A Guide to Using Regression Equations for Estimating Tree Biomass

Crow, Thomas R.; Schlaegel, Bryce E.

doi:10.1093/njaf/5.1.15

Cited by 57 publications

(16 citation statements)

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“…The underestimation is consistent with the previous studies of biomass equations that generalized 26 urban-based species-specific allometric equations [49]. Part of the underestimation was probably caused by the inherent bias in applying logarithmic transformations when developing these equations [95,96,98,100]. It was found that logarithmic transformations could cause a slight downward bias when equations are converted back to compute biomass in measured units.…”

Section: Discussionsupporting

confidence: 88%

“…5) are the transformed coefficients from the corresponding regression equations. Four different criteria were computed to cross-validate the performance of Equations (9)-(13) [95,98]: The linear regression through the origin, the paired sample t-test, the root mean square error (RMSE), and the mean relative difference (MRD). The independent data points reserved for validation were first tested for normality with the Shapiro-Wilk test [97].…”

Section: Regression Analysis and Statistical Evaluationmentioning

confidence: 99%

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Developing General Equations for Urban Tree Biomass Estimation with High-Resolution Satellite Imagery

2019

Sustainability

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Urban trees provide various important ecological services, the quantification of which is vital to sustainable urban development and requires accurate estimation of tree biomass. A limited number of allometric biomass equations, however, have been developed for urban species due to the prohibitive cost. Remote sensing has provided cost-effective means for estimating urban forest biomass, although the propagation of error in the estimation process is not well understood. This study aimed to offer a baseline assessment of the feasibility of estimating urban tree biomass with remote sensing-based general equations applicable to broad taxonomic groups by conducting a large urban tree inventory on a university campus. The biomasses of 191 trees of seven species from the inventory, separated into two categories (i.e., evergreen and deciduous), were calculated exclusively with urban-based species-specific allometric equations. WorldView-2 satellite imagery data were acquired to retrieve normalized difference vegetation index (NDVI) values at the location, crown, and stand levels. The results indicated that biomass correlated with NDVI in varying forms and degrees. The general equations at the crown level yielded the most accurate biomass estimates, while the location-level estimates were the least accurate. Crown-level spectral responses provided adequate information for delivering spatially explicit biomass estimation. could be substantial [50][51][52], ranging from −97% to 205% depending on the individual species and the sizes of the trees [43]. Biomass estimates could even vary from 27% less to 29% more when applying the allometric equation developed for an individual urban species in California to the same species in Colorado because of considerable differences in site conditions [43].Considering the time and monetary cost of developing site-and species-specific allometric equations, it has been suggested to use general equations that are applicable to all species in a broad taxonomic grouping instead [43,53,54]. Such equations have been developed for 35 natural forest-grown genera on a national scale [39,40]. However, studies focused on developing allometric equations for general urban tree groups are scant [49], because urban-based equations over the entire range of site conditions are not available for compilation and synthesis [55].Another approach to overcome the prohibitive cost associated with the development of allometric equations is to utilize remote sensing and geospatial techniques [49,[56][57][58][59][60]. Remote sensing obtains information about the Earth's environment from a distance without the need for extensive field surveys over large areas. It has been used in several different ways as a non-destructive and cost-effective method for biomass estimation with varying degrees of success.Generated with Light Detection and Ranging (LiDAR) technology, point cloud data have been regularly used to measure urban tree biomass directly [58,[60][61][62] or extract basic silvicultural variables such as tree he...

