Skip to main content
SpringerLink
Log in

Spatial-temporal patterns of vegetation dynamics and their relationships to climate variations in Qinghai Lake Basin using MODIS time-series data

  • Published:
Journal of Geographical Sciences Aims and scope Submit manuscript

Abstract

Global warming has led to significant vegetation changes in recent years. It is necessary to investigate the effects of climatic variations (temperature and precipitation) on vegetation changes for a better understanding of acclimation to climatic change. In this paper, we focused on the integration and application of multi-methods and spatial analysis techniques in GIS to study the spatio-temporal variation of vegetation dynamics and to explore the vegetation change mechanism. The correlations between EVI and climate factors at different time scales were calculated for each pixel including monthly, seasonal and annual scales respectively in Qinghai Lake Basin from the year of 2001 to 2012. The primary objectives of this study are to reveal when, where and why the vegetation change so as to support better understanding of terrestrial response to global change as well as the useful information and techniques for wise regional ecosystem management practices. The main conclusions are as follows: (1) Overall vegetation EVI in the region increased 6% during recent 12 years. The EVI value in growing seasons (i.e. spring and summer) exhibited very significant improving trend, accounted for 12.8% and 9.3% respectively. The spatial pattern of EVI showed obvious spatial heterogeneity which was consistent with hydrothermal condition. In general, the vegetation coverage improved in most parts of the area since nearly 78% pixel of the whole basin showed increasing trend, while degraded slightly in a small part of the area only. (2) The EVI change was positively correlated with average temperature and precipitation. Generally speaking, in Qinghai Lake Basin, precipitation was the dominant driving factor for vegetation growth; however, at different time scale its weight to vegetation has differences. (3) Based on geo-statistical analysis, the autumn precipitation has a strong correlation with the next spring EVI values in the whole region. This findings explore the autumn precipitation is an important indicator, and then, limits the plant growth of next spring.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Anderson R G, Canadell, J G, Randerson J T et al., 2010. Biophysical considerations in forestry for climate protection. Frontiers in Ecology and the Environment, 9(3): 174–182.

    Article  Google Scholar 

  • Breshears D D and Barnes F J, 1999. Interrelationships between plant functional types and soil moisture heterogeneity for semiarid landscapes within the grassland/forest continuum: A unified conceptual model. Landscape Ecology, 14(5): 465–478.

    Article  Google Scholar 

  • Carpenter C, 2005. The environmental control of plant species density on a Himalayan elevation gradient. Journal of Biogeography, 32(6): 999–1018.

    Article  Google Scholar 

  • Chamaille-Jammes S, Fritz H, Murindagomo F, 2006. Spatial patterns of the NDVI-rainfall relationship at the seasonal and inter-annual time scales in an African savanna. International Journal of Remote Sensing, 27(23): 5185–5200.

    Article  Google Scholar 

  • Chen J, Jonsson P, Tamura M et al., 2004. A simple method for reconstructing a high-quality NDVI time-series dataset based on the Savitzky-Golay filter. Remote Sensing of Environment, 91: 332–344.

    Article  Google Scholar 

  • Chen X, Hu B, Yu R, 2005. Spatial and temporal variation of phonological growing season and climate change impacts in temperate eastern China. Global Change Biology, 11: 1118–1130.

    Article  Google Scholar 

  • Chen Xiaoguang, Li Jianping, Li Zhijun et al., 2007. Vegetation coverage and its relation with climate change in Qinghai Lake area. Journal of Desert Research, 27(5): 797–804. (in Chinese)

    Google Scholar 

  • Cramer W, Bondeau A, Woodward F I et al., 2001. Global response of terrestrial ecosystem structure and function to CO2 and climate change: Results from six dynamic global vegetation models. Global Change Biology, 7: 357–373.

    Article  Google Scholar 

  • Fay P A, Kaufman D M, Nippert J B et al., 2008. Changes in grassland ecosystem function due to extreme rainfall events: Implications for responses to climate change. Global Change Biology, 14: 1600–1608.

