Our machine learning models predict and prove how nature positive practices will impact the health of land. All our models are reviewed by our partners in the scientific community to ensure that they are appropriate, and are tested to ensure that they are statistically valid.
We monitor plots onboarded onto Landler using several types of satellite data; including pictures of the Earth’s surface, thermal measurements and observations from radar. This data is combined to build models which predict the impact of nature positive practices at scale.
We collect field data from private and public databases. Plus, we work with our customers to collect samples and measurements from their land. This data is used to train our models to predict the impact of nature positive practices across carbon, water, soil and biodiversity.
What our models measure
What I find particularly remarkable is the team's willingness to critically reflect on their own approach”
CEO | Data Scientist | Author