Equine Operations and Populations Dataset for the U.S.
Description
The purpose of this case is to develop a dataset that addresses the problem of not having complete information about where horse farms are located and how many horses they have.
Detailed example
Output is a national-level dataset of domestic horse operations and estimated populations.
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
Developing this dataset/model provides detailed data on horse farm locations and populations, which is essential for emergency preparedness and response and for predicting the spread of equine (horse or members of the horse family) diseases.
Controls / human review
ATO: No; PIA: Not published
Data needed
The data is created from National Agriculture Imagery Program (NAIP) images and the National Agricultural Statistics Service (NASS) Census of Agriculture, which includes number of farms by size and type, inventory and values for crops and livestock, producer characteristics, and much more.