A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China
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 inspectio...
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| Format: | Article |
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Frontiers Media S.A.
2021-02-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2021.609916/full |
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| author | Yaguo Zou Yaguo Zou Yunfa Miao Yunfa Miao Yunfa Miao Shiling Yang Shiling Yang Shiling Yang Yongtao Zhao Zisha Wang Zisha Wang Guoqian Tang Shengli Yang |
| author_facet | Yaguo Zou Yaguo Zou Yunfa Miao Yunfa Miao Yunfa Miao Shiling Yang Shiling Yang Shiling Yang Yongtao Zhao Zisha Wang Zisha Wang Guoqian Tang Shengli Yang |
| author_sort | Yaguo Zou |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T02:42:55Z |
| format | Article |
| id | doaj.art-aaa8213d92004e6981b7343c4fa41fd4 |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-12-20T02:42:55Z |
| publishDate | 2021-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-aaa8213d92004e6981b7343c4fa41fd42022-12-21T19:56:16ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632021-02-01910.3389/feart.2021.609916609916A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest ChinaYaguo Zou0Yaguo Zou1Yunfa Miao2Yunfa Miao3Yunfa Miao4Shiling Yang5Shiling Yang6Shiling Yang7Yongtao Zhao8Zisha Wang9Zisha Wang10Guoqian Tang11Shengli Yang12Key Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaKey Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaCenter for Excellence in Tibetan Plateau Earth Sciences, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, ChinaKey Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, ChinaCAS Center for Excellence in Life and Paleoenvironment, Beijing, ChinaCollege of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, ChinaKey Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaKey Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaKey Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, ChinaKey Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, ChinaMicrocharcoal 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.https://www.frontiersin.org/articles/10.3389/feart.2021.609916/fullmicrocharcoalpaleofireautomatic statisticsvegetationLate Pleistoceneloess |
| spellingShingle | Yaguo Zou Yaguo Zou Yunfa Miao Yunfa Miao Yunfa Miao Shiling Yang Shiling Yang Shiling Yang Yongtao Zhao Zisha Wang Zisha Wang Guoqian Tang Shengli Yang A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China Frontiers in Earth Science microcharcoal paleofire automatic statistics vegetation Late Pleistocene loess |
| title | A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China |
| title_full | A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China |
| title_fullStr | A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China |
| title_full_unstemmed | A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China |
| title_short | A New Automatic Statistical Microcharcoal Analysis Method Based on Image Processing, Demonstrated in the Weiyuan Section, Northwest China |
| title_sort | new automatic statistical microcharcoal analysis method based on image processing demonstrated in the weiyuan section northwest china |
| topic | microcharcoal paleofire automatic statistics vegetation Late Pleistocene loess |
| url | https://www.frontiersin.org/articles/10.3389/feart.2021.609916/full |
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