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Publiclandsdata.com – US public lands visitation, reservations, economy

Hacker News

Publiclandsdata.com – US public lands visitation, reservations, economy

Federal agencies publish an enormous amount of recreation data, but much of it is “hidden” in random CSV files and distributed across various agency websites. I built this as a one-stop resource to see recreation data in one place and organized the data into clearer takeaways and visualizations where possible. More on the process: https://read.hereandthere.club/p/publiclandsdatacom-a-home-f...

Visit productView on Hacker NewsSep 17, 2026
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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

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Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: visual · Missing: mac, agents, macos
28%28% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
27%27% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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