Commonwealth of Massachusetts

Executive Office of Energy and Environmental Affairs

Request for Information: Remote Sensing, Artificial Intelligence, Field Data Collection, and Other Approaches for Measuring Forest Carbon

Baselines and Monitoring Changes Over Time

COMMBUYS Bid Number BD-27-1042-ENV-ENV01-134465

Project # FY27RES0002

Issue Date: October 14, 2026

Respondents to this Request for Information (RFI) are invited to respond to any or all of the questions in this document. Responses to this RFI shall serve solely to assist the Commonwealth in understanding the current state of technology and the marketplace with regards to the solicited information or to inform the development of a possible solicitation for a Request for Responses (RFR) or other procurement in the future. This RFI does not in any way obligate the Commonwealth to issue or amend a solicitation or to include any of the RFI provisions or responses in any solicitation. Responding to this RFI is entirely voluntary and will in no way affect the Commonwealth’s consideration of any proposal submitted in response to any subsequent solicitation, nor will it serve as an advantage or disadvantage to the respondent in the course of any procurement that may be subsequently issued or amended.

This is a single document associated with a Request for Information (RFI) that can be found on www.COMMBUYS.com. Interested parties are responsible for reviewing and adhering to all information, forms and requirements for the RFI.

http://www.commbuys.com/

Background

Massachusetts has established climate, conservation, and biodiversity commitments, including achieving net zero greenhouse gas emissions in 2050 and protecting 30% of the Commonwealth’s land by 2030 and 40% by 2050. Through initiatives such as Forests as Climate Solutions, the 2023 Recommendations of the Climate Chief, the Clean Energy and Climate Plans for 2025/2030 and 2050, and the Biodiversity Goals for Massachusetts, the Commonwealth has identified forest conservation as an important tool in reducing emissions and increasing carbon sequestration, protecting biodiversity, and advancing climate commitments.

The Executive Office of Energy and Environmental Affairs and the Office of Climate Innovation and Resilience are interested in understanding current best practices and recent technological, methodological, and marketplace developments in remote sensing data sources and technologies (e.g. LiDAR; high resolution or hyperspectral imagery; aerial, satellite, or autonomous platforms), in situ field data collection, modeling, and related methods (e.g. artificial intelligence) for spatially explicit estimates of forest conversion, carbon stocks, and changes in forest extent and carbon stocks over time. The Commonwealth is interested in methodologies applicable to aboveground biomass, belowground biomass, and soil organic carbon, as well as identifying areas undergoing permanent forest loss, forest degradation, forest regeneration, and active or passive reforestation or afforestation. Through this RFI, the Commonwealth seeks information from entities experienced in measuring and monitoring changes to forest carbon and forest land extent using currently available and emerging technologies and methodologies; the accuracy, precision, uncertainty, spatial resolution, and temporal resolution of available approaches; methods for detecting changes associated with forest growth, management, harvesting, natural disturbance, and land-use change; potential costs of systems; how these data sources and methodologies compare to one another in terms of costs and utility of information gained; and additional considerations. Responses to this RFI may inform a future competitive procurement process.

Current Forest Monitoring Program by State Agencies

• The state monitors its forests on the landscape and project levels, for both short-term and long-term timeframes to evaluate forest status and assess forest conditions after a disturbance or management action.

• The state also monitors statewide annual carbon flux on Massachusetts natural and working lands against a 1990 baseline, using greenhouse gas inventory methodology from the U.S. Environmental Protection Agency. The U.S. Forest Service’s Forest https://www.mass.gov/info-details/forests-as-climate-solutions https://www.mass.gov/info-details/forests-as-climate-solutions https://www.mass.gov/info-details/recommendations-of-the-climate-chief https://www.mass.gov/info-details/massachusetts-clean-energy-and-climate-plan-for-2025-and-2030 https://www.mass.gov/info-details/massachusetts-clean-energy-and-climate-plan-for-2050 https://www.mass.gov/info-details/biodiversity-goals-for-massachusetts

Inventory and Analysis data are used for the forest carbon stock change component of that methodology.

• Landscape-level monitoring by leaf-on and leaf-off LiDAR examines broader patterns and trends across regions, ownerships, or ecological boundaries, providing insight into large-scale changes, cumulative impacts, and long-term forest resilience.

