Scientia Agricultura Sinica ›› 2016, Vol. 49 ›› Issue (22): 4352-4365.doi: 10.3864/j.issn.0578-1752.2016.22.008

• TILLAGE & CULTIVATION·PHYSIOLOGY & ECOLOGY • Previous Articles     Next Articles

Analysis of Temporal and Spatial Variation of Vegetation Phenology in the Loess Plateau

LI Qiang1,2, ZHANG Chong3, REN Zhi-yuan1   

  1. 1Tourism and Environment College of Shaanxi Normal University, Xi’an 710119
    2Department of Environment and Resource Management, Shaanxi Xueqian Normal University, Xi’an 710100
    3Shaanxi Key Laboratory of Disaster Monitoring and  Mechanism Modeling, Baoji University of Arts and Sciences, Baoji 721013, Shaanxi
  • Received:2015-11-20 Online:2016-11-16 Published:2016-11-16

Abstract: 【Objective】The Loess plateau is in the transitional region from wetness to dryness, from forest to grassland, from farming to animal husbandry, being the sensitive zone in climate change and agricultural development in China, the research on phenological feature of surface vegetation coverage in the region is of directive significance to agricultural production, environmental protection and ecological construction. Analysis of difference in phenological trends of vegetation in different time series and altitudes and hydrothermal conditions shall offer theoretical support and decision basis for current agricultural ecological environment improvement and sustainable development on loess plateau.【Method】Phenological feature values of vegetation on Loess Plateau every year were determined and phenological change trend was analyzed based on NDVI of ten-day values of SPOT VEGETATION from 1998 to 2012 and combined with harmonic analysis method and linear trend method.【Result】(1) From 1998 to 2012, the start of growing season advanced by 0.9 d on average every year and the end of growing season delayed by about 0.8 d on average every year, the length of growing season every year extended by 1.7 d on average under the joint action of advance at the start of growing season and delay at the end of growing season. (2) Hydrothermal condition on Loess Plateau has an immediate impact on phenological difference, the restrictive temperature for vegetation growth is 9,with the restrictive precipitation of 475 mm and 540 mm, respectively and restrictive altitude of 1 750 m. (3) The spatial partial correlation coefficients between the length trend of growing season of vegetation and altitude and air temperature are 0.0591and 0.0139 respectively, the spatial partial correlation coefficients between the length trend of growing season of vegetation and precipitation is -0.0174, therefore, the degree of correlation between three factors and the trend at the start of growing season is higher than that at the end of growing season.【Conclusion】The zones showing a significant and stable trend of phenological feature of vegetation on loess plateau are primarily distributed on plateau in the north of Shaanxi and Beishan in the middle of Shanxi. The phenological change in arid area and desert and grassland area in northwest is mainly subject to control by air temperature. The phenological change in semi-arid area and farming and grassland areas is mainly subject to control by precipitation. The phenological change in agricultural area in Fenwei Basin is subject to hydrothermal condition. Difference in hydrothermal condition has an insignificant impact on vegetation phenology in broad leaved forest zone. Altitude has an insignificant impact on change trend of vegetation phenology on loess plateau. The extension trend of growing season is on the increase with the increase of altitude and air temperature under the joint action of the start and end of growing reason, the shortening trend of growing season is on the increase with the increase of precipitation, the change characteristics of the same type of vegetations in terms of phenological trend based on the change of altitude, precipitation and air temperature are consistent, the change characteristics at the start of growing season have a greater influence on length change of growing season compared with that at the end of growing season.

Key words: vegetation coverage, growth season, harmonic analysis, Fourier interpolation, loess plateau

