Tula van Balen of BCG presented H3 Parcel Suitability at the H3 Conference 2026 in New York City: a single Fused canvas that answers how well suited a piece of land is by putting every relevant dataset on the same H3 grid. The session wasn't recorded, so this post walks through the canvas Tula presented.
Kristin Scholten is a farmer turned data scientist in the advanced analytics department at Nationwide, and she is building OpenFields, an AI prediction engine for agriculture. At the H3 Conference 2026 in New York City, she argued that crop acreage is decided months before any satellite can see a plant, and showed how she used H3 to put a crop probability on every field in North Dakota.
Mo Fotouhi is a Senior Manager of Data Science at John Deere, where he leads teams working on geospatial intelligence and AI for agriculture. At the H3 Conference 2026 in New York City he gave a lightning talk he described as a love letter to H3 with footnotes: H3 makes agricultural data easy to combine, but field-level questions need finer detail and a sense of time that H3 does not provide on its own.
TL;DR Kristin created a UDF to mask cropland areas using USDA data and run a Zonal Statistics workflow for corn yield predictions.
A raster, a vector, and an array walk into a bar…
Ok I will spare you the corny jokes.
But seriously, I was facing a problem with these three data types when I approached Fused. It felt impossible to join this information together in a meaningful way. Fortunately, I was quickly proven wrong with the power of UDFs. Let me catch you up.
TL;DR Fused streamlined Kristin's workflow to integrate CSV and NetCDF data directly from S3.
Ever tried to make sense of the myriad file types in spatial data science and felt like you've wandered into a linguistic labyrinth? Trust me, you're not alone. As a data scientist who's spent more time wrangling datasets than I care to admit, I thought I'd take a casual stroll down memory lane with an old high school friend: regression models. Just a simple plot of actual vs. predicted, right? But when spatial data's involved, you can't just sit back and relax—you've got to keep one eye on the geometries.
I'm currently working on an agricultural project, and growing up on a farm gives me a personal stake in this. This blog illustrates my solution to the geometry debacle. I'll first take you to the area where I grew up: Lyon County.