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Climate Change and...
COLE is a program that draws from US Forest Service FIA (Forest Inventory and Analysis) Data and allows users to generate estimates for forest carbon inventory and carbon growth-and-yield curves within a user-defined region of the continental United States or Alaska. Regions can be defined from the county-scale on up. Users can select from 19 pre-defined filters (forest type, ownership, stand size, physiographic class, etc.) and sort by several quantitative or qualitative variables to receive aggregate or pool-specific carbon stock and growth-and-yield estimates. COLE is similar to, but more customizable than, NE-GTR-343.
Detailed carbon stock report, with data that is specific to the user-defined regions, filters, and variables.
Interactive, online tool
Continental United States, Alaska
County to national
Informational data for a variety of applications including Forest Management Plans and NEPA analyses
Uncertainty of the estimates decreases over larger areas: Detailed, small-scale reports are subject to inaccuracies due to the small sample size of the underlying FIA data (see more detailed info, below)
COLE (Carbon OnLine Estimator)
Overview & Applicability
COLE is a versatile and appropriate tool to use for a wide range of carbon estimation needs. COLE draws from Forest Inventory and Analysis (FIA) data to provide basic carbon inventory and growth-and-yield estimates for a particular forest, region, or state. While COLE draws from FIA plot data, the data is aggregated at the county or national forest level, so analysis can occur at this level or higher. However, if the user is interested in learning about the baseline carbon inventory or carbon growth-and-yield on a smaller plot of land (county level or smaller) COLE can be a great launching off point for learning some basic information about carbon stored in at the county level, and help the user determine whether to conduct a more comprehensive, site-specific, field-based inventory for a particular parcel of interest.
COLE allows the user to create a growth and yield prediction of carbon pools according to forest type, ownership class, and a variety of other variables Estimates may also be produced corresponding to the format for the inventory of US greenhouse gas emissions and sinks, and can be useful for the carbon criterion in the Montreal Process criteria and indicators for sustainability. However, the tool is not necessarily sufficient for an individual to use as a means of establishing a baseline or current carbon inventory for the purpose of enrolling a project in carbon markets or registries – this can usually only be done through a field-based inventory, conducted by a forestry professional.
COLE was originally developed to aid in voluntary reporting of greenhouse gases as described in section 1605(b) of the Energy Policy Act of 1992. COLE, and NE-GTR-343 are based on similar data and conversion factors.
Inputs and outputs
Users may select one or more particular counties, states, or regions, or some combination of these, from an interactive map. The latest version of COLE also allows users to pick a point on a Google map and define an inclusion radius to examine a more customized geography. Behind the scenes, COLE is drawing from FIA data to create customized reports and maps of carbon inventories according to user-selected, pre-defined filters. The output is an instantly generated report, in pdf format, based upon these user-defined inputs (see below).
Restrictions and limitations
COLE draws from FIA data. The FIA program is considered the “nation’s forest census,” and reports on the status, trends, and health of forests through annual on-the-ground sampling. So, the accuracy of a COLE-generated carbon report is related to the sample size of the underlying data. This is the reason why COLE works from a county-scale on up. The more filters that a user applies, the more important it becomes to choose a larger (multiple counties, states, etc.) area over which to apply these filters. While COLE will not prevent you from generating a very specific report (e.g. an aboveground carbon stock report for overstocked, privately owned, white oak/red oak/hickory stands in Elk County, PA), the user should be aware that such a detailed report on a small scale is subject to sample-size inaccuracies.