Glaciers are one of the key indicators of climate change and play an important role in our society by providing freshwater, which can be used for domestic, industrial and agricultural applications. As they are severely affected by climate change, it is of crucial importance to monitor their morphological evolution to estimate ice volume and mass changes. However, the accurate reconstruction of glacier morphology changes over time is not an easy task. In this context, the use of Unmanned Aerial Vehicles (UAVs) is of interest to the glaciological community thanks to their flexibility, fine spatial detail and ease of processing with state-of-the-art software packages, which makes them an ideal candidate to monitor small glacier changes. However, when dealing with large glaciers, UAV approaches can be time consuming and not efficient. On the other hand, optical and Synthetic Aperture Radar (SAR) high-resolution satellite imagery can provide continuous monitoring of wide areas without being affected by logistic constraints. The goal of this work is to combine the information coming from different sensors (UAV data, optical and SAR imagery) for glacier 3D reconstruction and volume change estimation over time. The idea is to assess the accuracy that can be achieved with UAV and satellite observations when comparing volume changes computed from multi-temporal acquisitions. The study area is the Forni Glacier, an important geosite located in Stelvio Park (Italian Alps). The data processing focuses on UAV data, Pléiades and IKONOS optical imagery and ICEYE SAR data, capturing the site of interest. The UAV images will be processed using the Leica Infinity software, while optical and SAR imagery will be analysed using the commercial software Agisoft Metashape and a free and open-source software developed at the Geodesy and Geomatic Division of Sapienza University of Rome, named DATE.
The main innovative aspect and challenge of the project is related to the integration of UAV data, optical and SAR satellite imagery in the field of 3D glacier surface reconstruction. The project will focus on the area of the Forni Glacier, in which different approaches have been used over the years but none based on the combination of UAVs and optical and SAR satellites.
The innovation of the proposal is also related to the investigation of the ICEYE SAR data. The ICEYE X-band constellation offers rapid satellite revisits, very high-resolution imagery (GSD: 0.25×0.5 metres for Spotlight High, 0.5×0.5 metres for Spotlight, 0.5×2.5-3 metres for Stripmap High, 0.5-1.5×2.5-3 metres for Stripmap, in range×azimuth respectively) and coverage of wide areas. The system can acquire 24h ground track repeat on a global scale and it will be further developed by ICEYE in 2021 and beyond. This will enable the acquisition of images with different incidence angles, multiple times a day over specified areas of interest, benefiting from SAR independence from cloudy weather and sunlight illumination. The constellation will represent, therefore, a groundbreaking solution for near real-time 3D change detection of glaciers. The constellation has been only partially investigated and, to date, there are no available studies in the field of DSM generation from ICEYE data. The use of such imagery in the field of glacier monitoring will therefore represent a first test which will also open up the possibility for new and completely different applications (e.g. water reservoir level monitoring and sea level rise with ICEYE SAR imagery).
Another innovative aspect is related to the optical data processing through the satellite module of Agisoft Metashape since only few studies have been carried out with this software (Lastilla et al., 2021) and none for glacier surface reconstruction.
Finally, the use of DATE for optical and SAR data processing will contribute to the innovation of the project since this is the only free and open-source software capable of processing both optical and SAR imagery. It is also worth noticing that the software has been already assessed over urban and natural areas but it has never been adopted to generate DSMs of glacial environments.
Lastilla L., Belloni V., Ravanelli R. and Crespi M.: DSM Generation from Single and Cross-Sensor Multi-View Satellite Images Using the New Agisoft Metashape: The Case Studies of Trento and Matera (Italy). Remote Sensing, 13(4):593. https://doi.org/10.3390/rs13040593, 2021.