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This project is adapted from the original CNES S1tiling processing chain available here : https://github.com/CNES/S1Tiling.
For more documentation please refere to this repository.
## Eodag config file
This is an example of eodag configuration file
```
peps:
priority: # Lower value means lower priority (Default: 1)
search: # Search parameters configuration
download:
extract: # whether to extract the downloaded products (true or false).
outputs_prefix: # where to store downloaded products.
dl_url_params: # additional parameters to pass over to the download url as an url parameter
delete_archive: # whether to delete the downloaded archives (true or false, Default: true).
auth:
credentials:
username: your@email.com
password: password
```
## S1Processor config file
Extract of S1Processor.cfg.
This file contains settings for the input/output folders used by s1tiling, as well as the various processing parameters: date, tile, download, etc. The file is clearly annotated.
Folders output, s1images, srtm, eodag and eventually tmp must link to the host. With the below execution command it must be in "/home"
```[Paths]
# Path for result tiled images
output : /home/data_out
# Path to store the S1 images to be processed
s1_images : /home/raw
# Path to geoid model
# geoid_file : ./Geoid/egm96.grd
# Path to a temporary file
tmp : /home/tmp
# tmp : %(TMPDIR)s/s1tiling
```
## Execution
The main change from the original container is the integration of jupyter-lab. When executing the container, you need to assign a communication port to access Jupyter from your browser. To retrieve processed data more easily, we create a bind folder with the "--mount" command. In this folder, you'll place the SRTM folder containing the tiles in .hgt format, as well as the configuration files eodag.yml and S1Processor.cfg.
```
docker run -it -p 8888:8888 --mount type=bind,source="/path/to/target",target=/home s1tiling
```