Jupyter Notebook - Water Observations from Space (WOFS)
- Creators
- Killough, Brian
- Others:
- Open Data Cube Community
- CEOS SEO/AMA
Description
About
This notebook demonstrates the Australian Water Observations from Space (WOFS) algorithm. This water detection algorithm is an improvement over the Landsat QA water flag or the Normalized Difference Water Index (NDWI) for water identification. For more information, visit this website: http://www.ga.gov.au/scientific-topics/hazards/flood/wofs
This notebook uses global Landsat-8 data from Google Earth Engine which has been indexed to work with the Open Data Cube. The selected data is used to create a time series water product that reflects the percentage of time each pixel has been water over the entire time window. If a pixel is cloudy, it is not considered in the analysis. Users should review the "Cloud Statistics" notebook for more information about the temporal cloud cover for a given region.
This baseline notebook runs in about 4 minutes after the Google authorization step is complete. The default region (0.10 degrees square) and time window (3 years) use about 15% of the allocated RAM memory. Selecting larger regions and time windows should be done carefully to avoid exceeding the system limits or having execution times.