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National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China
2015
Remote Sensing
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The forest AGB prediction models were separately developed for different forest types in each of the seven forest zones at GLAS footprint level from GLAS waveform parameters and biomass derived from height ...
Some waveform parameters used in the prediction models were able to reduce the effects of slope on biomass estimation. ...
Contributions All authors contributed their work in this study. ...
doi:10.3390/rs70505534
fatcat:hxk5neh7yfb6tmheffyovdc6wi
Comparison and Evaluation of Three Methods for Estimating Forest above Ground Biomass Using TM and GLAS Data
2017
Remote Sensing
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Three modeling methods (stepwise regression (SR), support vector regression (SVR) and random forest (RF)) were used to estimate forest AGB over the Daxing'anling Mountains in northeastern China. ...
In the case of the RF AGB models, including GLAS data no longer led to significant improvement. ...
The authors would also like to express gratitude to Sun Guoqing, who provided field measurements for this research, and Zhang Yuzhen, who provide much help and instruction in data processing. ...
doi:10.3390/rs9040341
fatcat:2wwevywahnenxej7u5iqkhb47i
Requirements of a habitat specialist in Swiss mountain forests – an assessment of forest structure and composition using laser remote sensing and field data
2012
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The methods applied in this study can also be used to identify hotspots of forest structural richness, a matter of interest in the light of emerging attempts to conserve biodiversity in forests. ...
To study the habitat requirements of hazel grouse (Bonasa bonasia), an indicator species of structurally rich forest stands, we assessed the structure and composition of Swiss mountain forests over three ...
The authors of the global forest height products are thanked for the efforts in producing these important products and for sharing the results in a free and accessible fashion. ...
doi:10.5167/uzh-77306
fatcat:gtpnt3jpdfcjpcdlxw6sxjei44