TLS-bridged co-prediction of tree-level multifarious stem structure   variables from worldview-2 panchromatic imagery: a case study of the   boreal forest

doi:10.1080/17538947.2016.1247473

CORC > 北京大学 > 地球与空间科学学院

	TLS-bridged co-prediction of tree-level multifarious stem structure variables from worldview-2 panchromatic imagery: a case study of the boreal forest
	Lin, Yi ; Wei, Tian ; Yang, Bin ; Knyazikhin, Yuri ; Zhang, Yuhu ; Sato, Hisashi ; Fang, Xing ; Liang, Xinlian ; Yan, Lei ; Sun, Shanlin
刊名	INTERNATIONAL JOURNAL OF DIGITAL EARTH
	2017
关键词	Tree stem structure variable (SSV) WorldView-2 panchromatic image (WPI) static terrestrial laser scanning (TLS) allometric relationship co-prediction model TERRESTRIAL LASER SCANNER SPECIES CLASSIFICATION FEATURE PARAMETERS ALLOMETRIC RELATIONSHIPS BIOMASS ESTIMATION INDIVIDUAL TREES PINUS-SYLVESTRIS SATELLITE IMAGES STANDING TREES CROWN HEIGHT
DOI	10.1080/17538947.2016.1247473
英文摘要	In forest ecosystem studies, tree stem structure variables (SSVs) proved to be an essential kind of parameters, and now simultaneously deriving SSVs of as many kinds as possible at large scales is preferred for enhancing the frontier studies on marcoecosystem ecology and global carbon cycle. For this newly emerging task, satellite imagery such as WorldView-2 panchromatic images (WPIs) is used as a potential solution for co-prediction of tree-level multifarious SSVs, with static terrestrial laser scanning (TLS) assumed as a bridge'. The specific operation is to pursue the allometric relationships between TLS-derived SSVs and WPI-derived feature parameters, and regression analyses with one or multiple explanatory variables are applied to deduce the prediction models (termed as Model1s and Model2s). In the case of Picea abies, Pinus sylvestris, Populus tremul and Quercus robur in a boreal forest, tests showed that Model1s and Model2s for different tree species can be derived (e.g. the maximum R-2=0.574 for Q. robur). Overall, this study basically validated the algorithm proposed for co-prediction of multifarious SSVs, and the contribution is equivalent to developing a viable solution for SSV-estimation upscaling, which is useful for large-scale investigations of forest understory, macroecosystem ecology, global vegetation dynamics and global carbon cycle.; National Natural Science Foundation of China [41471281, 31670718]; SRF for ROCS, SEM, China; SCI(E); ARTICLE; 7; 701-718; 10
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/475989]
专题	地球与空间科学学院
推荐引用方式 GB/T 7714	Lin, Yi,Wei, Tian,Yang, Bin,et al. TLS-bridged co-prediction of tree-level multifarious stem structure variables from worldview-2 panchromatic imagery: a case study of the boreal forest[J]. INTERNATIONAL JOURNAL OF DIGITAL EARTH,2017.
APA	Lin, Yi.,Wei, Tian.,Yang, Bin.,Knyazikhin, Yuri.,Zhang, Yuhu.,...&Sun, Shanlin.(2017).TLS-bridged co-prediction of tree-level multifarious stem structure variables from worldview-2 panchromatic imagery: a case study of the boreal forest.INTERNATIONAL JOURNAL OF DIGITAL EARTH.
MLA	Lin, Yi,et al."TLS-bridged co-prediction of tree-level multifarious stem structure variables from worldview-2 panchromatic imagery: a case study of the boreal forest".INTERNATIONAL JOURNAL OF DIGITAL EARTH (2017).