Daniel Carcereri

Orcid: 0000-0002-3956-1409

According to our database1, Daniel Carcereri authored at least 11 papers between 2020 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Country-Scale Mapping of Forest Parameters Using Deep Learning and Tandem-X Insar Data.
Proceedings of the IGARSS 2024, 2024

Forest Mapping with Tandem-X Insar Data and Self-Supervised Learning.
Proceedings of the IGARSS 2024, 2024

2023
A Deep Learning Framework for the Estimation of Forest Height From Bistatic TanDEM-X Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023

Sentinel-1 and TanDEM-X InSAR Coherence for Monitoring Forests Using Deep Learning.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Potential of Deep Learning for Forest Height Estimation from Tandem-X Bistatic Insar Data.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Monitoring Forest Degradation in the Amazon Basin with Tandem-X High-Resolution Images and Deep Learning Techniques.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2022
On the Derivation of Volume Decorrelation From TanDEM-X Bistatic Coherence.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022

Deep Learning for Mapping Tropical Forests with TanDEM-X Bistatic InSAR Data.
Remote. Sens., 2022

Large Scale Forest Parameter Estimation Through a Deep Learning-Based Fusion of Sentinel-2 and Tandem-X Data.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

Tropical Forests Mapping with Tandem-X and Deep Learning Methods.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

2020
Large-Scale Precise Mapping of Agricultural Fields in Sentinel-2 Satellite Image Time Series.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020


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