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@article{2368186, author = {Jelének, Jan and Kopačková, Veronika and Fárová, Kateřina}, article_location = {Switzerland}, doi = {http://dx.doi.org/10.3390/ecrs-2-05174}, keywords = {Kaikōura earthquake; landslide detection; DInSAR; Sentinel-1; Sentinel-2}, issn = {2504-3900}, journal = {Proceedings (MDPI)}, title = {Post-earthquake landslide distribution assessment using sentinel-1 and-2 data: The example of the 2016 mw 7.8 earthquake in New Zealand}, url = {https://www.mdpi.com/2504-3900/2/7/361}, year = {2018} }
TY - JOUR ID - 2368186 AU - Jelének, Jan - Kopačková, Veronika - Fárová, Kateřina PY - 2018 TI - Post-earthquake landslide distribution assessment using sentinel-1 and-2 data: The example of the 2016 mw 7.8 earthquake in New Zealand JF - Proceedings (MDPI) SN - 25043900 KW - Kaikōura earthquake KW - landslide detection KW - DInSAR KW - Sentinel-1 KW - Sentinel-2 UR - https://www.mdpi.com/2504-3900/2/7/361 N2 - Post-earthquake analysis using radar interferometry has become a standard procedure for assessing earthquakes with significant damages. Sentinel-1 satellite provides 6-day revisiting time, and Sentinel-2 data has 5-day revisiting time and the same viewing angle that can enable the detection of changes in surface/land-cover after a major seismic event. Using Sentinel-2 alongside Sentinel-1 could bring new benefits when gathering spatial information about a post seismic event. In our study, we focused on analyzing a major earthquake, which occurred on 14 November 2016 with 7.8 magnitude near the city of Kaikōura, New Zealand, using both Sentinel-1 radar images and Sentinel-2 optical data. Hundreds of landslides were reported as a result of this earthquake. In addition, substantial land uplift was detected in some parts of the sea shore. Differential interferometry allowed us to estimate earthquake strength analyzing the distribution of absolute vertical displacement values. Sentinel-2 pre- and post-earthquake images were used in order to assess land-cover changes and automatically detect landslides, which occurred after the earthquake. Linking DInSAR results with Sentinel-2 change detection analysis helped us to get a more complex perspective on the earthquake impact, to create landslide inventory maps, and to subsequently develop workflows for quick post-event analysis. ER -
JELÉNEK, Jan, Veronika KOPAČKOVÁ a Kateřina FÁROVÁ. Post-earthquake landslide distribution assessment using sentinel-1 and-2 data: The example of the 2016 mw 7.8 earthquake in New Zealand. \textit{Proceedings (MDPI)}. Switzerland, 2018. ISSN~2504-3900. Dostupné z: https://dx.doi.org/10.3390/ecrs-2-05174.
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