干旱区生态环境知识资源中心(Arid): A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China

Arid

DOI	10.3389/feart.2021.609916
	A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China
	Zou, Yaguo; Miao, Yunfa; Yang, Shiling; Zhao, Yongtao; Wang, Zisha; Tang, Guoqian; Yang, Shengli
通讯作者	Miao, YF (corresponding author), Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Desert & Desertificat, Lanzhou, Peoples R China. ; Miao, YF (corresponding author), Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China. ; Miao, YF (corresponding author), Chinese Acad Sci, Inst Tibetan Plateau Res, Ctr Excellence Tibetan Plateau Earth Sci, Beijing, Peoples R China.
来源期刊	FRONTIERS IN EARTH SCIENCE
EISSN	2296-6463
出版年	2021
卷号	9
英文摘要	Microcharcoal is a proxy of biomass burning and widely used in paleoenvironment research to reconstruct the fire history, which is influenced by the climate and land cover changes of the past. At present, microcharcoal characteristics (amount, size, shape) are commonly quantified by visual inspection, which is a precise but time-consuming approach. A few computer-assisted methods have been developed, but with an insufficient degree of automation. This paper proposes a new methodology for microcharcoal statistical analysis based on digital image processing by ImageJ software, which improves statistical efficiency by 80-90%, and validation by manual statistical comparison. The method is then applied to reconstruct the fire-related environmental change in the Weiyuan loess section since about 40 thousand years before present (ka BP), northwest China with a semi-arid climate, found that the microcharcoal concentration is low in cold and dry climate and high in warm and humid climate. The two main contributions of this study are: 1) proposal of a new, reliable and high efficient automatic statistical method for microcharcoal analysis; and 2) using the new method in a semi-arid section, revealing the paleofire evolution patterns in the semi-arid region was mainly driven by the biomass rather than the aridity degree found in humid regions.
英文关键词	microcharcoal paleofire automatic statistics vegetation Late Pleistocene loess
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:000626463800001
WOS类目	Geosciences, Multidisciplinary
WOS研究方向	Geology
来源机构	兰州大学 ; 中国科学院青藏高原研究所 ; 中国科学院地质与地球物理研究所
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/350273
作者单位	[Zou, Yaguo; Miao, Yunfa; Zhao, Yongtao; Wang, Zisha] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Desert & Desertificat, Lanzhou, Peoples R China; [Zou, Yaguo; Miao, Yunfa; Wang, Zisha] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China; [Miao, Yunfa] Chinese Acad Sci, Inst Tibetan Plateau Res, Ctr Excellence Tibetan Plateau Earth Sci, Beijing, Peoples R China; [Yang, Shiling] Chinese Acad Sci, Inst Geol & Geophys, Key Lab Cenozo Geol & Environm, Beijing, Peoples R China; [Yang, Shiling] CAS Ctr Excellence Life & Paleoenvironm, Beijing, Peoples R China; [Yang, Shiling] Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing, Peoples R China; [Tang, Guoqian; Yang, Shengli] Lanzhou Univ, Coll Earth & Environm Sci, Minist Educ, Key Lab Western Chinas Environm Syst, Lanzhou, Peoples R China
推荐引用方式 GB/T 7714	Zou, Yaguo,Miao, Yunfa,Yang, Shiling,et al. A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China[J]. 兰州大学, 中国科学院青藏高原研究所, 中国科学院地质与地球物理研究所,2021,9.
APA	Zou, Yaguo.,Miao, Yunfa.,Yang, Shiling.,Zhao, Yongtao.,Wang, Zisha.,...&Yang, Shengli.(2021).A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China.FRONTIERS IN EARTH SCIENCE,9.
MLA	Zou, Yaguo,et al."A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China".FRONTIERS IN EARTH SCIENCE 9(2021).