Digital Earth Pacific Coastlines

This is a work-in-progress adaptation of Digital Earth Australia (DEA) and Digital Earth Africa Coastlines products for the Pacific nations. Please refer to the following for a description of the algorithms on which we based this work:

Bishop-Taylor, R., Nanson, R., Sagar, S., Lymburner, L. (2021). Mapping Australia's dynamic coastline at mean sea level using three decades of Landsat imagery. Remote Sensing of Environment, 267, 112734. Available: https://doi.org/10.1016/j.rse.2021.112734

Bishop-Taylor, R., Sagar, S., Lymburner, L., Alam, I., Sixsmith, J. (2019). Sub-pixel waterline extraction: characterising accuracy and sensitivity to indices and spectra. Remote Sensing, 11 (24):2984. Available: https://doi.org/10.3390/rs11242984

We have adapted the algorithms where necessary to account for differences in the study area and the available input datasets, as well as for performance. A full writeup is in process.

Processing

Coastline creation consists of five primary steps:

1. Calculating tides for each location and available landsat image. The code for this is in dep_coastlines/calculate_tides.py. (See the notes in that file on tide model data location.)
2. Filtering landsat images based on the tide values and creating annual mosaics. This is done in dep_coastlines/tide_corrected_mosaics.py.
3. Post-processing the annual mosaics to remove clouds, and mask the analysis zone to the coastal zone. In dep_coastlines/clean_rasters.py. Note that this step requires a model file.
4. Delineating the coastline using the cleaned annual mosaic (a second step in the script in #3).
5. Calculating rates of change over time and merging data into final products (see dep_coastlines/continental.py).

Processing is done over an grid of arbitrary size, as defined in dep_coastlines/grid.py using Landsat Collection-2 Level-2 (tiers 1 and 2) data loaded from the Microsoft "Planetary Computer". The tides dataset is TPXO9.

Steps 2, 3, and 4 were accomplished using a deployment of argo. The workflows for these are saved in .argo/. Steps 1 and 5 were completed locally using a modest workstation-level computer. The dockerfile for step 1 is Dockerfile.tides. The remaining step use Dockerfile.