ForestERA Data Layer Detail - Stand Height (in meters)

Note to data users: Please carefully review the metadata provided with each layer. We request that users consult with the ForestERA project in advance of using these data in publications and/or presentations to ensure that the strengths and limitations of the data are considered.

Description

Crown base height (hereafter CBH) is the distance between the ground and the lowest live branches in the crown of a tree. A mean or other percentile of individual tree CBHs is usually used to define CBH for all trees in a given area. Stand height (hereafter SH) is the average top canopy height in a group of trees. These layers are provided in units of meters and has a resolution of 90m (0.8 ha or 2 acres).

Purpose

These data layers were created as part of the ForestERA project to support landscape-scale forest restoration planning efforts by a broad group of stakeholders including federal and state agencies, academic institutions, and non-governmental entities. These data are intended for regional analyses over spatial extents on the order of tens to hundreds of thousands of acres, and were not developed for use at finer spatial scales, although they may be useful for some applications at finer scales.

Development

These layers were created using the quadratic mean diameter (QMD) layer developed by the ForestERA team. Attributes of the tree canopy cannot be directly measured using readily available and inexpensive types of remote-sensing imagery. Because of this, it was necessary to use allometric equations to develop these layers. Mean values for CBH and tree height for individual trees are strongly correlated to the mean diameter at breast height (DBH) of those trees. Since DBH and QMD are related measures (QMD = DBH when all trees in the QMD analysis are of equal DBH), we were able to use our QMD layer and linear regression equations to estimate CBH and SH across the region.

A field crew hired by the ForestERA project measured the DBH, CBH, and canopy height on several thousand trees across the region. We used the data from these measurements to create the regression equations. First, a mean CBH and mean tree height was determined for all trees of the same size (equal DBH) and vegetation type (ponderosa pine, aspen, mixed conifer, and pinyon - juniper). For the mixed conifer vegetation type, all Douglas’ fir, spruces, firs, and white pines were considered together, and for the pinyon - juniper vegetation type all pinyon pines and junipers were considered together. This was deemed valid since most tree species in each of these vegetation types have similar structure.

Once mean values for CBH and tree height were determined for every DBH value of a given tree species, we then regressed the mean CBH and mean tree heights at each DBH vs. the entire range of DBH values for that tree species. If significant relationships (P < 0.05) were determined to exist we used the regression equations to predict mean tree height and mean CBH for that tree species. Otherwise, we used the mean tree height and CBH for that species. The following table contains the results of these analyses. In the equations, values for QMD should be in centimeters, while values for CBH and SH should be in meters. To eliminate the possibility of values outside the range of possibility, maximum SH was set at 30m and maximum mean CBH was set at 10m.

Tree Species Attribute Regression Equation r² Value
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ponderosa pine SH 0 + (0.614 * QMD) 0.923
<= 20cm DBH CBH 0 + (0.277 * QMD) 0.817

ponderosa pine SH 5.56 + (0.336 * QMD) 0.799
> 20cm DBH CBH 3.82 + (0.277 * QMD) 0.397

mixed conifer SH 0 + (0.596 * QMD) 0.922
CBH 0 + (0.167 * QMD) 0.744

pinyon - juniper SH 0 + (0.386 * QMD) 0.651
CBH none (mean = 0.550) ---

aspen SH 0 + (0.699 * QMD) 0.833
CBH 0 + (0.384 * QMD) 0.656
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These equations provide mean values for CBH and SH. We felt the values for SH were reasonably representative of top canopy height. However, the values for mean CBH will seriously overestimate the effective CBH of a stand for purposes of fire modeling. This is because the fire can transition to the crown through trees with much lower CBHs than average. In order to account for this a low percentile of CBH (often a quartile; e.g., Fule et al., 2000) is often used rather than mean CBH. To obtain such a measure from our data we first determined the standard deviation of CBH for each tree species and DBH class. We then divided the standard deviation of CBH by the mean CBH for each DBH class. This value (hereafter CBH/1SD) represents the mean percent of CBH that is covered by one standard deviation of CBH. A height that is 1 standard deviation below CBH is equal to CBH * (1 - (CBH/1SD)). For example CBH/1SD = 0.6 then a height 1 standard deviation below mean CBH is equal to CBH * 0.4) We then used the lowest quartile of CBH/1SD across all DBH classes to identify likely minimum values of CBH for any particular DBH class. These lowest quartiles of CBH are listed in the following table.

Tree Species Lowest Quartile of CBH
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ponderosa pine 0.195 * Mean CBH

mixed conifer 0.256 * Mean CBH

pinyon - juniper 0.231

aspen 0.341 * Mean CBH
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Accuracy Assessment

No accuracy assessment is possible for these layers as we do not have comprehensive measurements of tree heights or crown base heights across this region. The use of this methodology resulted in reasonable values for mean SH, mean CBH, and minimum CBH. However, we note that there are accuracy issues with the QMD layer (see the metadata for that layer), and that all of these attributes may vary widely across the region depending on actual tree size class distributions, management history, and other factors.

Sources of errors

These layers are among the most uncertain layers in fire behavior modeling. There is no way to accurately predict CBH or SH without extensive measurements on the ground or very expensive and hard to obtain remote sensing imagery. We advise using these layers with caution. We believe they are suitable for modeling to assess relative fire behavior across the landscape even though the fire models cannot represent absolute predictions of fire behavior.

Recommendations

We do not believe these layers are highly accurate, and we recommend using them with caution. We recommend that this layer be used at a minimum resolution of 90m (0.8 ha or 2 acres) for purposes of analysis and display. However, ForestERA data layers were not designed for analyses at the level of individual pixels, and uncertainty in the data will generally decline over greater spatial extents. Therefore, we recommend using larger analysis units, with groupings of at least 50 cells (40 ha or 100 acres). Finally, we reiterate that ForestERA data layers were developed for the purpose of regional landscape-level planning, and we suggest that the analyses be applied over spatial extents of tens to hundreds of thousands of acres. We recognize, however, that this layer may be useful for analyses over smaller spatial extents depending on the type and purpose of those analyses.

References

Fule, P. Z., C. McHugh, T. A. Heinlein, and W. W. Covington. 2002. Potential fire behavior is reduced following forest restoration treatments. Pp 28 -35 in Ponderosa pine ecosystems restoration and conservation: steps toward stewardship (R. K. Vance, C. B. Edminster, W. W. Covington, and J. A. Blake, eds.). USDA Forest Service Conference Proceedings RMRS-P-22.

Page last updated February 23, 2005