    Article  Google Scholar 

  • Feng S, Tang M C, Wang D M, 1998. New evidence for the Qinghai-Xizang (Tibet) Plateau as a pilot region of climatic fluctuation in China. Chinese Science Bulletin, 43(20): 1475–1479.

    Article  Google Scholar 

  • Frolking S, Palace M W, Clark D B et al., 2009. Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on above-ground biomass and canopy structure. Journal Geophysical Research, 114.

  • Gao X, Huete A R, Ni W G et al., 2000. Optical-biophysical relationships of vegetation spectra without background contamination. Remote Sensing of Environment, 74: 609–620.

    Article  Google Scholar 

  • Gaston K J, 2000. Global patterns in biodiversity, Nature, 405(6783): 220–227.

    Article  Google Scholar 

  • Guillevic P, Koster R D, Suarez M J et al., 2002. Influence of the inter-annual variability of vegetation on the surface energy balance: A global sensitivity study. Journal of Hydrometeorology, 3(6): 617–629.

    Article  Google Scholar 

  • Holben B N, 1986. Characteristics of maximum value composite images from temporal AVHRR. International Journal of Remote Sensing, 7: 1417–1434.

    Article  Google Scholar 

  • Huete A R, Didan K, Miura T et al., 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83(1/2): 195–213.

    Article  Google Scholar 

  • Huete A R, Justice C, Liu H, 1994. Development of vegetation and soil indexes for MODIS-EOS. Remote Sensing of Environment, 49: 224–234.

    Article  Google Scholar 

  • Huete A R, Liu H Q, Batchily K et al., 1997. A comparison of vegetation indices global set of TM images for EOS-MODIS. Remote Sensing of Environment, 59(3): 440–451.

    Article  Google Scholar 

  • Jackson R B, Randerson J T, Canadell J G et al., 2008. Protecting climate with forests. Environmental Research Letters, 3, 044006.

    Article  Google Scholar 

  • Justice C, Vermote E, Townshend J et al., 1998. The Moderate Resolution Imaging Spectroradiometer (MODIS): Land remote sensing for global change research. IEEE Transactions on Geoscience and Remote Sensing, 36, 1228–1249.

    Article  Google Scholar 

  • Li Yungang, He Daming 2009. The spatial and temporal variation of NDVI and its relationships to the climatic factors in Red River Basin. Journal of Mountain Science, 27(3): 333–340.

    Google Scholar 

  • Li D, Lewis J, Rowland J et al., 2004. Evaluation of land performance in Senegal using multi-temporal NDVI and rainfall series. Journal of Arid Environments, 59(3): 463–480.

    Article  Google Scholar 

  • Loik M E, Breshears D D, Lauenroth W K et al., 2004. A multi-scale perspective of water pulses in dryland ecosystems: climatology and ecohydrology of the western USA. Oecologia, 141(2): 269–281.

    Article  Google Scholar 

  • Mao F, Tang S H, Sun H et al., 2008. A study of dynamic change of dry and wet climate regions in the Tibetan Plateau over the last 46 years. Chin. J. Atmos. Sci., 32: 499–507. (in Chinese)

    Google Scholar 

  • McCulley R L, Burke I C, Nelson J A et al., 2005. Regional patterns in carbon cycling across the Great Plains of North America. Ecosystems, 8: 106–121.

    Article  Google Scholar 

  • Mu Shaojie, Yang Hongfei, Li Jianlong et al., 2013. Spatio-temporal dynamics of vegetation coverage and its relationship with climate factors in Inner Mongolia, China. Journal of Geographical Science, 23(2): 231–246.

    Article  Google Scholar 

  • Nemani R, Hashimoto H, Votava P et al., 2009. Monitoring and forecasting protected area ecosystem dynamics using the Terrestrial Observation and Prediction System (TOPS). Remote Sensing of Environment, 113, 1497–1509.