• Project-level monitoring is conducted by state staff through regular field measurements of 2000+ plots on state-owned land across Massachusetts, as part of the Commonwealth’s Continuous Forest Inventory. It focuses on a specific site or management action, evaluating conditions and outcomes to determine whether objectives were met and whether follow-up actions are needed. Specific metrics include tree species, forest type, forest heath/condition, forest structure, and aboveground biomass.

The table below summarizes data collected via different types of monitoring.

Metrics Measured by Different Monitoring Approaches

Continuous Forest Inventory Leaf-off LiDAR Leaf-on LiDAR

Collection Method On the ground Remote Remote

Scale Site Level Landscape Level Landscape Level

Tree Species Yes No No

Forest Type Yes Limited Yes

Forest Health/ Condition Yes No No

Vertical Structure Yes Yes Limited

Canopy Structure Yes Yes Yes

Understory Structure Yes Yes No

Above Ground Biomass Yes Limited Yes

Captures Below Ground Biomass No No No

LiDAR Project with University of Massachusetts and Continuous Forest Inventory The Division of Fisheries and Wildlife (MassWildlife) is working with the University of Massachusetts Amherst - Itter Lab to analyze Western Mass LiDAR (2024 data recently made available) and develop forest structural metrics, compare it with Eastern Massachusetts forest structural metrics, and demonstrate utility of datasets for wildlife and habitat planning at a MassWildlife Wildlife Management Area. The project was designed to characterize a variety of structural forest metrics for wildlife suitability based on available "leaf-off" LiDAR available through USGS for Massachusetts.

• The Western Massachusetts LiDAR results were processed so they are compatible with the previously developed products for the eastern portion of the state. We now have a statewide dataset that is contiguous and uniformly processed.

• The LiDAR products received are valuable in planning landscape-level approaches to management.

• This data may be used for:

ο Characterization of canopy height heterogeneity at a landscape and patch scale ο Comparison of understory to overstory structure ο Targeting specific structural components for wildlife and predicting species-specific abundance and habitat management potential This LiDAR information combined with Continuous Forest Inventory plot data and Natural Community characterizations create more accurate and robust data sets.

RFI Timeline

Responses must be submitted electronically via www.COMMBUYS.com.

Activity Date RFI release 10/14/2026 Vendor questions due (optional) 10/23/2026 at 5:00 AM Responses to vendor questions posted online (estimated)

10/28/2026

Deadline for response via COMMBUYS 11/9/2026 at 10:00 AM http://www.commbuys.com/

Requested Information

1. Respondent qualifications and relevant projects

a. Describe your organization’s role and experience in measuring and monitoring forest land conversion and carbon. Identify the services your organization provides directly and those provided by subcontractors, third-party data providers, or others.

b. Describe your experience using forest inventory data, as well as remote sensing and other advanced technologies, for establishing forest land conversion and carbon baselines and/or to monitor changes in forest extent and carbon over time. Include detail on location and geographic extent, acreage or other relevant scale, forest types and conditions represented, technologies and data sources used, landowner type, carbon pools measured or estimated, field inventories or other methods used for calibration or validation, spatial resolution of reported results, frequency of measurement or updating, duration of the program, reported measures of uncertainty, principal deliverables and uses of the resulting data, the utility or relevance of these data compared to other methodologies such as field studies and modeling, and the costs associated with using remote sensing or other advanced technologies compared to other methods of gathering data on forest carbon baselines and change over time.

c. Describe your experience measuring forest carbon in the following contexts:

i. on public lands or at statewide, regional, or other jurisdictional scales

ii. across landscapes containing multiple ownership types

iii. separately by public, Tribal, private, conservation, municipal, or other ownership categories

iv. across landscapes containing different forest-management regimes

d. Describe any experience measuring forest carbon in Massachusetts or in regions with forest composition, climate, land use, or other characteristics similar to Massachusetts.

2. Measurement frameworks for estimating statewide forest conversion and carbon over time

a. Describe a measurement and monitoring framework you would recommend for estimating statewide forest land cover and land use, and for monitoring changes in forest extent over time. Please distinguish methodologies for assessing permanent forest loss, afforestation or reforestation, and regeneration of temporarily disturbed forests, as well as the ability of these approaches to attribute these changes to different causes (e.g. conversion to various other land uses, active v. passive reforestation/afforestation, natural or human stressors or disturbances). What are the known limitations of your proposed methodology, and how might these limitations affect the results?

