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Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories
Shang, Rong1,2; Liu, Ronggao1; Xu, Mingzhu3; Liu, Yang1; Dash, Jadunandun4; Ge, Quansheng1
2018
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume10Issue:1Pages:16
Corresponding AuthorLiu, Ronggao(liurg@igsnrr.ac.cn)
AbstractIn the Indian monsoon region, frequent cloud cover in the rainy season results in less valid satellite observations during the vegetation growth period, making it difficult to extract land surface phenology (LSP). Even worse, many valid but humid observations were misidentified as clouds in the MODIS cloud mask, causing severe gaps in the LSP product. Using a refined cloud detection approach to separate clear-sky and cloudy observations, this study found that potentially valid observations during the vegetation growth period could be identified. Furthermore, the varied vegetation growth trajectories cannot be well-fitted by a global curve-fitting approach, but can be modelled by using the locally adjusted cubic-spline capping approach, which performed well for any seasonal patterns. Applying this approach, the start of growing season (SOS) was determined with 9.18% of vegetation growth amplitude between the maximum and minimum NDVI to generate the SOS product (2000-2016). The valid percentage of this regional product largely increased from 29.30% to 69.76% compared with the MCD12Q2 product, and its reliability was approximate to that of deciduous broadleaf forest in North America and Europe. This product could serve as a basis for understanding the response of terrestrial ecosystems to the changing Indian monsoon.
Keywordland surface phenology vegetation growth trajectory start of growing season Indian monsoon climate change MODIS
DOI10.3390/rs10010122
WOS KeywordLAND-SURFACE PHENOLOGY ; TIME-SERIES DATA ; EXTREME WET ; DRY SPELLS ; RAINFALL ; PRODUCTS ; DYNAMICS ; PATTERNS ; FORESTS ; CLIMATE
Indexed BySCI
Language英语
Funding ProjectChinese Academy of Sciences[XDA19080303] ; Key Research and Development Programs for Global Change and Adaptation[2016YFA0600201] ; Distinctive Institutes Development Program, CAS[TSYJS04] ; National Natural Science Foundation from China[41171285]
Funding OrganizationChinese Academy of Sciences ; Key Research and Development Programs for Global Change and Adaptation ; Distinctive Institutes Development Program, CAS ; National Natural Science Foundation from China
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000424092300120
PublisherMDPI AG
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/56938
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLiu, Ronggao
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210023, Jiangsu, Peoples R China
4.Univ Southampton, Geog & Environm, Southampton SO17 1BJ, Hants, England
Recommended Citation
GB/T 7714
Shang, Rong,Liu, Ronggao,Xu, Mingzhu,et al. Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories[J]. REMOTE SENSING,2018,10(1):16.
APA Shang, Rong,Liu, Ronggao,Xu, Mingzhu,Liu, Yang,Dash, Jadunandun,&Ge, Quansheng.(2018).Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories.REMOTE SENSING,10(1),16.
MLA Shang, Rong,et al."Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories".REMOTE SENSING 10.1(2018):16.
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