    Article  Google Scholar 

  • Nemani R R, Keeling C D, Hashimoto H et al., 2003. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 300(5625): 1560–1563.

    Article  Google Scholar 

  • Piao S, Friedlingstein P, Ciais P et al., 2007. Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades. Global Biogeochemical Cycles, 21(3): GB3018.

    Article  Google Scholar 

  • Piao S L, Cui M D, Chen A P et al., 2011. Altitude and temperature dependence of change in the spring vegetation green-up date from 1982 to 2006 in the Qinghai-Xizang Plateau. Agricultural and Forest Meteorology, 151, 1599–1608.

    Article  Google Scholar 

  • Piao S L, Fang J Y, Ji W et al., 2004. Variation in a satellite-based vegetation index in relation to climate in China. Journal of Vegetation Science, 15(2): 219–226.

    Article  Google Scholar 

  • Sims D A, Rahman A F, Cordova V D et al., 2006. On the use of MODIS EVI to assess gross primary productivity of North American ecosystems, Journal of Geophysical Research, 111: G04015.

    Article  Google Scholar 

  • Theurillat J, Guisan A, 2001. Potential impact of climate change on vegetation in the European Alps: A Review. Climatic Change, 50: 77–109.

    Article  Google Scholar 

  • Verbesselt J, Hyndman R, Newnham G et al., 2010. Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment, 114: 106–115.

    Article  Google Scholar 

  • Wang J, Rich P M, Price K P, 2003. Temporal responses of NDVI to precipitation and temperature in the central Great Plains, USA. International Journal of Remote Sensing, 24(11): 2345–2364.

    Article  Google Scholar 

  • Wang Junbang, Tao Jian, Li Guicai et al., 2010. Monitoring inter-annual vegetation variation in middle Inner Mongolia through MODIS NDVI. Journal of Geo-information Science, 12(6): 835–842.

    Google Scholar 

  • White A B, Kumar P, Tcheng D, 2005. A data mining approach for understanding topographic control on climate-induced inter-annual vegetation variability over the United States, Remote Sensing of Environment, 98: 1–20.

    Article  Google Scholar 

  • Xu Jianhua, 2002. Mathematical Methods in Contemporary Geography. Beijing: High Education Press. (in Chinese)

    Google Scholar 

  • Xu X Q, Chen H, LEVY Jason K, 2008. Plateau vegetation cover change and its spatial and temporal characteristics of the Causes of climate warming. Chinese Science Bulletin, 54(3): 456–462.

    Google Scholar 

  • Zhang Geli, Xu Xingliang, Zhou Caiping et al., 2011. Responses of grassland vegetation to climatic variations on different temporal scales in Hulun Buir Grassland in the past 30 years. Journal of Geographical Sciences, 21(4): 634–650.

    Article  Google Scholar 

  • Zhou L, Tucker C J, Kaufmann R K et al., 2001. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research, 106(D17): 20069–20083.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

    Wei Guo, Xiangnan Ni & Duanyang Jing

  2. School of Urban and Resources Sciences, Northwest University, Xi’an, 710032, China

    Shuheng Li

Authors
  1. Wei Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiangnan Ni
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Duanyang Jing
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shuheng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shuheng Li.

Additional information

Foundation: National Science & Technology Support Program, No.2012BAH31B03; National Natural Science Foundation of China, No.41301007; No.40901101; The Fundamental Research Funds for the Central Universities, No.xjj2013079

Author: Guo Wei, PhD, specialized in physical geography.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guo, W., Ni, X., Jing, D. et al. Spatial-temporal patterns of vegetation dynamics and their relationships to climate variations in Qinghai Lake Basin using MODIS time-series data. J. Geogr. Sci. 24, 1009–1021 (2014). https://doi.org/10.1007/s11442-014-1134-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11442-014-1134-y

Keywords

Search

Navigation