Aboveground stand-level biomass estimation: a comparison of two methods for major forest species in northwest Spain

Castedo‐Dorado, Fernando; Gómez-García, Esteban; Diéguez-Aranda, Ulises; Barrio-Anta, Marcos; Crecente-Campo, Felipe

doi:10.1007/s13595-012-0191-6

Cited by 69 publications

(68 citation statements)

References 21 publications

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“…There is a growing need of accurate and effective methods for estimating forest biomass/carbon stocks to meet the requirements of both Kyoto Protocol and UN-REDD programmes (Castedo et al, 2012). The REDD+ Measurement, Reporting and Verification (MRV) requires accurate and precise estimates, a large number of reference plots must be established, which inevitably increases the time and effort and expense of the method.…”

Section: Introductionmentioning

confidence: 99%

Derivation of Forest Inventory Parameters for Carbon Estimation Using Terrestrial Lidar

Kalwar

Hussin

Weir

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This research was conducted to derive forest sample plot inventory parameters from terrestrial LiDAR (T-LiDAR) for estimating above ground biomass (AGB)/carbon stocks in primary tropical rain forest. Inventory parameters of all sampled trees within circular plots of 500 m 2 were collected from field observations while T-LiDAR data were acquired through multiple scanning using Reigl VZ-400 scanner. Pre-processing and registration of multiple scans were done in RSCAN PRO software. Point cloud constructing individual sampled tree was extracted and tree inventory parameters (diameter at breast height-DBH and tree height) were measured manually. AGB/carbon stocks were estimated using Chave et al., (2005)

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Section: Introductionmentioning

confidence: 99%

Derivation of Forest Inventory Parameters for Carbon Estimation Using Terrestrial Lidar

Kalwar

Hussin

Weir

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Moreover, compatible biomass modelling systems have been proposed and applied to ensure compatibility between total biomass models and component biomass models. Researchers have developed two principal ways of creating compatible biomass models: (1) the total biomass regression function is defined as the sum of separately calculated best regression functions of component biomasses; (2) joint-generalized least squares regression, like seemingly unrelated regressions (SUR), two-stage least-squares methods (2SLS) , three-stage least-squares methods (3SLS) and generalized method of moments (GMM) (António et al, 2007;Balboa-Murias et al, 2006;Bi et al, 2010;Brandeis et al, 2006;Castedo-Dorado et al, 2012;Gómez-García et al, 2013;Gómez-García et al, 2014;Hasenauer et al, 1998;Carvalho and Parresol, 2003;Li and Zhao, 2013;Menéndez-Miguélez et al, 2013;Parresol, 1999Parresol, , 2001Ruiz-Peinado et al, 2011;Shaiek et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

A single-tree additive biomass model of Quercus variabilis Blume forests in North China

Zheng

Mason

Jia

et al. 2015

Trees

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Key message Fitting and comparing three sets of compatible biomass models for prediction of biomass or carbon stocks of natural and planted Quercus variabilis Blume forests.Abstract To make the sum of estimated values from biomass models of various components of a tree equal to estimated tree total biomass for Quercus variabilis Blume (cork oak) forests in North China, single-tree compatible biomass models were developed. 100 trees from 100 plots in North China were felled to obtain biomass of aboveground components, and roots of 19 of those trees were extracted for measurement of root biomass. After Box-Cox transformations of variables, two sets of independent component biomass models with a dummy variable in models to define stand origin were separately built using linear mixed effects analyses (one set of models with site as a random factor; the other set without any random factor). Then three methods were compared to force compatibility of the biomass models: sums of linear mixed effects models, sums of linear models, and simultaneous equation fits based on linear models. Model parameters were estimated by ordinary least squares (OLS) or seeming unrelated regression procedures (SUR). Coefficients of determination (r 2 ), root mean square error (Rmse), residuals plots and histograms of residuals indicated that models fitted with sums of linear mixed effects models were the least biased and most precise at estimating total above-ground biomass.Further testing for the linear mixed effects models with jackknife validation and prediction sum of squares (PRESS) statistics indicated that the compatible biomass models can be used to predict biomass or carbon stocks of cork oak forests in North China within specific tree diameter at breast height and height ranges.

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“…La elección del método de estimación de biomasa depende, entre otros factores, de la información que aporte el inventario que se toma como base para realizar los cálculos. El uso de ecuaciones de estimación de biomasa proporcionan estimaciones más precisas que el uso de factores de expansión de biomasa, ya que el primer método se basa en ecuaciones obtenidas a partir de muestreos regionales representativos; además, evita la fuente de error adicional introducida al emplear factores de expansión (Schoene 2002, Jalkanen et al 2005, Gil et al 2011, Castedo-Dorado et al 2012.…”

Section: Introductionunclassified

Evolución de la biomasa y del carbono acumulado por Quercus robur en Galicia (España)

Gómez-García¹,

Rodríguez²

2015

Bosque (Valdivia)

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Evolución de la biomasa y del carbono acumulado por Quercus robur en Galicia (España)Changes in biomass and carbon storage in Quercus robur trees in Galicia (Spain) Esteban Gómez-García*, Fernando Pérez-Rodríguez Key words: pedunculate oak, carbon sequestration, national forest inventory (NFI). RESUMENEn este trabajo se ha estudiado la evolución de la biomasa y del carbono acumulado en los árboles de Quercus robur presentes en Galicia (noroeste de España). Se desarrollaron ecuaciones de estimación de biomasa para árbol individual, las cuales utilizan como variable independiente el diámetro normal. Se realizó un ajuste simultáneo para garantizar la aditividad, y se empleó la metodología GMM (generalized method of moments) debido a la presencia de heterocedasticidad. Para estimar la evolución de la biomasa de Q. robur en Galicia, las ecuaciones desarrolladas se aplicaron a los datos del número de árboles por clase diamétrica de los cuatro inventarios forestales nacionales (IFN) realizados hasta el momento. La concentración media de carbono en los diferentes componentes arbóreos considerados permitió estimar el carbono acumulado a partir de la biomasa. Aunque en Galicia ha disminuido la superficie de bosques puros de Q. robur, la evolución del número de árboles ha sido positiva en el periodo considerado

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Aboveground stand-level biomass estimation: a comparison of two methods for major forest species in northwest Spain

Abstract: International audienc

Cited by 69 publications

References 21 publications

Derivation of Forest Inventory Parameters for Carbon Estimation Using Terrestrial Lidar

Derivation of Forest Inventory Parameters for Carbon Estimation Using Terrestrial Lidar

A single-tree additive biomass model of Quercus variabilis Blume forests in North China

Evolución de la biomasa y del carbono acumulado por Quercus robur en Galicia (España)

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