Registration open for Data Challenge #2: Satellite-Based Orchard Stress Mapping in California's Central Valley

Registration is open for Data Challenge #2: Satellite-Based Orchard Stress Mapping, a competitive four-week AI code sprint open to university teams and individual technologists. The challenge launches on April 13 with a virtual kickoff webinar.

California's Central Valley produces more than $10 billion annually in tree nuts and stone fruits, yet detecting orchard stress — from water deficit, nutrient deficiency, or soil variability — remains costly and labor-intensive. Data Challenge #2 asks competitors to build AI pipelines using freely available Sentinel-2 satellite imagery and geospatial datasets to automatically detect and map underperforming zones across Central Valley orchards, addressing a problem growers have identified as an operational burden.

Teams will analyze multi-season vegetation index time series to identify persistent stress zones, explore probable causes using open datasets (soil, terrain, irrigation data), and test their pipelines across different orchard sites spanning almond, pistachio, and walnut crops in Kern, Tulare, Fresno, and Stanislaus counties. The challenge is hosted on the National Data Platform (NDP).

Submissions will be judged by a panel of agricultural, remote sensing, data science, and agtech experts on:

• Technical quality (35%)

• Methodology and reproducibility (25%)

• Innovation (20%)

• Grower applicability (10%)

• Communication (10%)

Each team must submit a reproducible code pipeline and PDF technical report. Submission deadline is May 8, with winners announced at an awards webinar on May 26.

Cash prizes will be awarded to the top three teams:

• First place: $1,500

• Second place: $750

• Third place: $400

Participants can register here.