Skip to main content
SpringerLink
Log in

Analysis of net primary productivity of terrestrial vegetation on the Qinghai-Tibet Plateau, based on MODIS remote sensing data

  • Research Paper
  • Published:
Science China Earth Sciences Aims and scope Submit manuscript

Abstract

GLO-PEM is driven by soil moisture data of AMSR-E and PAR (Photosynthetically active radiation) which is retrieved from MODIS atmospheric data product in this paper. Using remote sensing data can overcome uncertainty brought from interpolation of precipitation and PAR. Comparing with observed radiation data, PAR retrieved by remote sensing is in high accuracy in this study. RMSE is 9 and 19.68 W m−2 and R 2 is 0.89 and 0.67 respectively. As a result of GLO-PEM, annual total amount of NPP of Qinghai-Tibet Plateau is 0.37 Pg C a−1 in 2005–2008. There is a significant linear relationship between field and simulated NPP. Determination coefficient reached 0.93. NPP is decrease from southeast to northwest in the Qinghai-Tibet Plateau. NPP changes from 0 to 1500 g C m−2 a−1. There is different limit factors of vegetation growth in west and east plateau. In the west of 450 mm rainfall line, the limit factors is precipitation. In the east of 450 mm rainfall line, temperature is the dominated factor of vegetation growth.

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

  1. Zheng D, Yao T D. The Uplifting and Environmental Effectivity in Qinghai-Tibet Plateau. (in Chinese) Beijing: Science Press, 2004

    Google Scholar 

  2. Wu S H, Yin Y H, Zheng D, et al. Climate changes in the Tibetan Plateau during the last three decades (in Chinese). Acta Geogr Sin, 2005, 60: 3–11

    Google Scholar 

  3. Huang M, Ji J J, Peng L L. The response of vegetation Net Primary Productivity to climate change during 1981–2000 in the Tibetan Plateau (in Chinese). Clim Environ Res, 2008, 13: 608–617

    Google Scholar 

  4. Cramer W, Kicklighter D W, Bondeau A, et al. Comparing global models of terrestrial net primary productivity (NPP): Overview and key results. Glob Change Biolgoy, 1999, 5: 1–15

    Article  Google Scholar 

  5. Field C B, Behrenfeld J, Randerson J T, et al. Primary production of the biosphere: Intergrating terrestrial and oceanic components. Science, 1998, 281: 237–240

    Article  Google Scholar 

  6. Field C B, Randerson J T, Malmstrom C M. Global net primary production: combining ecology and remote sensing. Remote Sensing Environ, 1995, 51: 74–88

    Article  Google Scholar 

  7. Keeling C D, Chin J F S, Whorf T P. Increased activity of northern vegetation inferred from atmospheric CO2 measurements. Nature, 1996, 382: 146–149

    Article  Google Scholar 

  8. Ruimy A, Kergoat L, Bondeau A. Comparing global models of terrestrial net primary productivity (NPP): Analysis of differences in light absorption and light-use efficiency. Glob Change Biol, 1999, 5(Suppl. 1): 56–64

    Article  Google Scholar 

  9. Lü J H, Ji J J. A simulation study of atmosphere-vegetation interaction over the Tibetan Plateau. Part II: Net primary productivity and leaf area index (in Chinese). Chin J Atmos Sci, 2002, 26: 255–262

    Google Scholar 

  10. Zhou C P, Ouyang H, Wang Q X, et al. Estimation of Net Primary Productivity in Tibetan Plateau (in Chinese). Acta Geogr Sin, 2004, 59: 74–79

    Google Scholar 

  11. Piao S L, Fang J Y. Terrestrial net primary production and its spatiotemporal patterns in Qinghai-Xizang, China during 1982–1999 (in Chinese). Nat Resour J, 2002, 17: 373–381

    Google Scholar 

  12. Prince S D, Goward S N. Global primary production: a remote sensing approach. J Biogeogr, 1995, 22: 815–835

    Article  Google Scholar 

  13. Cao M, Prince S D, Small J, et al. Satellite remotely sensed interannual variability in terrestrial net primary productivity from 1980 to 2000. Ecosystems, 2004, 7: 233–242

    Article  Google Scholar 

  14. Hunt E R. Relationship between woody biomass and PAR conversion efficiency for estimating net primary production from NDVI. Int J Remote Sensing, 1994, 15: 1725–1729

    Article  Google Scholar 

  15. Running S W, Coughlan J C. A general model of forest ecosystem processes for regional application I. Hydrological balance, canopy gas exchange and primary production processes. Ecol Model, 1988, 42: 125–154

    Article  Google Scholar 

  16. Ryan M G. A simple method for estimating gross carbon budgets for vegetation in forest ecosystems. Tree Phys, 1991, 9: 255–266

    Google Scholar 

  17. Liu J, Chen J M, Cihlar J, et al. Net primary productivity distribution in the BOREAS region from a process model using satellite and surface data. J Geophys Res, 1999, 104: 27735–2754

    Article  Google Scholar 

  18. Laake P E, Azofeifa G A. Simplified atmospheric radiative transfer modeling for estimation incident PAR using MODIS atmosphere products. Remote Sensing Environ, 2004, 91: 98–113

    Article  Google Scholar 

  19. Laake P E, Sanchez-Azofeifa G A. Mapping PAR using MODIS atmosphere products. Remote Sensing Environment. 2005, 94: 554–563

