Literature DB >> 24639008

Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010.

Xiaoyang Zhang1, Bin Tan, Yunyue Yu.   

Abstract

Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3 decades. OGI mainly showed late trends in the Southern Hemisphere of Africa while GSL was reversed from reduced GSL trends (1982-1999) to prolonged trends (2000-2010). In Australia, GSL exhibited considerable interannual variation, but the consistent trend lacked presence in most regions. Finally, the proportion of pixels with significant trends was less than 1 % in most of climate regions although it could be as large as 10 %.

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Year:  2014        PMID: 24639008     DOI: 10.1007/s00484-014-0802-z

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  3 in total

1.  Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999.

Authors:  C J Tucker; D A Slayback; J E Pinzon; S O Los; R B Myneni; M G Taylor
Journal:  Int J Biometeorol       Date:  2001-11       Impact factor: 3.787

2.  Drought-induced reduction in global terrestrial net primary production from 2000 through 2009.

Authors:  Maosheng Zhao; Steven W Running
Journal:  Science       Date:  2010-08-20       Impact factor: 47.728

3.  Near-surface remote sensing of spatial and temporal variation in canopy phenology.

Authors:  Andrew D Richardson; Bobby H Braswell; David Y Hollinger; Julian P Jenkins; Scott V Ollinger
Journal:  Ecol Appl       Date:  2009-09       Impact factor: 4.657

  3 in total
  8 in total

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Journal:  ISPRS J Photogramm Remote Sens       Date:  2016-03-03       Impact factor: 8.979

2.  Greater phenological sensitivity on the higher Tibetan Plateau: new insights from weekly 5 km EVI2 datasets.

Authors:  Bingwen Qiu; Jiangping Zhong; Zhenghong Tang; Min Feng; Chongcheng Chen; Xiaoqin Wang
Journal:  Int J Biometeorol       Date:  2016-10-26       Impact factor: 3.787

3.  Interannual variations in spring phenology and their response to climate change across the Tibetan Plateau from 1982 to 2013.

Authors:  Lingling Liu; Xiaoyang Zhang; Alison Donnelly; Xinjie Liu
Journal:  Int J Biometeorol       Date:  2016-03-02       Impact factor: 3.787

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Journal:  Proc Natl Acad Sci U S A       Date:  2017-12-26       Impact factor: 11.205

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Journal:  PLoS One       Date:  2019-08-21       Impact factor: 3.240

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Authors:  Giovanni Forzieri; Vasilis Dakos; Nate G McDowell; Alkama Ramdane; Alessandro Cescatti
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7.  Monitoring cotton root rot by synthetic Sentinel-2 NDVI time series using improved spatial and temporal data fusion.

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Journal:  Sci Rep       Date:  2018-01-31       Impact factor: 4.379

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Journal:  PeerJ       Date:  2018-08-31       Impact factor: 2.984

  8 in total

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