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Articles | Volume XLVIII-4/W1-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W1-2022, 27–34, 2022
https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-27-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W1-2022, 27–34, 2022
https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-27-2022
 
05 Aug 2022
05 Aug 2022

MONITORING LANDSLIDE DISPLACEMENTS THROUGH MAXIMUM CROSS-CORRELATION OF SATELLITE IMAGES

L. Amici1, V. Yordanov1,2, D. Oxoli1, X. Q. Truong3, and M. A. Brovelli1,4 L. Amici et al.
  • 1Department of Civil and Environmental Engineering (DICA), Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan, Italy
  • 2Vasil Levski National Military University, Veliko Tarnovo, Bulgaria
  • 3Hanoi University of Natural Resources and Environment, 41A Phu Dien Road, Phu Dien, North-Tu Liem district, Hanoi, Vietnam
  • 4Istituto per il Rilevamento Elettromagnetico dell’Ambiente, CNR-IREA, via Bassini 15, 20133 Milano, Italy

Keywords: Landslide displacement monitoring, Earth Observation, Maximum Cross-Correlation, satellite images

Abstract. Landslides are one of the most dangerous and disastrous geological hazard worldwide, posing threats to human life, infrastructures and to the natural environment. Consequently, monitoring active landslides is crucial in order to reduce the risk of damages and casualties. With this aim, this work proposes a way to compute landslide displacements through time, by exploiting the great availability of high quality multispectral satellite images. The developed procedure produces maps of displacement magnitude and direction by means of local cross-correlation of Earth Observation data from the Sentinel-2 and PlanetScope missions. The Ruinon landslide, an active landslide in Northern Lombardy, Italy, was selected as a case study. The workflow of the developed procedure is described, and the results are presented and discussed. Moreover, a validation of the analysis by comparison with UAV surveys of the landslide is reported, along with a discussion on future developments and improvements of this technique. This work was designed to be entirely based on free and open-source GIS software and to rely mainly on open data. These characteristics allow the proposed analysis to be easily replicated, customized, and empowered.