气候变化领域集成服务门户(CCPortal): Estimation of Above-Ground Forest Biomass in Nepal by the Use of Airborne LiDAR, and Forest Inventory Data

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DOI	10.3390/land13020213
	Estimation of Above-Ground Forest Biomass in Nepal by the Use of Airborne LiDAR, and Forest Inventory Data
	Bahadur, K. C. Yam; Liu, Qijing; Saud, Pradip; Gaire, Damodar; Adhikari, Hari
发表日期	2024
EISSN	2073-445X
起始页码	13
结束页码	2
卷号	13 期号:2
英文摘要	Forests play a significant role in sequestering carbon and regulating the global carbon and energy cycles. Accurately estimating forest biomass is crucial for understanding carbon stock and sequestration, forest degradation, and climate change mitigation. This study was conducted to estimate above-ground biomass (AGB) and compare the accuracy of the AGB estimating models using LiDAR (light detection and ranging) data and forest inventory data in the central Terai region of Nepal. Airborne LiDAR data were collected in 2021 and made available by Nepal Ban Nigam Limited, Government of Nepal. Thirty-two metrics derived from the laser-scanned LiDAR point cloud data were used as predictor variables (independent variables), while the AGB calculated from field data at the plot level served as the response variable (dependent variable). The predictor variables in this study were LiDAR-based height and canopy metrics. Two statistical methods, the stepwise linear regression (LR) and the random forest (RF) models, were used to estimate forest AGB. The output was an accurate map of AGB for each model. The RF method demonstrated better precision compared to the stepwise LR model, as the R2 metric increased from 0.65 to 0.85, while the RMSE values decreased correspondingly from 105.88 to 60.9 ton/ha. The estimated AGB density varies from 0 to 446 ton/ha among the sample plots. This study revealed that the height-based LiDAR metrics, such as height percentile or maximum height, can accurately and precisely predict AGB quantities in tropical forests. Consequently, we confidently assert that substantial potential exists to monitor AGB levels in forests effectively by employing airborne LiDAR technology in combination with field inventory data.
英文关键词	above-ground biomass; airborne laser scanning; forest inventory; random forest
语种	英语
WOS研究方向	Environmental Sciences & Ecology
WOS类目	Environmental Studies
WOS记录号	WOS:001171041000001
来源期刊	LAND
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/301193
作者单位	Beijing Forestry University; Tribhuvan University; Institute of Forestry (IOF) - Nepal; University of Arkansas System; University Arkansas Monticello; University of Helsinki
推荐引用方式 GB/T 7714	Bahadur, K. C. Yam,Liu, Qijing,Saud, Pradip,et al. Estimation of Above-Ground Forest Biomass in Nepal by the Use of Airborne LiDAR, and Forest Inventory Data[J],2024,13(2).
APA	Bahadur, K. C. Yam,Liu, Qijing,Saud, Pradip,Gaire, Damodar,&Adhikari, Hari.(2024).Estimation of Above-Ground Forest Biomass in Nepal by the Use of Airborne LiDAR, and Forest Inventory Data.LAND,13(2).
MLA	Bahadur, K. C. Yam,et al."Estimation of Above-Ground Forest Biomass in Nepal by the Use of Airborne LiDAR, and Forest Inventory Data".LAND 13.2(2024).