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Iceland Vegetation Viewer Using WebGL

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Iceland Vegetation Viewer Using WebGL

We at Visual Perspective just released an open source, web-based, remote sensing viewer ( https://iceland.visualperspective.io/ ). With this viewer, you can explore Iceland’s vegetation over space and time. There is an accompanying blog post which goes over Normalized Difference Vegetation Index (NDVI) and how to use the viewer ( https://visualperspective.io/blog/iceland-ndvi-viewer ). Source code is at: https://github.com/VisualPerspective/ndvi-viewer WebGL is used for the display, but also for GPGPU averaging of NDVI in the selected region.

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual, using, code · Missing: mac, agents, macos
76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: just released, open source, io · Missing: https docs, excited, exist
71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
40%40% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
15%15% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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