Hatfield receives grant from Microsoft’s AI for Earth program, accelerating our work in caribou habitat disturbance mapping in northern Canada
Apr 08, 2021
A grant from Microsoft’s AI for Earth program will support Hatfield’s work on boreal caribou, whose populations are in decline in the boreal forest regions of Canada due to habitat fragmentation. With the resources and support from AI for Earth, Hatfield will advance research using satellite Earth observation data and deep learning methods to identify and classify linear habitat disturbances. With this Earth observation data captured across millions of hectares of the boreal caribou ranges, we will develop automated methods to map caribou habitat, both frequently and affordably, to support the decision-making surrounding and implementation of new caribou conservation efforts.
As a member of the Microsoft AI for Earth program, Hatfield joins a cohort of more than 600 organizations in over 85 different countries supported by Microsoft to make a positive impact on the planet through innovative work, while transforming the way the world addresses environmental challenges. Our work relies on access to cloud computing technologies in order to map up to one billion hectares in Canada for linear disturbances, and achieve our overarching goal of supporting boreal caribou conservation. We hope this research will be used in the future as monitoring and assessment solutions by governments, First Nations, industry organizations and NGOs.
AI for Earth is a $50 million, 5-year program by Microsoft providing chosen organizations with access to AI tools and resources, with a particular focus in the areas of water, biodiversity, climate change, and agriculture. As a member of AI for Earth and Microsoft’s Partner network, Hatfield’s team of data scientists and software engineers are focused on helping our clients to embrace cloud native environmental data analytics.
Learn more about Microsoft’s AI for Earth program, or read more about our caribou habitat disturbance mapping here.
