DOI: 10.1016/j.jag.2017.06.004
Scopus记录号: 2-s2.0-85032218072
论文题名: LiDAR-based TWI and terrain attributes in improving parametric predictor for tree growth in southeast Finland
作者: Mohamedou C ; , Tokola T ; , Eerikäinen K
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2017
卷: 62 起始页码: 183
结束页码: 191
语种: 英语
英文关键词: Forest
; LiDAR
; Terrain attributes
; Trees’ growth
; TWI
Scopus关键词: forest dynamics
; growth
; lidar
; moisture content
; soil moisture
; terrain
; tree
; vegetation cover
; Finland
英文摘要: The effect of soil moisture content on vegetation and therefore on growth is well known. Information about the growth of forest stands is key in forest planning and management, and is the concern of various stakeholders. One way to assess moisture content and its impacts on forest growth is to apply the Topographic Wetness Index (TWI) and the derived terrain attributes from the Digital Terrain Model (DTM). The TWI is an important terrain attribute, used in various ecological studies. In the current study, a total of 9987 tally trees within 197 sample plots in southeastern Finland and LiDAR (Light Detection and Ranging) −based TWI were selected to examine: 1) the effect of cell resolutions and focal statistics of neighborhood cells of DTM, on tree diameter increment, and 2) possibilities to improve the prediction accuracy of an existing single-tree growth model using the terrain attributes and TWI with the combined effects of three characteristics (i.e., cell resolutions, neighborhood cells and terrain attributes). The results suggest that the TWI with terrain attributes improved the growth estimation significantly, and within different site types the Root Mean Square Errors (RMSE) were lowered substantially. The best results were obtained for birch trees. The higher resolution of the DTM and the lower focal neighborhood cells were found to be the best alternative in computing the TWI. © 2017 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79988
Appears in Collections: 气候变化事实与影响
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作者单位: School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101, Joensuu, Finland; Forestland Investment Finland Ltd., Kauppakatu 23 a, Joensuu, Finland
Recommended Citation:
Mohamedou C,, Tokola T,, Eerikäinen K. LiDAR-based TWI and terrain attributes in improving parametric predictor for tree growth in southeast Finland[J]. International Journal of Applied Earth Observation and Geoinformation,2017-01-01,62