Python wrapper for the ASF SearchAPI
import asf_search as asf
import json
results = asf.granule_search(['ALPSRS279162400', 'ALPSRS279162200'])
print(f'Granule search results: {json.dumps(results, indent=2)}')
wkt = 'POLYGON((-135.7 58.2,-136.6 58.1,-135.8 56.9,-134.6 56.1,-134.9 58.0,-135.7 58.2))'
results = asf.geo_search(platform=[asf.PLATFORM.SENTINEL1], intersectsWith=wkt, maxResults=10)
print(f'Geographic search results: {json.dumps(results, indent=2)}')
In order to easily manage dependencies, we recommend using dedicated project environments via Anaconda/Miniconda or Python virtual environments.
asf_search can be installed into a conda environment with
conda install -c conda-forge asf_search
or into a virtual environment with
python -m pip install asf_search
Programmatically searching for ASF data is made simple with asf_search. Several search functions are provided:
geo_search()
Find product info over an area of interest using a WKT stringgranule_search()
Find product info using a list of scenesproduct_search()
Find product info using a list of productssearch()
Find product info using any combination combination of search parametersstack()
Find a baseline stack of products using a reference scene- Additionally, numerous constants are provided to ease the search process
Examples of all of the above can be found in examples/
Instance | Branch | Description, Instructions, Notes |
---|---|---|
Stable | stable | Accepts merges from Working and Hotfixes |
Working | master | Accepts merges from Features/Issues and Hotfixes |
Features/Issues | topic-* | Always branch off HEAD of Working |
Hotfix | hotfix-* | Always branch off Stable |
For an extended description of our workflow, see https://gist.github.com/digitaljhelms/4287848