A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems
Citations
163 citations
Cites background or methods from "A survey of remote sensing-based ab..."
...The challenging factors include topography, soil conditions, and forest structures [20]....
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...To overcome this limitation, integrating multi-source data such as optical images and SAR has been proposed to enhance the accuracy of the forest AGB estimation [20,21]....
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..., principal component analysis (PCA) or wavelet transforms) [22]; and (ii) incorporation of all images [20]....
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151 citations
146 citations
Cites background or methods or result from "A survey of remote sensing-based ab..."
...However, one common problem is the data saturation in Landsat imagery; that is, spectral reflectance values are not sensitive to the change in biomass of dense and multilayer canopy forests, which results in low accuracy of AGB estimation, especially when AGB is high, such as greater than 130 Mg/ha [5,6,29]....
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...This is because a good texture image for a given vegetation type depends on different factors such as spatial resolution of the remote sensing data, the complexity of forest stand structure, species composition, and the window size used for extraction of a textural image [6,30,52]....
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...GLCM-based texture measures are the most common approach to producing textural images [6,21,25,26,31,52]....
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...In this research, root mean square error (RMSE) between the estimated and observed values of AGB (see Equation (3)) and relative RMSE (RMSEr) [4,6] (see Equation (4)) were employed to compare the accuracies of the models and their estimates based on the test plots in Table 2 and Table 3, which were based on different scenarios....
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...However, high correlation between vegetation indices or spectral bands makes these variables less important in AGB modeling [6,31]....
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144 citations
Cites background or methods from "A survey of remote sensing-based ab..."
...Biomass estimation using airborne LiDAR can offer higher accuracy in tree extraction [154], tree height estimation [155], and AGB estimation [156] than those from radar and optical data [157], since LiDAR can characterize both horizontal and vertical canopy structures [130]....
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...In addition, LiDAR has limited spectral information, in most cases, having only one wavelength of laser point intensity [130]....
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131 citations
References
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79,257 citations
"A survey of remote sensing-based ab..." refers methods in this paper
...…can be optimized using the principle of Difficult to develop a favorable model when a large (e.g. Marabel and AlvarezTaboada 2013) Random forest, a nonparametric ensemble modeling approach robust to overfitting, constructs numerous small regression trees contributing to predictions (Breiman 2001)....
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...The distance between the target and reference units is calculated as one minus the proportion of terminal nodes from all regression trees where the target observation is in the same terminal node as the specific reference unit (Breiman 2001)....
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13,120 citations
"A survey of remote sensing-based ab..." refers background in this paper
...An overfitting problem exists when the constraints are based on empirical averages of sample data, especially when a very large number of environmental variables are used (Phillips et al. 2006)....
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7,890 citations
"A survey of remote sensing-based ab..." refers background or methods in this paper
...Other GLAS waveform metrics used for biomass estimation include the slope of the leading extent (e.g. Boudreau et al. 2008; Hansen et al. 2013) and various waveform statistics such as maximum, variance, and skewness (e.g. Duncanson et al. 2010)....
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...Deforestation and forest degradation can result in carbon emission to the atmosphere, thus affecting global climate and environmental change (Achard et al. 2004; Hese et al. 2005; Houghton 2005; Frolking et al. 2009; Hansen et al. 2013)....
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...Other GLAS waveform metrics used for biomass estimation include the slope of the leading extent (e.g. Boudreau et al. 2008; Hansen et al. 2013) and various waveform statistics such as maximum, variance, and skewness (e....
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5,314 citations
"A survey of remote sensing-based ab..." refers methods in this paper
...The MaxEnt approach is a general-purpose machine-learning method for predicting or inferring target probability distribution from incomplete information (Phillips and Dudík 2008)....
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4,586 citations
"A survey of remote sensing-based ab..." refers methods in this paper
...Traditionally, the accuracy of forest biomass/carbon estimates is assessed by calculating the root mean square error (RMSE) and the Pearson’s correlation coefficient of the estimated and observed values (Congalton 2001; Congalton and Green 2009; Wang and Gertner 2013)....
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