Access to Satellite Data for AI-Based Risk Management of Produce Safety in Farms

The objective of this project is to develop a high-resolution, spatially explicit dataset of leafy green farm locations across California and detect CAFOs in other states along with relevant crop and environmental data, to support outbreak investigation and pre-harvest risk assessment. Specifically, the vendor shall: Identify and map both current (most recent season) and historical (last five years) leafy green farm boundaries, classifying each by type of leafy green produce in California.

Determine the number of harvest cycles per season for each identified leafy green crop, incorporating this information into the spatial dataset to enhance understanding of farm activity and potential risk exposure. Detect and classify CAFOs in selected high-priority states that pose elevated risk for foodborne outbreaks.

For each CAFO, the vendor shall generate spatial boundaries and attribute data, including area, proximity to water bodies, operational status (active/inactive), and classification confidence metrics. This information will be integrated into a user-friendly ArcGIS dashboard to support stakeholders involved in food safety, agriculture, and public health.