SBIR Phase II: Registration of Below-Canopy, Above-Canopy, and Satellite Sensor Streams for Forest Inventories

Gaia Ai, Inc, Somerville MA

Investigators

Abstract

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project will be in scaling current resources available for collecting the data that is needed for making decisions on how to best manage trees and forests. This technology will be used broadly for scaling conservation work and scaling adoption of sustainable forest management practices, for identifying areas at high risk of wildfires that need to be proactively treated to mitigate that risk, and for verifying stewardship work that enhances biodiversity values in a given forest. This technology will help address the growing labor challenges currently facing the forest management industry, enabling foresters and indigenous forest stewards to manage much more land with the constrained resources they have available. This work will create new jobs and market opportunities for US citizens from the stewardship projects that come from the identified opportunities, be it around wildfire risk management treatments or restoring forests for carbon projects. All of these benefits for the country and its citizens align with the National Science Foundation’s core mission of advancing the nation’s health, prosperity, and welfare. The technology being developed is a hardware sensor backpack and an AI tool for processing the collected data into useful forest biometric indicators. This undertaking involves designing a sophisticated AI technology similar to that used in autonomous vehicles for building a map of the world around them, but designed from the ground up to work for processing data in natural environments to map out forests. This research will refine this technology to create an operationalized product for use by forestry professionals to support the decisions they make around actively managing working forests. This includes conserving areas of old growth trees, verifying the carbon sequestered in sustainable forestry stewardship projects, prescribing targeted treatments for mitigating risk for wildfire, and auditing forest management practices for maintaining and enhancing the biodiversity values of a given forested area. Specifically, the scope of this project will be to extend the capabilities of the AI technology built out in the Phase I work to be able to measure more dense forests, to output broader biomass measurements to be used in carbon verification and fuel load measurements to assess wildfire risk, and to reliably and accurately scale the below-canopy measurements with satellite imagery over very large forested areas. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.