[1]    Foley J A, Levis S, Costa M H, Cramer W, Pollard D. Incorporating dynamic vegetation cover within global climate models. Ecological Applications , 2000, 10: 1620-1632.
[2]    IPCC. 4th Assessment report of the intergovernmental panel on climate change. Synthesis Report, 2007: 52.
[3]    穆少杰, 李建龙, 陈奕兆. 2001-2010年内蒙古植被覆盖度时空变化特征. 地理学报, 2012, 67(9): 1255-1268.
MU S J, LI J L, CHEN Y Z. Spatial differences of variations of vegetation coverage in Inner Mongolia during 2001-2010. Acta Geographica Sinica, 2012, 67(9): 1255-1268. (in Chinese)
[4]    Tucker C J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 1979, 8(2): 127-150.
[5]    Prince S D, Tucker C J. Satellite remote sensing of rangelands in Botswana II. NOAA AVHRR and herbaceous vegetation. International Journal of Remote Sensing, 1986, 7(11): 1555-1570.
[6]    Alcaraz-Segura D, Chuvieco E, Epstein H E, Kasischke E S, Trishchenko A. Debating the greening vs. browning of the North American boreal forest: Differences between satellite datasets. Global Change Biology, 2009, 16(2): 760-770.
[7]    Pettorelli N, Vik J O, Mysterud A, Gaillard J M, Tucker C J, Stenseth N C. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology & Evolution, 2005, 20(9): 503-510.
[8]    White M A, de Beurs K M, Didan K, Inouye D W, Richardson A D, Jensen O P, O’KEEFE J, ZHANG G. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006. Global Change Biology, 2009, 15: 2335-2359.
[9]    Tottrup C, Rasmussen M S. Mapping long-term changes in savannah crop productivity in Senegal through trend analysis of time series of remote sensing data. Agriculture, Ecosystems & Environments, 2004, 103(3): 545-560.
[10]   Hüttich C, Herold M, Schmullius C, Egorov V, Bartalev S A. Indicators of Northern Eurasia's land-cover change trends from SPOT-VEG ETATION time-series analysis 1998-2005. Internation al Journal of Remote Sensing, 2007, 28: 4199-4206.
[11]   Symeonakis E, Drake N. Monitoring desertification and land degradation over sub-Saharan Africa. International Journal of Remote Sensing, 2004, 25(3): 573-592.
[12]   Sparks T H, Aasa A, Huber K, Wadsworth R. Changes and patterns in biologically relevant temperatures in Europe 1941-2000. Climate Research, 2009, 39: 191-207.
[13]   Zhang K, Kimball J S, Mu Q, Jones L A, Goetz S J, Running S W. Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005. Journal of Hydrology, 2009, 379(1): 92-110.
[14]   White M A, Running S W, Thornton P E. The impact of growing-season length variability on carbon assimilation and evapotranspiration over 88 years in the eastern US deciduous forest. International Journal of Biometeorology, 1999, 42(3): 139-145.
[15]   谢宝妮, 秦占飞, 王洋, 常庆瑞. 基于遥感的黄土高原植被物候监测及其对气候变化的响应. 农业工程学报, 2015, 31(15): 153-160.
Xie B N, Qin Z F, Wang Y, Chang Q R. Monitoring vegetation phenology and their response to climate change on Chinese    Loess Plateau based on remote sensing. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(15): 153-160. (in Chinese)
[16]   韦振锋, 任志远, 张翀. 1999-2010年陕甘宁黄土高原区气候对植被物候的影响. 水土保持通报, 2014, 34(5): 232-236.
Wei Z F, Ren Z Y, Zhang C. Impact of climate on vegetation phenology on Loess Plateau in Shaanxi-Gansu-Ningxia Region during 1999-2010. Bulletin of Soil and Water Conservation, 2014, 34(5): 232-236. (in Chinese)
[17]   张晗, 任志远. 基于Whittaker滤波的陕西省植被物候特征. 中国沙漠, 2015, 35(4): 901-906.
Zhang H, Ren Z Y. Remote sensing analysis of vegetation phenology characteristics in Shaanxi province based on Whittaker Smooth method. Journal of Desert Research, 2015, 35(4): 901-906. (in Chinese)
[18]   Yu H Y, Luedeling E, Xu J C. Winter and spring warming result in delayed spring phenology on the Tibetan Plateau. PNAS, 2010, 107(51): 22151-22156.
[19]   Zhang X Y, Friedl M A, Schaaf C B, Strahler A H, Hodges J C F, Gao F, Reed B C,Huete A. Monitoring vegetation phenology using MODIS. Remote Sensing of Environment, 2003, 84: 471-475.
[20]   Kendall M G. Rank Correlation Methods, 3rd edition. New York: Hafner Publishing Company, 1962.
[21]   Julien Y, Sobrino J A. Global land surface phenology trends from GIMMS database. International Journal of Remote Sensing, 2009, 30: 3495-3513.
[22]   Zhou L M, Tucker C J, Kaufmann R K, MYNENI R B. Variation in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research Atmospheres, 2001, 106: 20069-20083.
[23]   Jeong S J, Ho C H, Gim H J, BROWN M E. Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemi-sphere for the period 1982-2008. Global Change Biolog, 2001, 17: 2385-2399.
[24]   Piao S L, Fang J Y, Zhou L M, Ciais P, Zhu B. Variations in satellite-derived phenology in China’s temperate vegetation. Global Change Biology, 2006, 12: 672-685.
[25]   Zhang X Y, Friedl M A, Schaaf C B, Strahler A H, Hodges J C F, Gao F, Reed B C, Huete A. Monitoring vegetation phenology using MODIS. Remote Sensing of Environment, 2003, 84: 471-475.
[26]   俎佳星, 杨健. 东北地区植被物候时序变化. 生态学报, 2016, 36(7): 2015-2023.
ZU J X, YANG J. Temporal variation of vegetation phenology in northeastern China. Acta Ecological Sinica, 2016, 36(7): 2015-2023. (in Chinese)
[27]   Wang C, Cao R Y, Chen J, Rao Y,Tang Y. Temperature sensitivity of spring vegetation phenology correlates to within-spring warming speed over the Northern Hemisphere. Ecological Indicators, 2015, 50(3): 62-68.
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