Articles | Volume 372
https://doi.org/10.5194/piahs-372-311-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/piahs-372-311-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
12 Nov 2015
Exploitation of the full potential of PSI data for subsidence monitoring
Centre Tecnològic de les Telecomunicacions de Catalunya (CTTC), Castelldefels, Barcelona, Spain
N. Devanthéry
Centre Tecnològic de les Telecomunicacions de Catalunya (CTTC), Castelldefels, Barcelona, Spain
M. Cuevas-González
Centre Tecnològic de les Telecomunicacions de Catalunya (CTTC), Castelldefels, Barcelona, Spain
O. Monserrat
Centre Tecnològic de les Telecomunicacions de Catalunya (CTTC), Castelldefels, Barcelona, Spain
B. Crippa
Department of Earth Sciences, University of Milan, Milan, Italy
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M. Crosetto, J. A. Gili, O. Monserrat, M. Cuevas-González, J. Corominas, and D. Serral
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Guillermo Tamburini-Beliveau, Sebastián Balbarani, and Oriol Monserrat
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Short summary
Short summary
Landslides and ground deformation associated with the construction of a hydropower mega dam in the Santa Cruz River in Argentine Patagonia have been monitored using radar and optical satellite data, together with the analysis of technical reports. This allowed us to assess the integrity of the construction, providing a new and independent dataset. We have been able to identify ground deformation trends that put the construction works at risk.
M. Crosetto, L. Solari, A. Barra, O. Monserrat, M. Cuevas-González, R. Palamà, Y. Wassie, S. Shahbazi, S. M. Mirmazloumi, B. Crippa, and M. Mróz
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Q. Gao, M. Crosetto, O. Monserrat, R. Palama, and A. Barra
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N. Kotulak, M. Mleczko, M. Crosetto, R. Palamà, and M. Mróz
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S. M. Mirmazloumi, Á. F. Gambin, Y. Wassie, A. Barra, R. Palamà, M. Crosetto, O. Monserrat, and B. Crippa
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J. A. Navarro, D. García, M. Crosetto, and O. Monserrat
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R. Palamà, M. Crosetto, O. Monserrat, A. Barra, B. Crippa, M. Mróz, N. Kotulak, M. Mleczko, and J. Rapinski
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 321–326, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-321-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-321-2022, 2022
S. Shahbazi, M. Crosetto, and A. Barra
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 349–354, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-349-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-349-2022, 2022
Y. Wassie, Q. Gao, O. Monserrat, A. Barra, B. Crippa, and M. Crosetto
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 361–366, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-361-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-361-2022, 2022
M. Crosetto, L. Solari, J. Balasis-Levinsen, L. Bateson, N. Casagli, M. Frei, A. Oyen, D. A. Moldestad, and M. Mróz
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J. A. Navarro, A. Barra, O. Monserrat, and M. Crosetto
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Y. Wassie, M. Crosetto, G. Luzi, O. Monserrat, A. Barra, R. Palamá, M. Cuevas-González, S. M. Mirmazloumi, P. Espín-López, and B. Crippa
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P. Olea, O. Monserrat, C. Sierralta, A. Barra, L. Bono, F. Fuentes, Z. Qiu, and B. Crippa
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W12-2020, 1–6, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-1-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-1-2020, 2020
M. Crosetto and L. Solari
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O. Monserrat, C. Cardenas, P. Olea, V. Krishnakumar, and B. Crippa
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J. A. Navarro, G. Luzi, O. Monserrat, and M. Crosetto
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M. Crosetto, G. Luzi, O. Monserrat, A. Barra, M. Cuevas-González, R. Palamá, V. Krishnakumar, Y. Wassie, S. M. Mirmazloumi, P. Espín-López, and B. Crippa
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M. Crosetto, L. Solari, J. Balasis-Levinsen, N. Casagli, M. Frei, A. Oyen, and D. A. Moldestad
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M. Crosetto, O. Monserrat, A. Barra, M. Cuevas-González, V. Krishnakumar, M. Mróz, and B. Crippa
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1921–1926, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1921-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1921-2019, 2019
M. Crosetto, A. Budillon, A. Johnsy, G. Schirinzi, N. Devanthéry, O. Monserrat, and M. Cuevas-González
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V. Krishnakumar, O. Monserrat, M. Crosetto, and B. Crippa
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O. Monserrat, A. Barra, G. Herrera, S. Bianchini, C. Lopez, R. Onori, P. Reichenbach, R. Sarro, R. M. Mateos, L. Solari, S. Ligüérzana, and I. P. Carralero
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Q. Huang, M. Crosetto, O. Monserrat, and B. Crippa
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 457–463, https://doi.org/10.5194/isprs-annals-IV-2-W4-457-2017, https://doi.org/10.5194/isprs-annals-IV-2-W4-457-2017, 2017
M. Crosetto, O. Monserrat, G. Luzi, N. Devanthéry, M. Cuevas-González, and A. Barra
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 593–596, https://doi.org/10.5194/isprs-archives-XLII-2-W7-593-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-593-2017, 2017
M. Crosetto, O. Monserrat, N. Devanthéry, M. Cuevas-González, A. Barra, and B. Crippa
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 597–600, https://doi.org/10.5194/isprs-archives-XLII-2-W7-597-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-597-2017, 2017
M. Crosetto, O. Monserrat, N. Devanthéry, M. Cuevas-González, A. Barra, and B. Crippa
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 835–839, https://doi.org/10.5194/isprs-archives-XLI-B7-835-2016, https://doi.org/10.5194/isprs-archives-XLI-B7-835-2016, 2016
O. Monserrat, J. Moya, G. Luzi, M. Crosetto, J. A. Gili, and J. Corominas
Nat. Hazards Earth Syst. Sci., 13, 1873–1887, https://doi.org/10.5194/nhess-13-1873-2013, https://doi.org/10.5194/nhess-13-1873-2013, 2013
M. Crosetto, J. A. Gili, O. Monserrat, M. Cuevas-González, J. Corominas, and D. Serral
Nat. Hazards Earth Syst. Sci., 13, 923–933, https://doi.org/10.5194/nhess-13-923-2013, https://doi.org/10.5194/nhess-13-923-2013, 2013
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Short summary
Persistent Scatterer Interferometry (PSI) is a remote sensing technique used to monitor land deformation from interferometric SAR images. The main products that can be derived using the PSI technique are the deformation maps and the time series of deformation. In this paper, an approach to apply the PSI technique to a stack of Sentinel-1 images is described. Sentinel-1 deformation maps and time series obtained over the metropolitan area of Mexico DF are discussed.
Persistent Scatterer Interferometry (PSI) is a remote sensing technique used to monitor land...
