Michele Dalponte

Orcid: 0000-0001-9850-8985

According to our database1, Michele Dalponte authored at least 52 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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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
Automated Machine Learning Driven Stacked Ensemble Modeling for Forest Aboveground Biomass Prediction Using Multitemporal Sentinel-2 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

Individual Tree Crown Delineation and Biomass Estimation from LiDAR Data in Gorgona Island, Colombia.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2022
Generative Feature Extraction From Sentinel 1 and 2 Data for Prediction of Forest Aboveground Biomass in the Italian Alps.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022

Wood Decay Detection in Norway Spruce Forests Based on Airborne Hyperspectral and ALS Data.
Remote. Sens., 2022

Mapping a European Spruce Bark Beetle Outbreak Using Sentinel-2 Remote Sensing Data.
Remote. Sens., 2022

UAV-Based Hyperspectral Imagery for Detection of Root, Butt, and Stem Rot in Norway Spruce.
Remote. Sens., 2022

Hyperspectral and LiDAR data for the prediction via machine learning of tree species, volume and biomass: a possible contribution for updating forest management plans.
CoRR, 2022

Detection of heartwood rot in Norway spruce trees with lidar and multi-temporal satellite data.
Int. J. Appl. Earth Obs. Geoinformation, 2022

Using repeat airborne LiDAR to map the growth of individual oil palms in Malaysian Borneo during the 2015-16 El Niño.
Int. J. Appl. Earth Obs. Geoinformation, 2022

Hyperspectral and LiDAR Data for the Prediction via Machine Learning of Tree Species, Volume and Biomass: A Contribution for Updating Forest Management Plans.
Proceedings of the Geomatics for Green and Digital Transition - 25th Italian Conference, 2022

2021
Corrections to "A Novel Multitemporal Deep Fusion Network (MDFN) for Short-Term Multitemporal HR Images Classification".
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

A Novel Multitemporal Deep Fusion Network (MDFN) for Short-Term Multitemporal HR Images Classification.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

A Novel Feature Fusion Approach for VHR Remote Sensing Image Classification.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Prediction of Forest Aboveground Biomass Using Multitemporal Multispectral Remote Sensing Data.
Remote. Sens., 2021

Potential and Limitations of Grasslands α-Diversity Prediction Using Fine-Scale Hyperspectral Imagery.
Remote. Sens., 2021

Individual Tree Segmentation Based on Mean Shift and Crown Shape Model for Temperate Forest.
IEEE Geosci. Remote. Sens. Lett., 2021

A Disentangled Variational Autoencoder for Prediction of Above Ground Biomass from Hyperspectral Data.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020
Global Airborne Laser Scanning Data Providers Database (GlobALS) - A New Tool for Monitoring Ecosystems and Biodiversity.
Remote. Sens., 2020

VIS-NIR, Red-Edge and NIR-Shoulder Based Normalized Vegetation Indices Response to Co-Varying Leaf and Canopy Structural Traits in Heterogeneous Grasslands.
Remote. Sens., 2020

Mapping forest windthrows using high spatial resolution multispectral satellite images.
Int. J. Appl. Earth Obs. Geoinformation, 2020

2019
Prediction of Competition Indices in a Norway Spruce and Silver Fir-Dominated Forest Using Lidar Data.
Remote. Sens., 2019

Tree Species Classification in a Highly Diverse Subtropical Forest Integrating UAV-Based Photogrammetric Point Cloud and Hyperspectral Data.
Remote. Sens., 2019

Assessing Across-Scale Optical Diversity and Productivity Relationships in Grasslands of the Italian Alps.
Remote. Sens., 2019

A Weighted SVM-Based Approach to Tree Species Classification at Individual Tree Crown Level Using LiDAR Data.
Remote. Sens., 2019

Optimizing Field Data Collection for Individual Tree Attribute Predictions Using Active Learning Methods.
Remote. Sens., 2019

Modelling Site Index in Forest Stands Using Airborne Hyperspectral Imagery and Bi-Temporal Laser Scanner Data.
Remote. Sens., 2019

Weighted Support Vector Machines for Tree Species Classification Using Lidar Data.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Feature-Level Fusion of Landsat-8 OLI-SWIR and TIR Images for Fine Burned Area Change Detection.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2018
Predicting Selected Forest Stand Characteristics with Multispectral ALS Data.
Remote. Sens., 2018

Detection of Forest Changes with Multi-Temporal Lidar Data.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Prediction of Forest Attributes with Multispectral Lidar Data.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Prediction of Species-Specific Volume Using Different Inventory Approaches by Fusing Airborne Laser Scanning and Hyperspectral Data.
Remote. Sens., 2017

A graph cut approach to 3D tree delineation, using integrated airborne LiDAR and hyperspectral imagery.
CoRR, 2017

Individual tree crown approach for predicting site index in boreal forests using airborne laser scanning and hyperspectral data.
Int. J. Appl. Earth Obs. Geoinformation, 2017

2016
Individual Tree Species Classification From Airborne Multisensor Imagery Using Robust PCA.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016

Aboveground biomass estimation in tropical forests at single tree level with ALS data.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

2014
Cost-Sensitive Active Learning With Lookahead: Optimizing Field Surveys for Remote Sensing Data Classification.
IEEE Trans. Geosci. Remote. Sens., 2014

Unsupervised Selection of Training Samples for Tree Species Classification Using Hyperspectral Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014

A new procedure for identifying single trees in understory layer using discrete LiDAR data.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014

Fusion of hyperspectral and LiDAR data for forest attributes estimation.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014

2013
Tree Species Classification in Boreal Forests With Hyperspectral Data.
IEEE Trans. Geosci. Remote. Sens., 2013

Airborne laser scanning of forest resources: An overview of research in Italy as a commentary case study.
Int. J. Appl. Earth Obs. Geoinformation, 2013

Forest species and biomass estimation using airborne laser scanning and hyperspectral images.
Proceedings of the 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2013

Optimizing the ground sample collection with cost-sensitive active learning for tree species classification using hyperspectral images.
Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013

Unsupervised selection of training plots and trees for tree species classification.
Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013

2011
A System for the Estimation of Single-Tree Stem Diameter and Volume Using Multireturn LIDAR Data.
IEEE Trans. Geosci. Remote. Sens., 2011

Tree species classification in the Southern Alps with very high geometrical resolution multispectral and hyperspectral data.
Proceedings of the 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2011

2009
Analysis on the Use of Multiple Returns LiDAR Data for the Estimation of Tree Stems Volume.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2009

Fusion of Hyperspectral and Lidar Remote Sensing Data for the Estimation of Tree Stem Diameters.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2009

2008
Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas.
IEEE Trans. Geosci. Remote. Sens., 2008


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