• G. Bratic, D. Oxoli, M.A. Brovelli. Map of Land Cover Agreement: Ensambling Existing Datasets for Large-Scale Training Data Provision. MDPI. 2023, Remote Sensing. 2023; 15(15):3774. https://doi.org/10.3390/rs15153774
  • L. Bruzzone, and the CCI HRLC Team. ESA CCI High Resolution Land Cover: Methodology and EO Data Processing Chain. ESA. 2022.
  • L. Bruzzone, and the CCI HRLC Team. ESA CCI High resolution Land Cover Products. ESA. 2022, ESA Living planet Symposium, May 2022, Bonn.
  • R. San Martin, C. Ottlé, V. Bastrikov, Ph. Peylin, and the HRLC working group. ESA-CCI High Resolution Land Cover products: Contribution to the parameterization of ORCHIDEE land surface model and to the understanding of land-atmosphere interactions. ESA. 2022, ESA Living planet Symposium, May 2022, Bonn.
  • L. Pesquer, C. Domingo-Marimon, J. M. Espelta, J. Pino. Spatio-temporal analysis of Ecosystem Functional Types in relation to land cover/use changes. 2022, IALE 2022 European Landscape Ecology Congress, 11-15 July 2022.
  • L. Maggiolo, D. Solarna, G. Moser, S. B. Serpico. Optical-SAR decision fusion with Markov random fields for high-resolution large-scale land cover mapping. IEEE. 2022, IEEE Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, July 17-22, 2022. https://doi.org/10.1109/IGARSS46834.2022.9884751
  • D. Solarna, L. Maggiolo, G. Moser, S. B. Serpico. A tiling-based strategy for large-scale multisensor optical-SAR image registration. IEEE. 2022, IEEE Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, July 17-22, 2022. https://doi.org/10.1109/IGARSS46834.2022.9884048
  • L. Maggiolo, D. Solarna, G. Moser, S. B. Serpico. Registration of multisensor images through a conditional generative adversarial network and a correlation-type similarity measure. MDPI. 2022, Remote Sensing, 14(12):2811, 2022. https://doi.org/10.3390/rs14122811
  • D. Marzi, S. Todmal and P. Gamba. Mapping globally using multitemporal Sentinel-1 SAR: a semiautomatic approach. IEEE. 2021, IEEE International India Geoscience and Remote Sensing Symposium, Virtual Meeting, 2021. https://doi.org/10.1109/InGARSS51564.2021.9792073
  • A. Sorriso, D. Marzi, P. Gamba. A General Land Cover Classification Framework for Sentinel-1 SAR Data. IEEE. 2021, IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI), Napoli, September 2021. https://doi.org/10.1109/RTSI50628.2021.9597319
  • C. Lamarche, S. Bontemps, Q. Marissiaux, P. Defourny, O. Arino. Towards a Multi-Level Sampling Scheme for Land Cover and Land Cover Change Validation. Lessons Learned from the Land Cover Climate Change Initiative. IEEE. 2021, IEEE International Geoscience and Remote Sensing Symposium, Brussels, Belgium, Virtual Meeting, 12-16 July 2021. https://doi.org/10.1109/IGARSS47720.2021.9553898
  • D. Marzi, P. Gamba. Wide-scale Water Bodies Mapping Using Multi-temporal Sentinel-1 SAR Data. IEEE. 2021, IEEE International Geoscience and Remote Sensing Symposium, Brussels, Belgium, Virtual Meeting, 12-16 July 2021. https://doi.org/10.1109/IGARSS47720.2021.9553072
  • B. Pinel-Puysségur, L. Maggiolo, M. Roux, N. Gasnier, D. Solarna, G. Moser, S. B. Serpico, F. Tupin. Experimental comparison of registration methods for multisensor SAR-optical data. IEEE. 2021, IEEE International Geoscience and Remote Sensing Symposium, Brussels, Belgium, Virtual Meeting, 12-16 July 2021. https://doi.org/10.1109/IGARSS47720.2021.9553640
  • I. Podsiadlo, C. Paris, L. Bruzzone. An Approach Based on Low Resolution Land-Cover-Maps and Domain Adaptation to Define Representative Training Sets at Large Scale. IEEE. 2021, IEEE International Geoscience and Remote Sensing Symposium, Brussels, Belgium, Virtual Meeting, 12-16 July 2021. https://doi.org/10.1109/IGARSS47720.2021.9553498
  • C. Paris, L. Orlandi, L. Bruzzone. An Interactive Strategy for the Training Set Definition Based on Active Self-Paced Learning Implemented on a Cloud-Computing Platform. IEEE. 2021, IEEE Geoscience and Remote Sensing Letters, Vol. 17. https://doi.org/10.1109/LGRS.2021.3114611
  • D. Marzi, P. Gamba. Inland Water Body Mapping Using Multi-temporal Sentinel-1 SAR Data. IEEE. 2021, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 11789-11799, 2021. https://doi.org/10.1109/JSTARS.2021.3127748
  • L. Maggiolo, D. Solarna, G. Moser and S. B. Serpico. Automatic area-based registration of optical and SAR images through generative adversarial networks and a correlation-type metric. IEEE. 2020, IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, Hawaii, USA, 26 September - 2 October 2020. https://doi.org/10.1109/IGARSS39084.2020.9323235
  • Y. T. Solano-Correa, K. Meshkini, F. Bovolo, L. Bruzzone. A land cover-driven approach for fitting satellite image time series in a change detection context. SPIE. 2020, SPIE Conference on Image and Signal Processing for Remote Sensing XXVI, Virtual Meeting, 21-25 September 2020. https://doi.org/10.1117/12.2573942
  • I. Podsiadlo, C. Paris, L. Bruzzone. A study of the robustness of the long short-term memory classifier to cloudy time series of multispectral images. SPIE. 2020, SPIE Conference on Image and Signal Processing for Remote Sensing XXVI, Virtual Meeting, 21-25 September 2020. https://doi.org/10.1117/12.2574383
  • L. Pesquer, C. Domingo-Marimon, J. Cristóbal, C. Ottlé, P. Peylin, F. Bovolo, L. Bruzzone. Comparison of ecosystem functional type patterns at different spatial resolutions in relation with FLUXNET data. SPIE. 2019, In Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI, vol. 11149, p. 1114908. https://doi.org/10.1117/12.2533049
  • L. Bruzzone, and the CCI HRLC Team. CCI Essential Climate Variables: High Resolution Land Cover. ESA. 2019, ESA Living Planet Symposium, Milan, Italy, 13-17 May 2019.
  • G. Bratic, V. Yordanov, M. A. Brovelli. High-resolution land cover classification: cost-effective approach for extraction of reliable training data from existing land cover datasets. Taylor and Francis. 2023, International Journal of Digital Earth, 16:1, 3618-3636. https://doi.org/10.1080/17538947.2023.2253784