Author
Listed:
- Carlotta Parenti
(Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125 Modena, Italy
CRICT—Inter-Departmental Research and Innovation Centre on Constructions and Environmental Services, University of Modena and Reggio Emilia, Via Vivarelli 10, 41125 Modena, Italy)
- Francesca Grassi
(CRICT—Inter-Departmental Research and Innovation Centre on Constructions and Environmental Services, University of Modena and Reggio Emilia, Via Vivarelli 10, 41125 Modena, Italy
Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, Via Vivarelli 10, 41125 Modena, Italy)
- Paolo Rossi
(CRICT—Inter-Departmental Research and Innovation Centre on Constructions and Environmental Services, University of Modena and Reggio Emilia, Via Vivarelli 10, 41125 Modena, Italy
Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, Via Vivarelli 10, 41125 Modena, Italy)
- Mauro Soldati
(Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via Campi 103, 41125 Modena, Italy
CRICT—Inter-Departmental Research and Innovation Centre on Constructions and Environmental Services, University of Modena and Reggio Emilia, Via Vivarelli 10, 41125 Modena, Italy)
- Edda Pattuzzi
(Regional Agency for Territorial Safety and Civil Protection of Emilia-Romagna, Viale Silvani 6, 40122 Bologna, Italy)
- Francesco Mancini
(CRICT—Inter-Departmental Research and Innovation Centre on Constructions and Environmental Services, University of Modena and Reggio Emilia, Via Vivarelli 10, 41125 Modena, Italy
Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, Via Vivarelli 10, 41125 Modena, Italy)
Abstract
In mountain environments, landslide activity can be assessed through a combination of remote and proximal sensing techniques performed at different scales. The complementarity of methods and the synergistic use of data can be crucial for landslide recognition and monitoring. This paper explored the potential of Multi-Temporal Differential Synthetic Aperture Radar Interferometry (MT-DInSAR) to detect and monitor slope deformations at the basin scale in a catchment area of the Northern Apennines (Italy) and verified the consistency between the landslide classification by the Inventory of Landslide Phenomena in Italy (IFFI) and displacements from the SAR data. In this research, C- and X-band SAR were considered to provide insights into the performances and suitability of sensors operating at different frequencies. This study provides clues about the state of activity of slow-moving landslides and critically assessed its contribution to the IFFI inventory update. Moreover, it demonstrated the benefits of the synergistic use of SAR and geomorphological analysis to investigate slope dynamics in clayey terrains by exemplifying the approach for a relevant case study, the Gaiato landslide. Notwithstanding the widespread use of MT-DInSAR for landslide kinematics investigations, the main limiting factors are discussed along with the expected improvements related to the upcoming new generations of L-band SAR satellites.
Suggested Citation
Carlotta Parenti & Francesca Grassi & Paolo Rossi & Mauro Soldati & Edda Pattuzzi & Francesco Mancini, 2024.
"Synergistic Use of Synthetic Aperture Radar Interferometry and Geomorphological Analysis in Slow-Moving Landslide Investigation in the Northern Apennines (Italy),"
Land, MDPI, vol. 13(9), pages 1-24, September.
Handle:
RePEc:gam:jlands:v:13:y:2024:i:9:p:1505-:d:1479166
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