A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China | |
Chen Tian-tian1,2,3![]() | |
Corresponding Author | Yi Gui-hua(yigh@cdut.edu.cn) |
2019-09-01 | |
Source Publication | JOURNAL OF MOUNTAIN SCIENCE
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ISSN | 1672-6316 |
EISSN | 1993-0321 |
Volume | 16Issue:9Pages:2001-2014 |
Subtype | Article |
Abstract | Accurate measurements of the associated vegetation phenological dynamics are crucial for understanding the relationship between climate change and terrestrial ecosystems. However, at present, most vegetation phenological calculations are based on a single algorithm or method. Because of the spatial, temporal, and ecological complexity of the vegetation growth processes, a single algorithm or method for monitoring all these processes has been indicated to be elusive. Therefore, in this study, from the perspective of plant growth characteristics, we established a method to remotely determine the start of the growth season (SOG) and the end of the growth season (EOG), in which the maximum relative change rate of the normalized difference vegetation index (NDVI) corresponds to the SOG, and the next minimum absolute change rate of the NDVI corresponds to the EOG. Taking the Three-River Headwaters Region in 2000-2013 as an example, we ascertained the spatiotemporal and vertical characteristics of its vegetation phenological changes. Then, in contrast to the actual air temperature data, observed data and other related studies, we found that the SOG and EOG calculated by the proposed method is closer to the time corresponding to the air temperature, and the trends of the SOG and EOG calculated by the proposed method are in good agreement with other relevant studies. Meantime, the error of the SOG between the calculated and observed in this study is smaller than that in other studies. |
Keyword | Vegetation phenology Normalized difference vegetation index (NDVI) Start of the growth season (SOG) End of the growth season (EOG) Three-River Headwaters Region (TRHR) |
DOI | 10.1007/s11629-018-4982-6 |
Indexed By | SCI |
WOS Keyword | NET PRIMARY PRODUCTIVITY ; LAND-SURFACE PHENOLOGY ; GREEN-UP DATE ; SPRING PHENOLOGY ; TIME-SERIES ; GROWING-SEASON ; TIBETAN PLATEAU ; CLIMATE-CHANGE ; SATELLITE DATA ; SPOT-VGT |
Language | 英语 |
Quartile | 3区 |
Funding Project | National Natural Science Foundation of China[41801099] |
TOP | 否 |
WOS Research Area | Environmental Sciences & Ecology |
WOS Subject | Environmental Sciences |
WOS ID | WOS:000485301000002 |
Funding Organization | National Natural Science Foundation of China |
Publisher | SCIENCE PRESS |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.imde.ac.cn/handle/131551/27151 |
Collection | 山区发展研究中心 |
Corresponding Author | Yi Gui-hua |
Affiliation | 1.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Sichuan, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chongqing Normal Univ, Sch Geog & Tourism, Chongqing 401331, Peoples R China 4.Chengdu Univ Technol, Coll Management Sci, Chengdu 610059, Sichuan, Peoples R China 5.Chengdu Univ Technol, Coll Earth Sci, Chengdu 610059, Sichuan, Peoples R China 6.Chongqing Inst Surveying & Planning Land Resource, Chongqing 400020, Peoples R China |
First Author Affilication | 中国科学院水利部成都山地灾害与环境研究所 |
Recommended Citation GB/T 7714 | Chen Tian-tian,Yi Gui-hua,Zhang Ting-bin,et al. A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China[J]. JOURNAL OF MOUNTAIN SCIENCE,2019,16(9):2001-2014. |
APA | Chen Tian-tian,Yi Gui-hua,Zhang Ting-bin,Wang Qiang,&Bie Xiao-juan.(2019).A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China.JOURNAL OF MOUNTAIN SCIENCE,16(9),2001-2014. |
MLA | Chen Tian-tian,et al."A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China".JOURNAL OF MOUNTAIN SCIENCE 16.9(2019):2001-2014. |
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