kaikouradammedlakes_public
Kaikoura landslide dammed-lakes detection
Science Score: 49.0%
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Kaikoura landslide dammed-lakes detection
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README.md
Landslide dammed-lakes detection and monitoring after the Kaikoura earthquake in New Zealand
This repository centralizes the main processing steps to detect and monitor landslide-dammed lakes in NZ. It accompanies a paper published in STOTEN This study is part of the AW-funded RiCoLa project.
Please cite as:
Abad, L., Hlbling, D., Spiekermann, R., Prasicek, G., Dabiri, Z., & Argentin, A.-L. (2022). Detecting landslide-dammed lakes on Sentinel-2 imagery and monitoring their spatio-temporal evolution following the Kaikura earthquake in New Zealand. Science of The Total Environment, 153335. https://doi.org/10.1016/j.scitotenv.2022.153335
The objective of the study is to automatically map the landslide-dammed lakes caused by the 2016 Kaikura earthquake in New Zealand and to monitor their evolution at different points in time, using time series of Sentinel-2 imagery and GEE.
The figure below shows an overview of the methodology followed:
The main analysis was performed on Google Earth Engine (GEE), and its corresponding repository can be found here. To access the code files, you will need to have a GEE account.
If you would only like to see the main code, without a GEE account, see the gee-code directory.
The resulting datasets from the analysis are archived as assets here.
Some steps were done outside GEE including:
The resulting layer was then ingested into GEE.
A preview of how the GEE editor would look like with our results is shown below:
Acknowledgements:
This research is supported by the Austrian Academy of Sciences (AW) through the project RiCoLa (Detection and analysis of landslide-induced river course changes and lake formation) and by the New Zealand Ministry of Business, Innovation and Employment research program Smarter Targeting of Erosion Control (STEC) (Contract C09X1804).
Further dissemination:
Previous work was presented at the EGU General Assembly 2020, abstract is available at:
Abad, L., Hlbling, D., Spiekermann, R., Dabiri, Z., Prasicek, G., and Argentin, A.-L.: Mapping and monitoring of landslide-dammed lakes using Sentinel-2 time series - a case study after the 2016 Kaikura Earthquake in New Zealand, EGU General Assembly 2020, Online, 48 May 2020, EGU2020-572, https://doi.org/10.5194/egusphere-egu2020-572, 2019
It was also presented at the Geo For Good 2020 via this poster and a lightning talk on the topic as part of the Public Sector Meetup during the summit.
Owner
- Name: Lorena Abad Crespo
- Login: loreabad6
- Kind: user
- Location: Salzburg, Austria
- Company: University of Salzburg
- Website: http://loreabad6.github.io
- Repositories: 55
- Profile: https://github.com/loreabad6
Researcher - MSc. Geospatial Technologies - Environmental Engineer / Remote Sensing for the Environment - Spatial Analyses - R Programming - Statistics
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| Name | Commits | |
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| loreabad6 | l****6@g****m | 13 |
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