VegScape/CropCASMA Data Portals
Description
Shows crop conditions and soil moisture availability, which serve as inputs to increase the quality of crop modeling
Detailed example
Provides both quantitative and qualitative output products in support of Crop Progress and Condition and Disaster Assessment reporting
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
Supplements weekly Crop Progress and Condition Reports, provides direct input into disaster assessments on agriculture, and provides early disaster anomaly warnings
Controls / human review
ATO: No; PIA: Not published
Data needed
NASA Moderate Resolution Imaging Spectroradiometer (MODIS), NASA Soil Moisture Active Passive (SMAP), National Agriculture Statistics Service (NASS) historical crop progress and condition reports.