DOI: 10.1016/j.foreco.2017.05.013
Scopus记录号: 2-s2.0-85019488165
论文题名: Applicability of different non-invasive methods for tree mass estimation: A review
作者: Dittmann S. ; Thiessen E. ; Hartung E.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2017
卷: 398 起始页码: 208
结束页码: 215
语种: 英语
英文关键词: Allometric equations
; Biomass
; Estimation
; Forest
; Lidar
; Mass
; Optical Images
; Radar
; Review
; SfM
; Tree
Scopus关键词: Biomass
; Estimation
; Forestry
; Geometrical optics
; Noninvasive medical procedures
; Radar
; Remote sensing
; Reviews
; Allometric equations
; Forest
; Mass
; Optical image
; Tree
; Optical radar
; accuracy assessment
; allometry
; biomass
; efficiency measurement
; estimation method
; forest
; Internet
; lidar
; literature review
; nondestructive testing
; optical method
; radar
; remote sensing
; spatial analysis
; technology
; tree
英文摘要: Biomass estimations of trees are used at various different special scales. Along with the scale, there are diverse demands on accuracy and technical requirements. This paper reports the state of the art of different methods for non-invasive tree mass estimation technics. Different studies about biomass estimations at different spatial scales were compared on basis of three assessment criteria: accuracy, efficiency, and technical requirements. Publications were searched via Google Scholar, Web of Science and ScienceDirect including years from 1980 to 2016. References of 20 studies could be used to compare 10 methods of biomass estimation. Allometric approaches are comparably accurate but are suitable for small area applications only. Remote sensing techniques are less accurate but more efficient. Lidar and SfM appear to be the most efficient and most accurate techniques for medium sized area applications. Especially SfM applications are promising due to lower technical requirements. Optical images are suitable for coarse but large area applications. © 2017 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/64299
Appears in Collections: 影响、适应和脆弱性
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作者单位: Institute of Agricultural Engineering, University of Kiel, Max-Eyth-Str. 6, Kiel, Germany
Recommended Citation:
Dittmann S.,Thiessen E.,Hartung E.. Applicability of different non-invasive methods for tree mass estimation: A review[J]. Forest Ecology and Management,2017-01-01,398