2423614
Cooperative Agreement
Overview
Grant Description
SBIR Phase II: Registration of below-canopy, above-canopy, and satellite sensor streams for forest inventories.
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 U.S. 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.
Subawards are not planned for this award.
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 U.S. 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.
Subawards are not planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH PHASE II (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE II", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23516
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Somerville,
Massachusetts
02143-3260
United States
Geographic Scope
Single Zip Code
Gaia Ai was awarded
Cooperative Agreement 2423614
worth $1,000,000
from National Science Foundation in September 2024 with work to be completed primarily in Somerville Massachusetts United States.
The grant
has a duration of 2 years and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Cooperative Agreement was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase II Programs (SBIR/STTR Phase II).
SBIR Details
Research Type
SBIR Phase II
Title
SBIR Phase II: Registration of Below-Canopy, Above-Canopy, and Satellite Sensor Streams for Forest Inventories
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.
Topic Code
ET
Solicitation Number
NSF 23-516
Status
(Ongoing)
Last Modified 9/25/24
Period of Performance
9/15/24
Start Date
8/31/26
End Date
Funding Split
$1.0M
Federal Obligation
$0.0
Non-Federal Obligation
$1.0M
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2423614
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
YN7ZYGUBZMZ5
Awardee CAGE
9YCK0
Performance District
MA-07
Senators
Edward Markey
Elizabeth Warren
Elizabeth Warren
Modified: 9/25/24