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Synergic use of Sentinel-1 and Sentinel-2 data for automatic detection of earthquake-triggered landscape changes: A case study of the 2016 Kaikoura earthquake (Mw 7.8), New Zealand

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00025798%3A_____%2F21%3A00000128" target="_blank" >RIV/00025798:_____/21:00000128 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://www.sciencedirect.com/science/article/pii/S0034425721003540" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0034425721003540</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.rse.2021.112634" target="_blank" >10.1016/j.rse.2021.112634</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Synergic use of Sentinel-1 and Sentinel-2 data for automatic detection of earthquake-triggered landscape changes: A case study of the 2016 Kaikoura earthquake (Mw 7.8), New Zealand

  • Popis výsledku v původním jazyce

    Earthquakes can trigger numerous landslides and cause other significant changes in the landscape over large areas. This study presents a new processing scheme combining radar (Copernicus Sentinel-1) and optical satellite data (Copernicus Sentinel-2) to quickly and easily map landscape changes such as landslides, coastal uplift and changes in water bodies caused by a severe event such as an earthquake. The processing scheme has been tested for the 2016 Kaikoura earthquake (Mw 7.8), New Zealand, which impacted vast and mostly inaccessible areas, causing hundreds of landslides. The workflow combines the following change-detection methods: i) Sentinel-1 amplitude change detection ii) Sentinel-2-based detection of non-vegetated areas that occurred after the event using the atmospherically resistant vegetation index (ARVI). To get a more complex view of the surface changes caused by the Kaikoura earthquake, the available online services and tools were further tested (open source via the European Space Agency) allowing automatic detection of vertical displacements and deformations. It was concluded, that the above-mentioned approaches facilitated the assessment of earthquake-triggered changes in a comprehensive manner. The methodology is an example of how to detect earthquake landscape changes in an automatic and rapid manner. The new processing scheme for the synergic use of Sentinel-1 and Sentinel-2 data has high potential to be used for operational and scientific purposes, since it relies on globally available, free data and provides high spatial and temporal resolution. The results can be obtained and made available only a few days after an event, therefore providing significant insights into earthquake impact assessment and may also be helpful for prioritizing field work.

  • Název v anglickém jazyce

    Synergic use of Sentinel-1 and Sentinel-2 data for automatic detection of earthquake-triggered landscape changes: A case study of the 2016 Kaikoura earthquake (Mw 7.8), New Zealand

  • Popis výsledku anglicky

    Earthquakes can trigger numerous landslides and cause other significant changes in the landscape over large areas. This study presents a new processing scheme combining radar (Copernicus Sentinel-1) and optical satellite data (Copernicus Sentinel-2) to quickly and easily map landscape changes such as landslides, coastal uplift and changes in water bodies caused by a severe event such as an earthquake. The processing scheme has been tested for the 2016 Kaikoura earthquake (Mw 7.8), New Zealand, which impacted vast and mostly inaccessible areas, causing hundreds of landslides. The workflow combines the following change-detection methods: i) Sentinel-1 amplitude change detection ii) Sentinel-2-based detection of non-vegetated areas that occurred after the event using the atmospherically resistant vegetation index (ARVI). To get a more complex view of the surface changes caused by the Kaikoura earthquake, the available online services and tools were further tested (open source via the European Space Agency) allowing automatic detection of vertical displacements and deformations. It was concluded, that the above-mentioned approaches facilitated the assessment of earthquake-triggered changes in a comprehensive manner. The methodology is an example of how to detect earthquake landscape changes in an automatic and rapid manner. The new processing scheme for the synergic use of Sentinel-1 and Sentinel-2 data has high potential to be used for operational and scientific purposes, since it relies on globally available, free data and provides high spatial and temporal resolution. The results can be obtained and made available only a few days after an event, therefore providing significant insights into earthquake impact assessment and may also be helpful for prioritizing field work.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    20705 - Remote sensing

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/SS02030023" target="_blank" >SS02030023: Horninové prostředí a suroviny</a><br>

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Ostatní

  • Rok uplatnění

    2021

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Remote Sensing of Environment

  • ISSN

    0034-4257

  • e-ISSN

  • Svazek periodika

    265

  • Číslo periodika v rámci svazku

    November : 112634

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    20

  • Strana od-do

    nestránkováno

  • Kód UT WoS článku

    000697359400001

  • EID výsledku v databázi Scopus

    2-s2.0-85112321747