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Section: Discussionsupporting

confidence: 88%

Section: Regression Analysis and Statistical Evaluationmentioning

confidence: 99%

Developing General Equations for Urban Tree Biomass Estimation with High-Resolution Satellite Imagery

2019

Sustainability

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“…For species with several equations available (e.g. Acer saccharum ), preference was given to equations developed in ecologically similar sites (Crow & Schlaegel, 1988), rather than to those from geographically proximate sites. Allometric equations for ‘general hardwoods’≥ 10 cm d.b.h.…”

Section: Methodsmentioning

confidence: 99%

An initial intercomparison of micrometeorological and ecological inventory estimates of carbon exchange in a mid‐latitude deciduous forest

Ehman

Schmid

Grimmond

et al. 2002

Global Change Biology

109

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The role of mid‐latitude forests in the sequestration of carbon (C) is of interest to an increasing number of scientists and policy‐makers alike. Net CO2 exchange can be estimated on an annual basis, using eddy‐covariance techniques or from ecological inventories of C fluxes to and from a forest. Here we present an intercomparison of annual estimates of C exchange in a mixed hardwood forest in the Morgan‐Monroe State Forest, Indiana, USA for two years, 1998 and 1999. Based on eddy‐covariance measurements made at 1.8 times canopy height from a tower, C uptake by the forest was 237 and 287 g C m−2 y−1 for 1998 and 1999, respectively. For the same time period, biometric and ecophysiological measures and modelled estimates of all significant carbon fluxes within deciduous forests were made, including: change in living biomass, aboveground and belowground detritus production, foliage consumption, and forest floor and soil respiration. Using this ecological inventory method for these same two time periods, C uptake was estimated to be 271 and 377 g C m−2 y−1, which are 14.3% and 31.4% larger, respectively, than the tower‐based values. The relative change between this method's annual estimates is consistent with that of the eddy‐covariance based values. Our results indicate that the difference in annual C exchange rates was due to reduced heterotrophic soil respiration in 1999.

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“…where Wis weight per tree of above-ground biomass, D is stem diameter at 1 37 m, and a and b are empirically determined constants (Whittaker & Marks 1975;Parde 1980), although many other equations have been used (Parde 1980;Crow 1988 Hence, E may be viewed as the product of two components: the first related to the size of the plant and the relative allocation of biomass to leaves versus wood (a b c-' Db-I -d) and the second related to instantaneous diameter growth rate (dD/dt). The two components are not uniquely related, in that many combinations are possible depending on stand history and competitive regime.…”

Section: Theory E Versus Lai As An Index To Competitionmentioning

confidence: 99%

Modelling Growth and Optimal Rotations of Tropical Multipurpose Trees Using Unit Leaf Rate and Leaf Area Index

Fownes¹,

Harrington²

1990

The Journal of Applied Ecology

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JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. SUMMARY(1) A simple model of tree growth in even-aged stands calculated growth rate as the product of unit leaf rate (E) and leaf area per tree. Theoretical analysis showed that decreasing E with increasing leaf area index (LAI) depends on both allometry and current growth rate, which depend on planting density, growth history, and competition.(2) A case study using Eucalyptus saligna grown in Hawaii found that the growth trajectories of four different planting densities can be represented by a single curve of E versus LAI.(3) Using maximum mean annual increment (MAI) as the criterion for optimal rotation length, the model predicts increasing peak MAI from 16-4 to 21-5 t ha-I year-' for initial planting densities, varying from 500 to 2000 trees ha-l. Over this range of initial densities, rotation age decreases from 9-0 to 4-7 years; at rotation age for these initial densities, trunk diameter decreases from 28 to 14 cm, total biomass decreases from 148 to 102 t ha-', and LAI decreases from 4 0 to 2-9.(4) Such synthesis and generalization from empirical growth trials will permit improved decision-making in the context of desired rotation characteristics. Extrapolation to other sites and species will require understanding of how key parameters vary, in particular those of the allometric equations and those describing the E-LAI relationship.

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A Guide to Using Regression Equations for Estimating Tree Biomass

Cited by 57 publications

References 0 publications

Developing General Equations for Urban Tree Biomass Estimation with High-Resolution Satellite Imagery

Developing General Equations for Urban Tree Biomass Estimation with High-Resolution Satellite Imagery

An initial intercomparison of micrometeorological and ecological inventory estimates of carbon exchange in a mid‐latitude deciduous forest

Modelling Growth and Optimal Rotations of Tropical Multipurpose Trees Using Unit Leaf Rate and Leaf Area Index

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