OMB Individually Reported
Reducing elevation error in coastal wetland digital elevation models
Low riskExact public inventory row
Description
The objective of this use case was to train/deploy a random forest regression model to reduce elevation error in a coastal wetland digital elevation model.
Detailed example
Prediction
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
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
The model led to an enhanced digital elevation model for coastal wetland areas.
Controls / human review
ATO: No; PIA: Not published
Data needed
In situ elevation data was collected and used for the training and testing data development. The predictor variables used in the model included elevation data and satellite imagery.