DOI: 10.1016/j.foreco.2014.06.003
Scopus记录号: 2-s2.0-84903647625
论文题名: Estimating above-ground biomass of tropical rainforest of different degradation levels in Northern Borneo using airborne LiDAR
作者: Ioki K. ; Tsuyuki S. ; Hirata Y. ; Phua M.-H. ; Wong W.V.C. ; Ling Z.-Y. ; Saito H. ; Takao G.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2014
卷: 328 起始页码: 335
结束页码: 341
语种: 英语
英文关键词: Above-ground biomass
; Borneo
; Forest degradation
; LiDAR
; Tropical rainforest
Scopus关键词: Biomass
; Carbon
; Deforestation
; Tropics
; Above ground biomass
; Borneo
; Forest degradation
; REDD
; Tropical rain forest
; Optical radar
; aboveground biomass
; airborne sensing
; carbon budget
; deforestation
; environmental degradation
; environmental disturbance
; human activity
; lidar
; rainforest
; tropical forest
; Biomass
; Carbon
; Deforestation
; Forestry
; Radar
; Tropical Atmospheres
; Borneo
英文摘要: Deforestation and degradation of forests have severely depleted carbon storage in tropical countries, whose forests have the most carbon-rich ecosystems in the world. Estimating above-ground biomass (AGB) with high accuracy is critical to quantifying carbon stocks in the tropics. We propose a model to estimate AGB in the tropical montane forests of northern Borneo with different disturbance histories using airborne LiDAR data. The level of forest degradation was determined from species composition and field-observed AGB. Of 50 sample plots established in forests with various levels of degradation, we categorized 20 as highly degraded (AGB: 52.18-229.11Mg/ha), 16 as moderately degraded (AGB: 136.00-382.59Mg/ha), and 14 as old-growth forest (AGB: 280.31-622.79Mg/ha). Height metrics and laser penetration rate (LP) at specific heights from the ground were derived from vertical point profiles of LiDAR data. After testing the performance of single variables, we used stepwise multiple regressions to select variables to include in the model for AGB estimation. The best model with a single variable used the mean height from the laser returns (R2=0.78, RMSE=65.54Mg/ha). All LP variables were sensitive to AGB (R2>0.60). The final model from stepwise analysis included the mean height of the canopy height model and LP at 7m height (adjusted R2=0.81, RMSE=61.26Mg/ha). The results confirm the suitability of LP variables for estimating AGB. We suggest that airborne LiDAR data can capture AGB variability at fine spatial scales, which correspond to deforestation and forest degradation caused by human activities and natural disturbances. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/65858
Appears in Collections: 影响、适应和脆弱性
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作者单位: Graduate School of Agricultural and Life Sciences, University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8567, Japan; Forest and Forest Products Research Institute, Matsunosato 1, Tsukuba, Ibaraki 305-8687, Japan; School of International Tropical Forestry, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
Recommended Citation:
Ioki K.,Tsuyuki S.,Hirata Y.,et al. Estimating above-ground biomass of tropical rainforest of different degradation levels in Northern Borneo using airborne LiDAR[J]. Forest Ecology and Management,2014-01-01,328