| A Review of Change Detection in Multitemporal Hyperspectral Images: Current Techniques, Applications, and Challenges S Liu, D Marinelli, L Bruzzone, F Bovolo IEEE Geoscience and Remote Sensing Magazine 7 (2), 140-158, 2019 | 325 | 2019 |
| Automatic Pleural Line Extraction and COVID-19 Scoring from Lung Ultrasound Data L Carrer, E Donini, D Marinelli, M Zanetti, F Mento, E Torri, A Smargiassi, ... IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 67 …, 2020 | 88 | 2020 |
| A novel change detection method for multitemporal hyperspectral images based on binary hyperspectral change vectors D Marinelli, F Bovolo, L Bruzzone IEEE Transactions on Geoscience and Remote Sensing 57 (7), 4913-4928, 2019 | 85 | 2019 |
| A Novel Approach to 3-D Change Detection in Multitemporal LiDAR Data Acquired in Forest Areas D Marinelli, C Paris, L Bruzzone IEEE Transactions on Geoscience and Remote Sensing, 2018 | 43 | 2018 |
| ExtremeEarth meets satellite data from space DH Hagos, T Kakantousis, V Vlassov, S Sheikholeslami, T Wang, ... IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2021 | 18 | 2021 |
| An approach based on deep learning for tree species classification in lidar data acquired in mixed forest D Marinelli, C Paris, L Bruzzone IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2022 | 17 | 2022 |
| Spectral separability of bark beetle infestation stages: A single-tree time-series analysis using Planet imagery M Dalponte, R Cetto, D Marinelli, D Andreatta, C Salvadori, F Pirotti, ... Ecological Indicators 153, 110349, 2023 | 14 | 2023 |
| An Approach to Tree Detection Based on the Fusion of Multitemporal LiDAR Data D Marinelli, C Paris, L Bruzzone IEEE Geoscience and Remote Sensing Letters 16 (11), 1771-1775, 2019 | 13 | 2019 |
| A system for burned area detection on multispectral imagery M Zanetti, S Saha, D Marinelli, ML Magliozzi, M Zavagli, M Costantini, ... IEEE Transactions on Geoscience and Remote Sensing 60, 1-15, 2021 | 11 | 2021 |
| A novel method for unsupervised multiple Change Detection in hyperspectral images based on binary Spectral Change Vectors D Marinelli, F Bovolo, L Bruzzone Analysis of Multitemporal Remote Sensing Images (MultiTemp), 2017 9th …, 2017 | 11 | 2017 |
| Forest Change Detection in Lidar Data Based on Polar Change Vector Analysis D Marinelli, NC Coops, DK Bolton, L Bruzzone IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2020 | 10 | 2020 |
| A high resolution burned area detector for Sentinel-2 and Landsat-8 M Zanetti, D Marinelli, M Bertoluzza, S Saha, F Bovolo, L Bruzzone, ... 2019 10th International Workshop on the Analysis of Multitemporal Remote …, 2019 | 9 | 2019 |
| A method for continuous sub-annual mapping of forest disturbances using optical time series D Marinelli, M Dalponte, L Frizzera, E Næsset, D Gianelle Remote Sensing of Environment 299, 113852, 2023 | 8 | 2023 |
| Fusion of high and very high density lidar data for 3d forest change detection D Marinelli, C Paris, L Bruzzone 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2016 | 8 | 2016 |
| Artificial Intelligence and big data technologies for Copernicus data: The EXTREMEEARTH project M Koubarakis, G Stamoulis, D Bilidas, T Ioannidis, G Mandilaras, ... Conference on Big Data from Space, BiDS 2021: From Insights to Foresight, 9-12, 2021 | 7 | 2021 |
| Detection of forest windthrows with bitemporal COSMO-SkyMed and Sentinel-1 SAR data M Dalponte, YT Solano-Correa, D Marinelli, S Liu, N Yokoya, D Gianelle Remote Sensing of Environment 297, 113787, 2023 | 6 | 2023 |
| Crop Water Availability Mapping in the Danube Basin Based on Deep Learning, Hydrological and Crop Growth Modelling S Migdall, S Dotzler, E Gleisberg, F Appel, M Muerth, H Bach, ... Engineering Proceedings 9 (1), 42, 2022 | 6 | 2022 |
| A Triangulation-Based Technique for Tree-Top Detection in Heterogeneous Forest Structures Using High Density LiDAR Data D Marinelli, C Paris, L Bruzzone IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2021 | 6 | 2021 |
| A novel change detection method for multitemporal hyperspectral images based on a discrete representation of the change information D Marinelli, F Bovolo, L Bruzzone 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2017 | 6 | 2017 |
| An Unsupervised Change Detection Method for Lidar Data in Forest Areas Based on Change Vector Analysis in the Polar Domain D Marinelli, NC Coops, DK Bolton, L Bruzzone IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018 | 5 | 2018 |
Lorenzo BruzzoneProfessor of Telecommunications, University of TrentoVerified email at ing.unitn.it
