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      Modelling the Above-Ground Biomass (AGB) of Eucalyptus Plantations using WorldView-2 Imagery in Sabah, Malaysia

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      Environment-Behaviour Proceedings Journal
      e-IPH Ltd.

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          Abstract

          Forest plantations are established not only to provide supply of demands, but also to help mitigate climate change. Satellite remote sensing can be used to estimate above ground biomass (AGB). This study was conducted in Eucalyptus plantations in Sabah, Malaysia. Satellite images from WorldView-2 were acquired as primary data. Allometric functions were used to calculate the AGB. The individual bands and vegetation indices were used as predictor variables. From the analysis, the ‘best’ predictive model for AGB was . The predictive model recorded an I2=0.71, RMSE=0.44 tha-1 and p=0.001. The predicted AGB ranged from 4 to 225 tha-1.

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          Measuring inconsistency in meta-analyses.

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            Quantifying heterogeneity in a meta-analysis.

            The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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              An analysis of variance test for normality (complete samples)

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                Author and article information

                Journal
                Environment-Behaviour Proceedings Journal
                E-BPJ
                e-IPH Ltd.
                2398-4287
                January 07 2024
                January 07 2024
                : 9
                : SI17
                : 485-492
                Article
                10.21834/e-bpj.v9iSI17.5455
                68dff810-975e-4e42-a8c4-bbdb90007017
                © 2024

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/

                History

                Psychology,Urban design & Planning,Urban studies,General behavioral science,Cultural studies

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