    Article  Google Scholar 

  20. Chen L, Gao Y, Yang L, et al. MODIS-derived daily PAR simulation from cloud-free images and its validation. Solar Energy, 2008, 82: 528–534

    Article  Google Scholar 

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

    Article  Google Scholar 

  22. Kaufman Y J, Tanre D. Algorithm for remote sensing of tropospheric aerosols from MODIS. Algorithm theoretical basis document. Green belt, MD: NASA Goddard Space Flight Center, Revised October 26, 1998

    Google Scholar 

  23. Gao B, Kaufman Y J. The MODIS near-IR water vapor algorithm. Algorithm technical background document. Greenbelt, MD: NASA Goddard Space Flight Center, 1998

    Google Scholar 

  24. King M D, Tsay S C, Platnick S E, et al. Cloud retrieval algorithms for MODIS: Optical thickness, effective particle radius and thermodynamic phase. MODIS algorithm theoretical basis document no. ATBD-MOD-05. MOD06-Cloud product. Greenbelt, MD: NASA Goddard Space Flight Center, 23 December 1997

    Google Scholar 

  25. Menzel W P, Baum B A, et al. Cloud top properties and cloud phase algorithm theoretical basis document. Algorithm theoretical basis document. Greenbelt, MD: NASA Goddard Space Flight Center, Version 6, September 2002

    Google Scholar 

  26. Knyazikhin Y, Glassy J, Privette J L, et al. MODIS Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation Absorbed by Vegetation (FPAR) Product (MOD 15) Algorithm Theoretical Basis Document, 1999

  27. Njoku E G, Jackson T J, Lakshmi V, et al. Soil moisture retrieval from AMSR-E. IEEE Geosci Remote Sensing, 2003, 41: 215–229

    Article  Google Scholar 

  28. Hutchinson M F. ANUSPLIN version 4.2 user guide. 2001

  29. Grant R H, Ultraviolet band photosynthetically active radiation environment to fin cline leaf surfaces in a maize canopy and implications for modeling. Agr Forest Meteorol, 1999, 96: 187–201

    Article  Google Scholar 

  30. Alado S I, Foyo-Morenoi, Olmof J, et al. Relationship between net radiation and solar radiation for semiarid shrub-land. Agr Forest Meteorol, 2003, 116: 221–227

    Article  Google Scholar 

  31. Li Y N, Zhou H K. Features of photosynthetic active radiation (PAR) in Haibei alpinemeadow area of Qilian Mountain during plant growing period (in Chinese). Plateau Meteorol, 2002, 21: 90–95

    Google Scholar 

  32. Wang X, Yin G C, Zhou G Y, et al. Temporal and spatial distribution of photosynthetically active radiation flux of coniferous and broadleaved mixed forest at the Dinghu Mountain, low subtropical China (in Chinese). J Beijing Forestry Univ, 2007, 29: 90–96

    Google Scholar 

  33. Li Y N, Zhao L, Xu S X, et al, The climate characteristics of radiation of Haibei alpine meadow ecosystem research station (in Chinese). J Mt Sci, 2006, 24: 298–305

    Google Scholar 

  34. Gill R, Kelly R H, Parton W J, et al. Using simple environmental variables to estimate below-ground productivity in grasslands. Glob Ecol Biogeogr, 2002, 11: 79–86

    Article  Google Scholar 

  35. Fan J, Shao Q, Liu J, et al. Assessment of effects of climate change and grazing activity on grassland yield in the Three Rivers Headwaters Region of Qinghai-Tibet Plateau, China. Environment Monitor Assess, 2010, 170: 571–584

    Article  Google Scholar 

  36. Wang Q J, Zhou X M, Zhang Y Q, et al. Community structure and biomass dynamic of the kobresia pygmaea steppe meadow (in Chinese). Acta Phytoecol Sin, 1995, 19: 225–235

    Google Scholar 

  37. Zhang J X, Cao G M, Zhou D W, et al. The carbon storage and carbon cycle among the atmosphere, soil, vegetation and a nimal in the Kobresia humilis alpine meadow ecosystem (in Chinese). Acta Ecol Sin, 2003, 23: 627–634

    Google Scholar 

  38. Gao Q Z, Wan Y F, Li Y. Grassland net primary productivity and its spatiotemporal distribution in Northern Tibet: A study with CASA model (in Chinese). Chin J Appl Ecol, 2007, 18: 2526–2532

    Google Scholar 

  39. Luo T X, Li W H, Leng Y F. Estimation of total biomass and potential distribution of net primary productivity in the Tibetan Plateau. Geogr Res, 1998, 17: 832–840

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China

    ZhuoQi Chen

  2. Institute of Geographic Sciences and Natural Resource Research, Chinese Academy of Sciences, Beijing, 100101, China

    QuanQin Shao, JiYuan Liu & JunBang Wang

Authors
  1. ZhuoQi Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. QuanQin Shao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. JiYuan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. JunBang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to QuanQin Shao.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, Z., Shao, Q., Liu, J. et al. Analysis of net primary productivity of terrestrial vegetation on the Qinghai-Tibet Plateau, based on MODIS remote sensing data. Sci. China Earth Sci. 55, 1306–1312 (2012). https://doi.org/10.1007/s11430-012-4389-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11430-012-4389-0

Keywords

Search

Navigation