Short Description

  • An unsupervised learning of remote sensing to leverage exponential data growth, allowing our algorithms to detect and predict landuse changes and estimate carbon stocks.

Long Description

Exploring the application of novel machine learning and decentralised staking mechanisms to protect forests and indigenous people.

Caretakers stake funds on the well-being of a patch of forest, supporting local land owners, forest protection and restauration efforts. If satellite images show that that patch remains forested several months from then, the value of this patch increases automatically.

Our smart contract architecture connects donors from private and public sector with caretakers. We use machine learning to provide risk scores and verify outcomes.

We use a decentralized performance-based staking game to incentivize donor contribution and kickstart sustainable projects.

We want to find radical ways to exponentially stimulate climate action. We start field testing our ideas with a pilot in Brazil in early 2019 – and scale to the whole world next.

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Additional Details

  • Number of beneficiaries impacted: 1-100
  • SDG#:13
  • Other links:https://daviddao.org/papers/gainforest_2019.pdf
  • Short Description:An unsupervised learning of remote sensing to leverage exponential data growth, allowing our algorithms to detect and predict landuse changes and estimate carbon stocks.
  • Blockchain Technology:Other
  • Fundraising:Own funds
  • Stage:Proof of Concept or demo
  • Impact-first:Yes
  • Organization Type:Start-up
  • Founders:David Dao
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