eo-rbm-proc

EO River Basin Monitoring (Flood Mapping) using EO SNAP Toolbox.

Steps performed by the processor.

• terrain correction
• de-speckling
• image calibration
• orbit file application
• subsetting of data using vector file input
• image reclassification using band math calculations
• land cover downloading
• exporting of product objects to result file

Usage

To produce

./eo-rbm.py \
   --product-path data/S1A_IW_GRDH_1SDV_20180415T163146_20180415T163211_021480_025003_8E79.zip \
   --shape-path data/boundary.shp \
   --result-path ./final_mask

To obtain help for the parameters, run

$ ./eo-rbm.py -h
usage: eo-rbm.py [-h] --product-path PRODUCT --shape-path SHAPE --result-path RESULT

EO Flood Monitoring

optional arguments:
  -h, --help            show this help message and exit

required named arguments:
  --product-path PRODUCT
                        Sentinel 1 data product archive
  --shape-path SHAPE    Shape file in .shp format
  --result-path RESULT  Path to resulting TIF file (w/o .tif)
$

Example run

$ ./eo-rbm.py --product-path test-data/S1A_IW_GRDH_1SDV_20180415T163146_20180415T163211_021480_025003_8E79.zip --shape-path test-data/island_boundary2.shp --result-path ./final_mask-S1A
INFO: org.esa.s2tbx.dataio.gdal.GDALVersion: GDAL not found on system. Internal GDAL 3.0.0 from distribution will be used. (f1)
INFO: org.esa.s2tbx.dataio.gdal.GDALVersion: Internal GDAL 3.0.0 set to be used by SNAP.
INFO: org.esa.snap.core.gpf.operators.tooladapter.ToolAdapterIO: Initializing external tool adapters
INFO: org.esa.snap.core.util.EngineVersionCheckActivator: Please check regularly for new updates for the best SNAP experience.
INFO: org.esa.s2tbx.dataio.gdal.GDALVersion: Internal GDAL 3.0.0 set to be used by SNAP.
Width: 25220 px
Height: 16774 px
Name: S1A_IW_GRDH_1SDV_20180415T163146_20180415T163211_021480_025003_8E79
Band names: Amplitude_VH, Intensity_VH, Amplitude_VV, Intensity_VV
INFO: org.hsqldb.persist.Logger: dataFileCache open start

100% done.

100% done.
Width: 4871 px
Height: 4035 px
Name: Subset_S1A_IW_GRDH_1SDV_20180415T163146_20180415T163211_021480_025003_8E79_Orb
Band names: Amplitude_VH, Intensity_VH, Amplitude_VV, Intensity_VV

100% done.

100% done.

100% done.

100% done.

50%100% done.

100% done.

100% done.
writing product ...
done

Most of the time (~95%) is taken by writing of the product.

Visualisation

Use eo-rbm-vis.py to visualise results.

On an example of the product produced in the previous section.

./eo-rbm-vis.py final_mask-S1A.tif

Produces the following result

Building Docker image

docker image build . -t sixsq/eo-rbm:latest 
docker image push sixsq/eo-rbm:latest

Running Docker image

Mount directory with the product and shape files to the container. Save the result to the mounted volume.

 docker run --rm -it -v $(pwd)/test-data:/data sixsq/eo-rbm:latest \
    --product-path /data/S1A_IW_GRDH_1SDV_20180415T163146_20180415T163211_021480_025003_8E79.zip \
    --shape-path /data/island_boundary2.shp \
    --result-path /data/final_mask_S1A_IW_GRDH_1SDV_20180415T163146_20180415T163211_021480_025003_8E79

Extras

Building the image for manual exploration

If the goal is to obtain an interface for manual exploration of EO data, while still having the SNAP toolbox available for processing, then you can use Dockerfile.jupyter to build a new Docker image that inherits everything from the one above, plus Jupyter Notebook.

Simply make sure the image from above has already been built, and run:

docker build -f Dockerfile.jupyter . -t sixsq/eo-rbm:jupyter

To launch this image:

# replace /path/to/eodata with the path where your data is within the host
docker run -it -p 8888:8888 -v /path/to/eodata:/eodata sixsq/eo-rbm:jupyter 

# grab the TOKEN from from output

Then you can access http://localhost:8888/?token=TOKEN and your notebook should be ready. You'll find your data under /eodata.