Hey everyone — I wanted to share a project I’ve been working on that heavily leverages ArcGIS REST endpoints from multiple state and federal agencies.
Over the past year I’ve built a 14-state data pipeline that unifies public ArcGIS REST services from:
- Alaska Department of Fish & Game (ADF&G)
- Pennsylvania Fish & Boat Commission (PASDA / PFBC)
- Maryland Fish & Wildlife (FWC)
- USGS Water Services API
Each state provides a unique challenge — different geometry types, coordinate systems, pagination rules, and field schemas. My pipeline normalizes these in TypeScript and outputs unified JSON for use in mapping apps and APIs.
Example use cases
- Alaska: 9,031 officially cataloged water bodies (ADF&G AWC API) + 222 real-time stocking records
- Pennsylvania: PASDA “Best Fishing Waters” + PFBC trout stocking database (real fish quantities and species)
- Florida: FWC MRGIS boat ramps + Fish Management Areas (polygon-to-centroid transformation)
- USGS: Real-time water temperature, dissolved oxygen, and pH enrichment
Technical highlights
- Web Mercator → WGS84 coordinate transformation
- ArcGIS REST pagination using `resultOffset` / `resultRecordCount`
- Parallel data fetching (`Promise.all`) for 10K+ features
- Layer normalization and enrichment with USGS live feeds
- Cached API response times: 53 ms (from 1.8 s initial load)
Here’s a visual example of the Alaska implementation (9,000+ locations):
👉 https://youtu.be/Xwdm5tY2XU8
I also wrote about how I enriched Minnesotas waters as well: https://medium.com/@jcdesign/how-i-scaled-minnesotas-fishing-intelligence-through-dnr-data-enrichmen...
If anyone here has worked on large-scale ArcGIS REST normalization or best practices for cross-state schema harmonization, I’d love to compare notes — especially around rate-limits, batch queries, and geometry simplification.
Thanks,
John Carter
My Website: www.fishdata.co
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