← Back to NASA Technology Projects

Machine Learning for Agriculture Crop Damage Identification and Assessment from Intense Thunderstorms

Completed TRL 4 (started at 2, targeting 4)

Description

The goal of this CIF proposal is to develop machine learning-based (ML) models for the automated identification of severe weather damage to agricultural crops, using NASA land surface imaging. Damage detections will be verified using higher spatial resolution optical and synthetic aperture radar (SAR) data sets. T

Benefits

his CIF effort advances upon the current state of the art where NASA’s expertise will develop practical solutions supporting the agriculture community and stakeholders in (re)insurance, crop analysis, and food security sectors.

Details

Technology areaSoftware, Modeling, Simulation, and Information Processing > Software Development, Engineering, and Integrity > Real-Time Software
ProgramCenter Innovation Fund: MSFC CIF (MSFC CIF)
Lead organizationMarshall Space Flight Center, Huntsville, AL
Start date2021-10-01
End date2022-09-30

Project contacts

Listed on TechPort itself — the most direct way to ask about this specific project.

How to get involved

This is early/mid-stage (TRL 4) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

None of these are guaranteed paths for this specific project — TechPort itself doesn't have an "apply" button. Reaching out to the contact(s) above with a specific question is usually the fastest way to find out what's actually open.