DOI: 10.1016/j.jag.2014.01.010
Scopus记录号: 2-s2.0-84897516269
论文题名: Detecting pruning of individual stems using airborne laser scanning data captured from an Unmanned Aerial Vehicle
作者: Wallace L ; , Watson C ; , Lucieer A
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 30, 期: 1 起始页码: 76
结束页码: 85
语种: 英语
英文关键词: Change detection
; Forest management
; Laser scanning
; Pruning
; Unmanned Aerial Vehicle
Scopus关键词: aerial photography
; best management practice
; evergreen tree
; forest management
; pruning
; stem
; unmanned vehicle
英文摘要: Modern forest management involves implementing optimal pruning regimes. These regimes aim to achieve the highest quality timber in the shortest possible rotation period. Although a valuable addition to forest management activities, tracking the application of these treatments in the field to ensure best practice management is not economically viable. This paper describes the use of Airborne Laser Scanner (ALS) data to track the rate of pruning in a Eucalyptus globulus stand. Data is obtained from an Unmanned Aerial Vehicle (UAV) and we describe automated processing routines that provide a cost-effective alternative to field sampling. We manually prune a 500 m2 plot to 2.5 m above the ground at rates of between 160 and 660 stems/ha. Utilising the high density ALS data, we first derived crown base height (CBH) with an RMSE of 0.60 m at each stage of pruning. Variability in the measurement of CBH resulted in both false positive (mean rate of 11%) and false negative detection (3.5%), however, detected rates of pruning of between 96% and 125% of the actual rate of pruning were achieved. The successful automated detection of pruning within this study highlights the suitability of UAV laser scanning as a cost-effective tool for monitoring forest management activities. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79716
Appears in Collections: 气候变化事实与影响
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作者单位: School of Land and Food, University of Tasmania, Private Bag 76, Hobart, TAS 7001, Australia
Recommended Citation:
Wallace L,, Watson C,, Lucieer A. Detecting pruning of individual stems using airborne laser scanning data captured from an Unmanned Aerial Vehicle[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,30(1)