兰州大学机构库 >资源环境学院
Detecting patterns of vegetation gradual changes (2001-2017) in Shiyang River Basin, based on a Novel Framework
Wang, Ju1,2; Jie, YW(颉耀文)1,2; Wang, XY(王晓云)1,2; Dong, Jingru1,2; Bie, Qiang1,2
2019
Source PublicationRemote Sensing   Impact Factor & Quartile Of Published Year  The Latest Impact Factor & Quartile
ISSN20724292
EISSN2072-4292
Volume11Issue:21
page numbers24
AbstractA lot of timeseries satellite products have been well documented in exploring changes in ecosystems. However, algorithms allowing for measuring the directions, magnitudes, and timing of vegetation change, evaluating the major driving factors, and eventually predicting the future trends are still insufficient. A novel framework focusing on addressing this problem was proposed in this study according to the temporal trajectory of Normalized Difference Vegetation Index (NDVI) timeseries of Moderate Resolution Imaging Spectroradiometer (MODIS). It divided the inter-annual changes in vegetation into four patterns: linear, exponential, logarithmic, and logistic. All the three non-linear patterns were differentiated automatically by fitting a logistic function with prolonged NDVI timeseries. Finally, features of vegetation changes including where, when and how, were evaluated by the parameters in the logistic function. Our results showed that 87.39% of vegetation covered areas (maximum mean growing season NDVI in the 17 years not less than 0.2) in the Shiyng River basin experienced significant changes during 2001-2017. The linear pattern, exponential pattern, logarithmic pattern, and logistic pattern accounted for 36.53%, 20.16%, 15.42%, and 15.27%, respectively. Increasing trends were dominant in all the patterns. The spatial distribution in both the patterns and the transition years at which vegetation gains/losses began or ended is of high consistency. The main years of transition for the exponential increasing pattern, the logarithmic increasing pattern, and the logarithmic increasing pattern were 2008-2011, 2003-2004, and 2009-2010, respectively. The period of 2006-2008 was the foremost period that NDVIs started to decline in Liangzhou Oasis and Minqin Oasis where almost all the decreasing patterns were concentrated. Potential disturbances of vegetation gradual changes in the basin are refer to as urbanization, expansion or reduction of agricultural oases, as well as measures in ecological projects, such as greenhouses building, afforestation, grazing prohibition, etc.
© 2019 by the authors.
Keywordvegetation gradual changes pattern temporal trajectory logistic model Shiyang river basin
PublisherMDPI
DOI10.3390/rs11212475
Indexed BySCIE ; EI
Language英语
Funding ProjectChinese Academy of Sciences[XDA2009000001] ; National Key Research and Development Program of China Stem Cell and Translational Research[2018YFA0606404-03] ; Fundamental Research Funds for the Central Universities[]
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000504716700016
PublisherMDPI AG, Postfach, Basel, CH-4005, Switzerland
EI Accession Number20194607667097
EI KeywordsEcology ; Radiometers ; Reforestation ; Rivers ; Watersheds
EI Classification NumberSurface Water:444.1 ; Ecology and Ecosystems:454.3 ; Radiation Measuring Instruments:944.7
Original Document TypeJournal article (JA)
Citation statistics
Document Type期刊论文
Identifierhttps://ir.lzu.edu.cn/handle/262010/418307
Collection资源环境学院
Corresponding AuthorXie, Yaowen
Affiliation
1.College of Earth and Environment Sciences, Lanzhou University, Lanzhou; 730000, China
2.The Key Laboratory ofWestern China's Environmental Systems, Ministry of Education (MOE), Lanzhou; 730000, China
First Author AffilicationCollege of Earth Environmental Sciences
Corresponding Author AffilicationCollege of Earth Environmental Sciences
First Signature AffilicationCollege of Earth Environmental Sciences
Recommended Citation
GB/T 7714
Wang, Ju,Xie, Yaowen,Wang, Xiaoyun,et al. Detecting patterns of vegetation gradual changes (2001-2017) in Shiyang River Basin, based on a Novel Framework[J]. Remote Sensing,2019,11(21).
APA Wang, Ju,Xie, Yaowen,Wang, Xiaoyun,Dong, Jingru,&Bie, Qiang.(2019).Detecting patterns of vegetation gradual changes (2001-2017) in Shiyang River Basin, based on a Novel Framework.Remote Sensing,11(21).
MLA Wang, Ju,et al."Detecting patterns of vegetation gradual changes (2001-2017) in Shiyang River Basin, based on a Novel Framework".Remote Sensing 11.21(2019).
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