气候变化领域集成服务门户(CCPortal): A simple approach to forest structure classification using airborne laser scanning that can be adopted across bioregions

CCPortal

DOI	10.1016/j.foreco.2018.10.057
	A simple approach to forest structure classification using airborne laser scanning that can be adopted across bioregions
	Adnan S.; Maltamo M.; Coomes D.A.; García-Abril A.; Malhi Y.; Manzanera J.A.; Butt N.; Morecroft M.; Valbuena R.
发表日期	2019
ISSN	0378-1127
起始页码	111
结束页码	121
卷号	433
英文摘要	Reliable assessment of forest structural types (FSTs) aids sustainable forest management. We developed a methodology for the identification of FSTs using airborne laser scanning (ALS), and demonstrate its generality by applying it to forests from Boreal, Mediterranean and Atlantic biogeographical regions. First, hierarchal clustering analysis (HCA) was applied and clusters (FSTs) were determined in coniferous and deciduous forests using four forest structural variables obtained from forest inventory data – quadratic mean diameter (QMD), Gini coefficient (GC), basal area larger than mean (BALM) and density of stems (N) –. Then, classification and regression tree analysis (CART) were used to extract the empirical threshold values for discriminating those clusters. Based on the classification trees, GC and BALM were the most important variables in the identification of FSTs. Lower, medium and high values of GC and BALM characterize single storey FSTs, multi-layered FSTs and exponentially decreasing size distributions (reversed J), respectively. Within each of these main FST groups, we also identified young/mature and sparse/dense subtypes using QMD and N. Then we used similar structural predictors derived from ALS – maximum height (Max), L-coefficient of variation (Lcv), L-skewness (Lskew), and percentage of penetration (cover), – and a nearest neighbour method to predict the FSTs. We obtained a greater overall accuracy in deciduous forest (0.87) as compared to the coniferous forest (0.72). Our methodology proves the usefulness of ALS data for structural heterogeneity assessment of forests across biogeographical regions. Our simple two-tier approach to FST classification paves the way toward transnational assessments of forest structure across bioregions. © 2018 Elsevier B.V.
英文关键词	Classification and regression trees; Forest structural types; LiDAR; Nearest neighbour imputation; Structural heterogeneity
语种	英语
scopus关键词	Ecology; Laser applications; Optical radar; Statistical methods; Airborne Laser scanning; Classification and regression tree; Classification and regression tree analysis; Coefficient of variation; Nearest neighbour; Structural heterogeneity; Structural type; Sustainable forest management; Forestry; basal area; biogeographical region; boreal forest; coniferous forest; deciduous forest; ecoregion; forest inventory; forest management; heterogeneity; laser method; lidar; methodology; regression analysis; sustainable forestry; Classification; Coefficient Of Variation; Data; Ecology; Forestry; Forests; Statistical Methods; Sustainable Forest Management; Mediterranean Region
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156299
作者单位	University of Eastern Finland, Faculty of Forest Sciences, PO Box 111, Joensuu, FI-80101, Finland; University of Cambridge, Department of Plant Sciences, Forest Ecology and Conservation, Downing Street, Cambridge, CB2 3EA, United Kingdom; National University of Sciences and Technology, Institute of Geographical Information Systems, Islamabad, 44000, Pakistan; Universidad Politecnica de Madrid, College of Forestry and Natural Environment, Research Group SILVANET, Ciudad Universitaria, Madrid, 28040, Spain; University of Oxford, School of Geography and the Environment, Environmental Change Institute, Oxford, OX1 3QY, United Kingdom; The University of Queensland, School of Biological Sciences, St. Lucia, Queensland 4072, Australia; Natural England, Cromwell House, 15 Andover Road, Winchester, SO23 7BT, United Kingdom
推荐引用方式 GB/T 7714	Adnan S.,Maltamo M.,Coomes D.A.,et al. A simple approach to forest structure classification using airborne laser scanning that can be adopted across bioregions[J],2019,433.
APA	Adnan S..,Maltamo M..,Coomes D.A..,García-Abril A..,Malhi Y..,...&Valbuena R..(2019).A simple approach to forest structure classification using airborne laser scanning that can be adopted across bioregions.Forest Ecology and Management,433.
MLA	Adnan S.,et al."A simple approach to forest structure classification using airborne laser scanning that can be adopted across bioregions".Forest Ecology and Management 433(2019).