干旱区生态环境知识资源中心(Arid): An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images

Arid

DOI	10.1016/j.ecolind.2021.107494
	An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images
	Mao, Peng; Qin, Longjun; Hao, Mengyu; Zhao, Wenli; Luo, Jiechunyi; Qiu, Xu; Xu, Lijie; Xiong, Yujiu; Ran, Yili; Yan, Chunhua; Qiu, Guo Yu
通讯作者	Qin, LJ ; Qiu, GY (corresponding author), Peking Univ, Sch Environm & Energy, Shenzhen Grad Sch, Shenzhen 518055, Peoples R China.
来源期刊	ECOLOGICAL INDICATORS
ISSN	1470-160X
EISSN	1872-7034
出版年	2021
卷号	125
英文摘要	Above-ground biomass (AGB) is an essential indicator for assessing ecosystem health and carbon storage in desert shrub-related research. Above-ground volume (AGV) of vegetation is a crucial parameter to estimate the AGB. In unmanned aerial vehicle (UAV) remote sensing, the AGV and AGB are mainly estimated by vegetation feature metrics (for example, spectral indices, textural, and structural metrics). However, there is limited study on the AGV and AGB estimation in desert shrub communities by using UAV, and it is difficult to determine the contribution of these metrics to AGV models under eliminating the influence of background factors. Taking a typical desert shrub area in Inner Mongolia, China as an example, this study develops an improved approach to extracted three types of feature metrics simultaneously using UAV RGB (Red, Green, Blue) images. First, digital orthophoto map (DOM) and digital surface model (DSM) were created through the photogrammetric procedure based on UAV RGB images. Second, the digital terrain model (DTM) for canopy height calculation was generated based on DOM and DSM by object-oriented image binary classification and ground elevation interpolation. Here, we recommended the ENVI Landsat Gap-fill tool to interpolate the ground elevation of vegetation areas. Meanwhile, 21 spectral indices, eight textural metrics, and five structural metrics were extracted. Finally, singlevariable and multi-variable commonly used regression models were established based on these metrics and measured AGV with a leave-one-out cross-validation. Results showed that: (1) in the proposed model, the contribution of structural, textural, and spectral metric to shrub AGV models was 86.68, 7.08, and 6.24%, respectively. (2) The horizontal and vertical structural metrics, textural metrics, or spectral indices reflected the one-dimensional change of AGV, which had a saturation effect. (3) The canopy volume, combining the horizontal and vertical characteristics of vegetation canopy, could describe the overall change of AGV and played the most essential role in AGV modelling (R2 = 0.928, relative RMSE = 26.8%). The study findings provide a direct reference in determining suitable vegetation feature metrics for monitoring shrub AGV. The proposed approach for DTM generation and AGV estimation is more efficient, accurate and low-cost than before, and it can be a useful bridge between ground-based investigation and satellite remote sensing.
英文关键词	Above-ground biomass (AGB) Above-ground volume (AGV) Unmanned aerial vehicle (UAV) Spectral indices Textural metrics Structural metrics Desert shrub
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000636844900010
WOS类目	Biodiversity Conservation ; Environmental Sciences
WOS研究方向	Biodiversity & Conservation ; Environmental Sciences & Ecology
来源机构	北京大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/350002
作者单位	[Mao, Peng; Qin, Longjun; Hao, Mengyu; Zhao, Wenli; Luo, Jiechunyi; Yan, Chunhua; Qiu, Guo Yu] Peking Univ, Sch Environm & Energy, Shenzhen Grad Sch, Shenzhen 518055, Peoples R China; [Qiu, Xu] Univ Virginia, Coll Arts & Sci, Charlottesville, VA 22903 USA; [Xu, Lijie] Inner Mongolia Agr Univ, Coll Desert Control Sci & Engn, Hohhot 010018, Peoples R China; [Xiong, Yujiu] Sun Yat Sen Univ, Sch Civil Engn, Guangzhou 510275, Peoples R China; [Ran, Yili] Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Peoples R China; [Zhao, Wenli] Columbia Univ, Earth Inst, Dept Earth & Environm Engn, New York, NY 10027 USA
推荐引用方式 GB/T 7714	Mao, Peng,Qin, Longjun,Hao, Mengyu,et al. An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images[J]. 北京大学,2021,125.
APA	Mao, Peng.,Qin, Longjun.,Hao, Mengyu.,Zhao, Wenli.,Luo, Jiechunyi.,...&Qiu, Guo Yu.(2021).An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images.ECOLOGICAL INDICATORS,125.
MLA	Mao, Peng,et al."An improved approach to estimate above-ground volume and biomass of desert shrub communities based on UAV RGB images".ECOLOGICAL INDICATORS 125(2021).