Estimating above-ground biomass of trees: comparing Bayesian calibration with regression technique
نویسندگان
چکیده
منابع مشابه
Determine the most suitable Allometric equations for Estimating Above-ground Biomass of the Juniperus excelsa
Today, modeling and determination of allometric equations of forest trees, especially Junipers trees, are very important for determination of biological status and carbon storage capacity of forest species. The aim of this study was to determine the most suitable allometric equations for estimating the biomass of leaf, sub branch, main branch, trunk, and biomass of total Juniperus excelsa tr...
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Accurate measurement and mapping of biomass is a critical component of carbon stock quantification, climate change impact assessment, suitability and location of bio-energy processing plants, assessing fuel for forest fires, and assessing merchandisable timber. While above-ground biomass includes both live and dead plant material, most of the recent research effort on biomass estimation has foc...
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Assessing forest stand conditions in urban and peri-urban areas is essential to support ecosystem service planning and management, as most of the ecosystem services provided are a consequence of forest stand characteristics. However, collecting data for assessing forest stand conditions is time consuming and labor intensive. A plausible approach for addressing this issue is to establish a relat...
متن کاملModel for Estimating Above Ground Biomass of Reclamation Forest using Unmanned Aerial Vehicles
Among various stand parameters, the density of biomass volume is oftenly used as an indicator on evaluating the forest growth succes. The forest reclamation, which is intended to restore the land cover by revegetation process, the evaluation of biomass content has been a critical issue. Forest reclamation is expected to restore the land function to a proper state that might give better environm...
متن کاملBayesian Additive Regression Trees
We develop a Bayesian “sum-of-trees” model where each tree is constrained by a regularization prior to be a weak learner, and fitting and inference are accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples from a posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis elements. Motivated by en...
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ژورنال
عنوان ژورنال: European Journal of Forest Research
سال: 2014
ISSN: 1612-4669,1612-4677
DOI: 10.1007/s10342-014-0793-7