Glaciers are one of the main indicators of climate change. Monitoring their evolution is, therefore, crucial for understanding the Earth’s ecosystem. In this study, we present a time series of DEMs generated from high-resolution optical satellite stereo pairs and UAV surveys over the area of Forni Glacier (Ortles–Cevedale group, Italy) in the 2009-2022 timespan. Firstly, we performed DEM coregistration to remove DEM biases using the Nuth and Kääb algorithm. The DEM elevation differences after coregistration highlighted a bias removal with mean and median values close to zero and a final accuracy of around one meter. Then, using all the coregistered DEMs generated from both UAV and satellite data, we evaluated elevation changes, highlighting how climate change is causing the melting process of the glacier. Our results suggested that despite the limitations related to weather conditions (e.g. cloud coverage) and revisit time of high-resolution optical satellite imagery, the combination of UAV and satellite data can greatly improve glacier monitoring, increasing the amount of available data and the area of investigation.
Glacier Monitoring From Multi-Temporal UAV and Satellite Data: The Case Study of Forni Glacier (Italy) / V. Belloni, L. Ranaldi, D. Fugazza, M. Di Rita, M. Crespi (IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS). - In: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium[s.l] : IEEE, 2024. - ISBN 979-8-3503-6033-2. - pp. 22-26 (( convegno IGARSS tenutosi a Athens nel 2024 [10.1109/igarss53475.2024.10641110].
Glacier Monitoring From Multi-Temporal UAV and Satellite Data: The Case Study of Forni Glacier (Italy)
D. Fugazza;
2024
Abstract
Glaciers are one of the main indicators of climate change. Monitoring their evolution is, therefore, crucial for understanding the Earth’s ecosystem. In this study, we present a time series of DEMs generated from high-resolution optical satellite stereo pairs and UAV surveys over the area of Forni Glacier (Ortles–Cevedale group, Italy) in the 2009-2022 timespan. Firstly, we performed DEM coregistration to remove DEM biases using the Nuth and Kääb algorithm. The DEM elevation differences after coregistration highlighted a bias removal with mean and median values close to zero and a final accuracy of around one meter. Then, using all the coregistered DEMs generated from both UAV and satellite data, we evaluated elevation changes, highlighting how climate change is causing the melting process of the glacier. Our results suggested that despite the limitations related to weather conditions (e.g. cloud coverage) and revisit time of high-resolution optical satellite imagery, the combination of UAV and satellite data can greatly improve glacier monitoring, increasing the amount of available data and the area of investigation.File | Dimensione | Formato | |
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