What are the trade-offs among accuracy, spatial and temporal precision, spatial extent, historical consistency, speed, cost-effectiveness, and other considerations for different approaches?

b. Describe a measurement and monitoring framework you would recommend for establishing a statewide forest carbon baseline and for monitoring changes over time. What are the trade-offs among accuracy, spatial precision, speed, cost-effectiveness, historical consistency, spatial extent, and other factors of your recommended approach and potential alternatives? What are the known limitations of your proposed methodology, and how might these limitations affect the results? Please distinguish methodologies for aboveground biomass, belowground biomass, and soil organic carbon in your response.

c. Describe your experience using remote sensing, artificial intelligence, machine-learning or other similar advanced technologies to map forest extent, conversion, structure, carbon, or other conditions. Please include discussion of how you train and validate the models, as well as tradeoffs and limitations between these advanced approaches and other methods, including costs and data sharing.

3. Ground-based reference data and uncertainty

a. Describe how forest inventory data, permanent plots, activity data, or other ground-based information are used to calibrate, benchmark, or verify forest land conversion and biomass estimates from remote sensing technology, including detail on the geography and scope of any such comparisons and validations.

b. How could a third party verify or validate the measurements produced by methodologies using remote sensing, artificial intelligence, and similar technologies?

c. Given that all approaches to forest land conversion and biomass estimation involve uncertainty and data or methodological limitations, describe the principal sources of uncertainty and any limitations in your recommended measurement technologies, datasets, models, and analytical methods. How would your proposed framework address the limitations and reduce these principal sources of uncertainty?

4. Change detection and long-term consistency

a. Describe methodologies you are aware of for measuring changes in forest carbon stocks and forest extent over time using remote sensing and advanced technologies, including the minimum change that can be distinguished reliably, the spatial scale at which change can be detected, and the ability to attribute changes in forest extent and carbon stocks to changes in land use or management, natural disturbances or stressors, or other causes, and the ability to relate observations and changes to a given baseline (e.g., 1990 conditions).

b. Describe the extent to which these methodologies could be used to compare carbon outcomes associated with different forest-management practices.

What additional actions, such as experimental design and modeling, might be necessary to understand how different forest-management practices are associated with different carbon outcomes?

c. Describe the role that remote sensing and related measurement methods can play in detecting, quantifying, and monitoring losses or reversals associated with harvesting, wildfire, storms, pests, disease, land conversion, or other disturbances.

d. Describe how you maintain comparability among estimates generated over time when technology, sensors, source datasets, or models change. Over what time period could the approaches you are familiar with produce comparable estimates of forest carbon and related indicators?

5. Data ownership, collaboration and interoperability

a. Please describe all ways in which your models or methodologies are dependent on proprietary and/or publicly available data, models, etc. Please explain how data ownership is typically addressed in projects you have been involved with; who owns the data produced by remote sensing?

b. Describe any experience storing forest monitoring and carbon data in shared repositories or other systems designed to improve regional, national, or global forest datasets and models.

c. Describe any experience with measurement methods or technologies that have supported both jurisdiction forest carbon accounting and voluntary or compliance carbon-market applications.

6. Cost estimates and timelines

a. What are the main cost drivers of forest carbon measurement systems?

When answering this question, differentiate among cost drivers for aboveground biomass, belowground biomass, and soil carbon. What are options for reducing these costs, including use of publicly available datasets if feasible and comparable?

b. Provide estimated cost ranges for forest carbon measurement systems at a scale relevant to the Commonwealth. Include cost ranges for elements of a measurement system, including field data collection, LiDAR and remote sensing, and other elements. When answering this question, differentiate among cost ranges for aboveground biomass, belowground biomass, and soil carbon, and differentiate between cost ranges for establishing a baseline compared with ongoing monitoring costs.

c. Provide estimated timelines for designing, commencing, and completing forest carbon baseline calculations.

7. Additional information

a. What questions did we not ask that are important to consider? Please provide additional information that may be relevant to this RFI. This might include case studies, prior project descriptions, academic studies, or third-party resources, for instance.

b. Respondents may be requested to provide additional information or clarification, prepare presentations, or attend a meeting regarding this RFI.