We implement practical community-based AI solutions that improve the health and welfare of the communities we live in and the planet we live on. Together with our partners, we deploy these solutions to improve health and welfare, reduce inequality, fight climate change, and aid conservation efforts that protect endangered species and preserve our oceans and forests.
We are working on several exciting projects that utilizes remote sensing data from low earth orbit satellites and computer vision to aid on the ground conservation efforts. Remote areas in the jungle are difficult to patrol and often put a strain on the limited resources of conservationists. Added to that the overall lack of data on changes in the forest and movement of animals make it difficult to accurately count species and measure conservation efforts. With our technology and satellite partners we are utilizing computer vision models to monitor and detect changes in the forest canopy to map the extent and spread over time of invasive plant species. The goal of these projects is to automatically generate quality metrics and data on changes in the forest canopy, prove the viability of utilizing satellite imagery and machine learning models in a cost-efficient and scalable manner to support conservation efforts.
HISTORICAL ANALYSIS UTILIZING SATELLITE IMAGERY AND MACHINE LEARNING
Pu Mat National Park
We are collaborating with Save Vietnam Wildlife and Satellite Imaging Corporation to map the Pu Mat National Park, located in Nghệ An Province in Vietnam's North Central Coast region. By utilizing historical satellite imagery and Machine Learning technology we aim to categorize the park, such as vegetation types. This data will then be utilized to track changes in the park's composition over time, allowing for future prediction of potential negative impacts the external and internal environment might have on the remaining wildlife in the park.
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