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S1-GUNW within defined volcanic AOI track polygon is published to S3.
This triggers the AOI-Track Evaluator to run. Once a full track has been collected, a JSON file containing metadata about all the files within the track is published to S3.The data is run through the MintPy PGEMintPy PGE to run, which outputs the displacement time-series.
The time-series is run through the volcanic anomaly detection ML PGE, which outputs a volcano anomaly map.
Once a volcanic an AOI is defined, the system will also perform forward keep-up production of S1-GUNW products , as well as the most up-to-date time series for the area- this AOI is larger than the volcano polygon, and will include the enumeration strategy. Information for how to perform bulk processing and keep-up production can be found on the Bulk Processing and Keep-Up Ops Overview wiki page.
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S1-GUNW generation: Standard Product S1-GUNW Processing Pipeline
AOI-Track-Evaluator: S1-GUNW Completeness Evaluator for AOI-Track (is this actually what we want here, or is there some other page we need to link and/or create to describe this step?)
MintPy PGE: Displacement Time-Series using MintPy and Developer Information
Volcanic Anomaly Detection ML PGE: Volcanic Anomaly Detection
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User Interfaces (who is a user/operator? Developer already on our team or an outside person?)
User actions:
Defines AOI track polygon for volcano, including start time, end time, and separate, smaller bbox.
If monitoring two or more volcanoes separated by a water body, add two separate AOI tracks with identical information except for different bboxes.Leave a buffer of (TBR) around edge of bbox/polygons.
Creates a trigger rule for desired N-pairings.
Logs into system and downloads most recent time-series.
Logs into system and browses potential anomalies.
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