The Anew Epoch Evaluation Platform™

The technology, data, and evaluation processes driving our nature-based credit generation

Additionality, quantified

Epoch™ combines the latest advancements in high-frequency satellite monitoring, AI, and ground-level data collection to yield previously unachievable levels of accuracy for credit generation and additionality substantiation. Epoch™ evaluated projects exceed all current Registry standards and undergo the most advanced quality control and assurance in the industry.

Dynamic Baselines

Dynamic baselines

Epoch™ evaluations bring a new standard of scrutiny to project baselines, which underpin credit eligibility. Intensive analyses of economic, regulatory, and environmental conditions during every project reporting period determine each project’s ongoing climate benefit.

Monitoring and alerts for carbon loss

Projects are monitored monthly to detect forest loss from fire, storm damage, disease, or unanticipated harvest events. This adds a new layer of security above and beyond our on-the-ground presence to ensure that any unexpected carbon stock losses are immediately reported and accounted for.

Harvest Comparison

Accounting for the realities of forest management

During every reporting period, as frequently as annually, Epoch™ evaluates a series of key criteria related to forest management in and around a project. This determines whether the project’s current baseline, its hypothetical harvest plan, is still accurate. If it is not, the baseline and credit quantity are adjusted to reflect real world conditions.

Anew’s Dynamic Evaluation Criteria

Common Practice Silviculture

Anew utilizes Epoch™ to compare each project property to forest management practices occurring on similar sites within its relevant region for timber extraction, transportation, and processing. This involves a review of literature, interviews with local forestry professionals, and satellite substantiation of recent harvests based on cutting-edge AI technology and high-resolution imagery, capable of identifying harvest activity at the scale of single trees (.5-meter resolution).

Dynamic Baselines_3_Silviculture

Regional Timber Market Capacity

Anew limits baseline harvest scenarios to strictly reflect tree species and size classes for which there is wood product demand within the feasible economic region for timber extraction, transportation, and processing. The relevant region is delineated based on each project’s proximity to facilities such as operational mills, ports, and rail yards.

Dynamic Baselines_4_Mill Capacity

Harvest Operability and Access

Anew limits baseline harvesting scenarios to forest stands that are accessible. While always initially assessed, under the dynamic evaluation approach this review of factors such as road accessibility, infrastructure degradation or improvements, and changes to land ownership is done at every project verification.

Harvest Operability and Access

Dynamic Legal Review

All baselines must be updated to reflect legally permissible harvests and adhere to regional best management practices (BMPs). As one example, the image below depicts a newly expanded waterfront harvest exclusion zone, which would reduce the acres eligible for harvest in the baseline moving forward.

Dynamic Baselines_6_Legality

Ongoing Profitability Analysis

All baseline harvest scenarios must be financially advantageous. Credits are only generated in association with baseline harvests that would be feasible after accounting for factors such as current timber market conditions, stumpage prices, road building expenses, and maintenance and fuel costs for extraction and transportation equipment.

Ongoing Profitability Analysis

Deep dive: Epoch™ analysis of common practice silviculture

Common Practice Silviculture

Anew determines acceptable baseline harvest activities through recurring analysis of “common practice” forest management in the region, established based on the steps outlined below.
Reference region delineation

Reference region delineation

Anew establishes a reference region surrounding the project area based on the feasible hauling distance from the project’s boundary to accessible mills/wood markets.
Map forest types within the region

Map forest types within the region

Anew identifies specific forest types present in the project area and across the reference region using a combination of Anew’s carbon plot data, U.S. Forest Service data, high-resolution satellite imagery, and machine learning models.
Regional harvest analysis 

Regional harvest analysis 

Employing the same technologies utilized to identify forest type in concert with additional remote sensing data, Anew analyzes harvesting activities within the reference region.
Identifying comparable properties

Identifying comparable properties

Ultimately, Anew selects comparable properties within the reference region based on factors such as ownership type (public entity, private corporation, NGO), forest type(s), ecological condition(s), and topography. The harvests identified on these comparable properties provide the basis for what is considered common practice silviculture, and baseline harvests are modeled to conform to these observed practices.

What might change a project’s baseline?

The following example scenarios would lead to an adjustment of the project’s baseline and credits issued in that reporting period.

Collaborators and partners

American Carbon Registry
Treefera

Connect with our team to learn more

Our Sales team is available to guide you through current portfolio availability.