This repository contains training material that corresponds to the training manual provided. It is designed to introduce tools and analysis for monitoring coastal and riverine geomorphology in a region heavily impacted by climate change. The materials provide an introduction to Earth Observation (EO) and Google Earth Engine (GEE) through step-by-step workflows (notebooks) to provide insights through changes in surface water. It is a requirement that you have signed up for GEE in order to follow the material provided.
The material is divided into 4 modules:
- Module 1: Introduction to GEE.
- Module 2: Surface water classification at scale.
- Module 3: Timeseries analysis of river morphology and early warning identification.
- Module 4: Coastal analysis with tidal context.
The work is sponsored by the UN Climate Technology Centre & Network (CTCN). The CTCN promotes the accelerated transfer of environmentally sound technologies for low carbon and climate resilient development at the request of developing countries. They provide technology solutions, capacity building and advice on policy, legal and regulatory frameworks tailored to the needs of individual countries.
If you find this repository useful in your research, particularly the dataset in Module 3, please consider citing the following papers. Thank you.
- Druce, D.; Tong, X.; Lei, X.; Guo, T.; Kittel, C.M.M.; Grogan, K.; Tottrup, C. An Optical and SAR Based Fusion Approach for Mapping Surface Water Dynamics over Mainland China. Remote Sens. 2021, 13, 1663. https://doi.org/10.3390/rs13091663
- Tottrup, C.; Druce, D.; Meyer, R.P.; Christensen, M.; Riffler, M.; Dulleck, B.; Rastner, P.; Jupova, K.; Sokoup, T.; Haag, A.; Cordeiro, M.C.R.; Martinez, J.-M.; Franke, J.; Schwarz, M.; Vanthof, V.; Liu, S.; Zhou, H.; Marzi, D.; Rudiyanto, R.; Thompson, M.; Hiestermann, J.; Alemohammad, H.; Masse, A.; Sannier, C.; Wangchuk, S.; Schumann, G.; Giustarini, L.; Hallowes, J.; Markert, K.; Paganini, M. Surface Water Dynamics from Space: A Round Robin Intercomparison of Using Optical and SAR High-Resolution Satellite Observations for Regional Surface Water Detection. Remote Sens. 2022, 14, 2410. https://doi.org/10.3390/rs14102410