Forest stand biomass estimation using ALOS PALSAR data based on LiDAR-derived prior knowledge in the Qilian Mountain, western China-文献浏览-时空三极环境大数据平台

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He Q-S, Cao C-X, Chen E-X, Sun G-Q, Ling F-L, Pang Y, Zhang H, Ni W-J, Xu M, Li Z-Y, Li X-W. Forest stand biomass estimation using ALOS PALSAR data based on LiDAR-derived prior knowledge in the Qilian Mountain, western China. International Journal of Remote Sensing, 2012, 33(3): 710-729, doi:10.1080/01431161.2011.577829.

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Type Of Reference	JOUR
Title	Forest stand biomass estimation using ALOS PALSAR data based on LiDAR-derived prior knowledge in the Qilian Mountain, western China
Authors	He, Qisheng\| Cao, Chunxiang\| Chen, Erxue\| Sun, Guoqing\| Ling, Feilong\| Pang, Yong\| Zhang, Hao\| Ni, Wenjian\| Xu, Min\| Li, Zengyuan\| Li, Xiaowen\|
Secondary Title	International Journal of Remote Sensing
Abstract	Studies are needed to evaluate the ability of Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) for forest aboveground biomass (AGB) extraction in mountainous areas. In this article, forest biomass was estimated at plot and stand levels, and different biomass grades, respectively. Light detection and ranging (LiDAR) data with about one hit per m2 were first used for forest biomass estimation at the plot level, with R 2 of 0.77. Then the LiDAR-derived biomass, as prior knowledge, was used to investigate the relationship between ALOS PALSAR data and biomass. The results showed that at each biomass level, the range of the back-scatter coefficient in HH and HV polarization (where H and V represent horizontal and vertical polarizations, respectively, and the first of the two letters refers to the transmission polarization and the second to the received polarization) was very large and there was no obvious relationship between the synthetic aperture radar (SAR) back-scatter coefficient and biomass at plot level. At stand level and in different biomass grades, the back-scatter coefficient increased with the increase of forest biomass, and a logarithm equation can be used to describe the relationship. The main reason may be that forest structure is complex at the plot level, while the average value could partly decrease the influence of forest structure at stand level. Meanwhile, terrain radiometric correction (TRC) was investigated and found effective for forest biomass estimation.
Date	2012///
Year	2012
DOI	10.1080/01431161.2011.577829
Database Provider	Taylor and Francis+NEJM
volume	33
Issue Number	3
Start Page	710
Issn	0143-1161
Url	http://www.tandfonline.com/doi/abs/10.1080/01431161.2011.577829
Access Date	2013/10/04/06:22:35
file_attachments2	http://www.tandfonline.com/doi/abs/10.1080/01431161.2011.577829#.Uk5eqHjn5eQ
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Forest stand biomass estimation using ALOS PALSAR data based on LiDAR-derived prior knowledge in the Qilian Mountain, western China

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