Tree allometric equations for estimation of above, below and total biomass in a tropical moist forest: Case study with application to remote sensing
Autor: | Cedric Djomo Chimi, Adrien N. Djomo |
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Rok vydání: | 2017 |
Předmět: |
0106 biological sciences
Estimation Biomass (ecology) 010504 meteorology & atmospheric sciences Crown (botany) Tree allometry Estimator Forestry Management Monitoring Policy and Law 010603 evolutionary biology 01 natural sciences Tree (graph theory) Remote sensing (archaeology) Tropical and subtropical moist broadleaf forests 0105 earth and related environmental sciences Nature and Landscape Conservation Remote sensing |
Zdroj: | Forest Ecology and Management. 391:184-193 |
ISSN: | 0378-1127 |
DOI: | 10.1016/j.foreco.2017.02.022 |
Popis: | The unavailability of site-specific allometric equations to estimate forest biomass has promoted the use of general equations in tropical moist forests which may result to errors in the estimates. The aim of this study was to develop site-specific allometric equations to estimate biomass of trees in tropical moist forests of Cameroon. For this study, 237 trees (1 ≤ D ≤ 121 cm) obtained by destructive method were used to develop allometric equations for the estimation of aboveground biomass. Allometric equations to estimate belowground and total biomasses were developed with 25 trees and 13 trees respectively. Trunk and crown biomass estimators were also developed in this study using 96 sample trees. Predictor variables considered were diameter, tree height, wood density and crown diameter. 237 and 235 trees were also used to develop regressions equations to estimate tree height and crown diameter respectively. For remote sensing applications, this study developed allometric equations to estimate aboveground biomass using crown diameter as predictor variable. Comparison of our biomass data to existing models showed that the equation of Djomo et al. (2016) provided the best estimator of total and mean biomass. Our study contributes to site-specific allometric equations and to the knowledge of belowground, above, trunk, crown and total biomass, which lack in most of the biomass data in tropical moist forests. Also, adding allometric equations with application to remote sensing, this study is a significant input for the implementation of REDD+ in Central Africa. |
Databáze: | OpenAIRE |
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