet, A., … & Dedieu, G. (2019). Estimation and mapping of forest structure parameters from open access satellite images: Development of a generic method with a study case on coniferous plantation. Remote Sensing, 11(11), 1275. https://doi.org/10.3390/rs11111275
Rodríguez-Veiga, P., Quegan, S., Carreiras, J., Persson, H. J., Fransson, J. E., Hoscilo, A., … & Balzter, H. (2019). Forest biomass retrieval approaches from earth observation in different biomes. International Journal of Applied Earth Observation and Geoinformation, 77, 53-68. https://doi.org/10.1016/j.jag.2018.12.008
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