Extracting grassland vegetation phenology in North China based on cumulative SPOT-VEGETATION NDVI data

Plant phenology is one of the main indicators of climate or other environmental processes. This paper assesses the detection accuracy of start of season (SOS) and end of season (EOS) for grassland vegetation in north China from 2001 to 2010 using SPOT-VEGETATION normalized difference vegetation index (NDVI) data sets and in situ observations. The cumulative NDVI is calculated and fitted using a logistic model to identify phenological transition dates. The curvature of the fitted logistic models predicts phenological transition dates that correspond to the times at which the curvature in the yearly integrated NDVI exhibits local minimums or maximums. Validating with in situ observations, phenological dates are extracted from satellite time series data and are accurate to within 10 days. The spatial trends of SOS and EOS are very similar for 2001–2010. SOS mainly occurs from the day of year (DOY) 110 to DOY 170, and EOS occurs from DOY 240 to DOY 300. SOS displays a marked delay from south to north, while EOS gradually advances, indicating regional differences in climate and terrain. However, the effect of latitude and longitude on the average EOS of alpine grasslands is not significantly different, while SOS at low latitude and high longitude is 10 days earlier than at high-latitude and high-longitude regions. We detected an overall advance in SOS of 3.1 days over 10 years, and a 1.3-day delay in EOS. However, the amplitude is low (about 5 days) and the changes in most regions are not significant (close to zero). The results in this paper are concordant with many reported studies that explored the phenology of grasslands in North China, which is an important component of global grasslands science.

[1]  Mark D. Schwartz,et al.  Surface phenology and satellite sensor-derived onset of greenness: an initial comparison , 1999 .

[2]  P. Ciais,et al.  Variations in satellite‐derived phenology in China's temperate vegetation , 2006 .

[3]  Mingjun Ding,et al.  Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009 , 2013 .

[4]  Eike Luedeling,et al.  Winter and spring warming result in delayed spring phenology on the Tibetan Plateau , 2010, Proceedings of the National Academy of Sciences.

[5]  Per Jönsson,et al.  Seasonality extraction by function fitting to time-series of satellite sensor data , 2002, IEEE Trans. Geosci. Remote. Sens..

[6]  B. Fu,et al.  Land use change and anthropogenic driving forces: A case study in Yanhe River Basin , 2011 .

[7]  A. Strahler,et al.  Monitoring vegetation phenology using MODIS , 2003 .

[8]  Fang Jingyun,et al.  Seasonal Changes in Vegetation Activity in Response to Climate Changes in Ch ina between1982and1999 , 2003 .

[9]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[10]  Jin Chen,et al.  A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter , 2004 .

[11]  Yanhong Tang,et al.  Altitude and temperature dependence of change in the spring vegetation green-up date from 1982 to 2006 in the Qinghai-Xizang Plateau , 2011 .

[12]  Annette Menzel,et al.  Phenology: Its Importance to the Global Change Community , 2002 .

[13]  Yu Rong.  Spatial and Temporal Variations of the Vegetation Growing Season in Warm-temperate Eastern China during 1982 to 1999 , 2007 .

[14]  C. Tucker,et al.  Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999 , 2001 .

[15]  P. Sprent,et al.  Nonlinear Regression Modeling-A Unified Practical Approach. , 1985 .

[16]  Guirui Yu,et al.  Chinese ecosystem research network: Progress and perspectives , 2010 .

[17]  Shixiong Cao,et al.  Excessive reliance on afforestation in China's arid and semi-arid regions: Lessons in ecological restoration , 2011 .

[18]  José A. Sobrino,et al.  Global land surface phenology trends from GIMMS database , 2009 .

[19]  Thomas L. Saaty,et al.  Estimating technological coefficients by the analytic hierarchy process , 1979 .

[20]  N. Delbart,et al.  Determination of phenological dates in boreal regions using normalized difference water index , 2005 .

[21]  N. Delbart,et al.  Remote sensing of spring phenology in boreal regions: A free of snow-effect method using NOAA-AVHRR and SPOT-VGT data (1982-2004) , 2006 .

[22]  Mark A. Friedl,et al.  Long-Term Detection of Global Vegetation Phenology from Satellite Instruments , 2012 .

[23]  Impacts of climate warming on plants phenophases in China for the last 40 years , 2002 .

[24]  H. Freeland,et al.  Spring phenology trends in Alberta, Canada: links to ocean temperature , 2000, International journal of biometeorology.

[25]  J. Mustard,et al.  Green leaf phenology at Landsat resolution: Scaling from the field to the satellite , 2006 .

[26]  B. Duchemin,et al.  VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products , 2004 .

[27]  David A. Ratkowsky,et al.  Nonlinear regression modeling : a unified practical approach , 1984 .

[28]  M. Schaepman,et al.  Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006 , 2009 .

[29]  Stefan Wunderle,et al.  Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements , 2008, Sensors.

[30]  G. Yohe,et al.  A globally coherent fingerprint of climate change impacts across natural systems , 2003, Nature.

[31]  Chang-Hoi Ho,et al.  Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008 , 2011 .

[32]  J. Schaber,et al.  Responses of spring phenology to climate change , 2004 .

[33]  C. Tucker,et al.  Increased plant growth in the northern high latitudes from 1981 to 1991 , 1997, Nature.

[34]  Hans W. Linderholm,et al.  Growing season changes in the last century , 2006 .

[35]  Zhou Guangsheng.  Responses of woody plants phenology to air temperature in Northeast China in 1980-2005 , 2010 .

[36]  Fang Wei-hua.  Responses of vegetation phenology in Northeast China to climate change , 2010 .

[37]  S. Goetz,et al.  Satellite-observed photosynthetic trends across boreal North America associated with climate and fire disturbance. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[38]  A. Richardson,et al.  Landscape controls on the timing of spring, autumn, and growing season length in mid‐Atlantic forests , 2012 .

[39]  Kenneth Levenberg.  A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[40]  D. Marquardt.  An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[41]  Aaron Moody,et al.  Trends in vegetation activity and their climatic correlates: China 1982 to 1998 , 2004 .

[42]  Jörg Schaber,et al.  Physiology-based phenology models for forest tree species in Germany , 2003, International journal of biometeorology.