OMB Individually Reported
Global Detection of Historical Harmful Algal Blooms via combined Satellite Data and Deep Learning Methods
Low riskExact public inventory row
Description
Create a global-scale geospatial database of HABs occurrences over the past 40 years and compile in-situ measured HAB events and related parameters, remotely sensed data, and machine learning methods.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Provide resource managers, researchers, and the public with a novel ability to track and compare HABs occurrences across time and space, which could identify systematic trends and patterns that affect multiple inland water bodies.
Controls / human review
ATO: No; PIA: Not published