Daniele Marinelli
Orcid: 0000-0002-5038-6373Affiliations:
- University of Trento, Italy
According to our database1,
Daniele Marinelli
authored at least 18 papers
between 2016 and 2024.
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Bibliography
2024
Exploring the Detection of Bark Beetle Attacks in Norway Spruce Forests in Sentinel-1 Image Time Series.
Proceedings of the IGARSS 2024, 2024
2023
Multiyear Mapping of Water Demand at Crop Level: An End-to-End Workflow Based on High-Resolution Crop Type Maps and Meteorological Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023
Windthrows Detection With Satellite Remote Sensing Data: A Comparison Among Sentinel-2, Planet, And Cosmo Sky-Med Data.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023
2022
IEEE Trans. Geosci. Remote. Sens., 2022
An Approach Based on Deep Learning for Tree Species Classification in LiDAR Data Acquired in Mixed Forest.
IEEE Geosci. Remote. Sens. Lett., 2022
A Triangulation-Based Technique for Tree-Top Detection in Heterogeneous Forest Structures Using High Density LiDAR Data.
IEEE Geosci. Remote. Sens. Lett., 2022
IEEE Geosci. Remote. Sens. Lett., 2022
2021
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021
2019
A Novel Change Detection Method for Multitemporal Hyperspectral Images Based on Binary Hyperspectral Change Vectors.
IEEE Trans. Geosci. Remote. Sens., 2019
IEEE Geosci. Remote. Sens. Lett., 2019
Proceedings of the 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images, 2019
An Automatic Technique for Deciduous Trees Detection in High Density Lidar Data Based on Delaunay Triangulation.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
2018
A Novel Approach to 3-D Change Detection in Multitemporal LiDAR Data Acquired in Forest Areas.
IEEE Trans. Geosci. Remote. Sens., 2018
Fusion of Multitemporal LiDAR Data for Individual Tree Crown Parameter Estimation on Low Density Point Clouds.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
An Unsupervised Change Detection Method for Lidar Data in Forest Areas Based on Change Vector Analysis in the Polar Domain.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
2017
A novel method for unsupervised multiple Change Detection in hyperspectral images based on binary Spectral Change Vectors.
Proceedings of the 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images, 2017
A novel change detection method for multitemporal hyperspectral images based on a discrete representation of the change information.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017
2016
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016