Skip to main content
  • 571 Accesses

Abstract

In this chapter, land-cover change based on the Normalized Difference Vegetation Index (NDVI) derived from the NOAA AVHRR Global Vegetation Index (GVI) for the Lhasa area at the central Tibetan Plateau from 1985 to 1999 is presented, and its sensitivity to climate conditions is discussed, followed by analysis on vegetation phenologies and dynamics using the discrete Fourier transform (DFT). The time series of NDVI demonstrate a positive trend from 1985 to 1999, which means that general vegetation biomass on land surface presents increasing, and this trend is strongly associated with increased rainfall and temperature from the mid-1980s to 1990s. The correlation analysis shows that the NDVI is more sensitive to precipitation (r = 0.75, P < 0.01) than temperature (r = 0.63, P < 0.01) in this semiarid climate zone. The study also indicated that DFT is a very useful tool to understand vegetation phenologies and dynamic change through decomposition of temporal data to frequency domain.

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

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Andres, L., W.A. Salas, and D. Skoles. 1994. Fourier analysis of multi-temporal AVHRR data applied to a land cover classification. International Journal of Remote Sensing 15 (5): 1115–1121.

    Article  Google Scholar 

  • Azzali, S., and M. Menenti. 2000. Mapping vegetation-soil-climate complexes in southern Africa using temporal Fourier analysis of NOAAAVHRR data. International Journal of Remote Sensing 21: 973–996.

    Article  Google Scholar 

  • Bontemps, S., M. Herold, L. Kooistra, et al. 2012. Revisiting land cover observation to address the needs of the climate modeling community. Biogeosciences 9: 2145–2157.

    Article  Google Scholar 

  • Briggs, W.L., and V.E. Hensen. 1995. The DFT: An Owner’s Manual for the Discrete Fourier Transform. Philadelphia: Society for Industrial and Applied Mathematics.

    Book  Google Scholar 

  • Burgess, D.W., P. Lewis, and J.P. Muller. 1995. Topographic effects in AVHRR NDVI data. Remote Sensing of Environment 54: 223–232.

    Article  Google Scholar 

  • Chapin, F., and S. Zavaleta. 2000. Consequences of changing biodiversity. Nature 405: 234–242.

    Article  CAS  Google Scholar 

  • Chu, D. 2002. Spatial and Temporal Land-Use/Land-Cover Changes in Lhasa Area, Tibet. PhD thesis. Graduate School of Chinese Academy of Sciences, 20–23.

    Google Scholar 

  • ———. 2003. Global climate change and management strategies. Meteorology in Tibet, 25–27.

    Google Scholar 

  • Chuvieco, E., and A. Huete. 2009. Fundamentals of Satellite Remote Sensing. Boca Raton: CRC Press.

    Book  Google Scholar 

  • Comprehensive Scientific Expedition Team to Tibetan Plateau of CAS. 1984. Climate of Tibet. Beijing: Science Press, 43–44.

    Google Scholar 

  • Defries, R., M. Hansen, and J. Townshend. 1995. Global discrimination of land cover types from metrices derived from AVHRR pathfinder data. Remote Sensing of Environment 54 (3): 209–222.

    Article  Google Scholar 

  • DeFries, R., M. Hansen, J. Townshend, et al. 1998. Global land cover classifications at 8 km spatial resolution: The use of training data derived from Landsat imagery in decision tree classifiers. International Journal of Remote sensing 19 (16): 3141–3168.

    Article  Google Scholar 

  • Douglas, I. 1999. Hydrological investigations of forest disturbance and land cover impacts in South-East Asia: A review. Philosophical Transactions of the Royal Society of London, Series B 354: 1725–1738.

    Article  CAS  Google Scholar 

  • Ehlers, M., M.A. Jadkowski, R.R. Howard, et al. 1990. Application of SPOT data for regional growth analysis and local planning. Photogrammetric Engineering and Remote Sensing 56: 175–180.

    Google Scholar 

  • Giles, M., P. Foody, and J. Curran. 1994. Environmental Remote Sensing from Regional to Global Scales, 238 pp. New York: Wiley.

    Google Scholar 

  • Giri, C.P. 2012. Remote Sensing of Land Use and Land Cover: Principles and Applications. Boca Raton: CRC Press.

    Google Scholar 

  • Gutman, G., and A. Ignatov. 1995. Global land monitoring from AVHRR: Potential and limitations. International Journal of Remote sensing 16: 2301–2309.

    Article  Google Scholar 

  • Gutman, G., D. Tarpley, A. Ignatov, et al. 1995. The enhanced NOAA global land datasets from the advanced very high resolution radiometer. Bulletin of the American Meteorological Society 76: 1141–1156.

    Article  Google Scholar 

  • Hansen, M.C., and R.S. DeFries. 2004. Detecting long-term global forest change using continuous fields of tree-cover maps from 8-km advanced very high resolution radiometer (AVHRR) data for the years 1982–99. Ecosystems 7 (7): 695–716.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Holben, B., and R.S. Frazer. 1984. Red and near-infrared sensor response to off-nadir viewing. International Journal of Remote Sensing 5: 5145–5160.

    Article  Google Scholar 

  • Immerzeel, W.W., R.A. Quiroz, and S.M. de Jong. 2005. Understanding complex spatiotemporal weather patterns and land use interaction in the Tibetan Autonomous Region using harmonic analysis of SPOT VGT-S10 NDVI time series. International Journal of Remote Sensing 11: 2281–2296.

    Article  Google Scholar 

  • Justice, C.O., and P.H.Y. Hiernaux. 1986. Monitoring the grasslands of the Sahel using NOAA AVHRR data: Niger 1983. International Journal of Remote Sensing 7: 1475–1497.

    Article  Google Scholar 

  • Kleemann, J., G. Baysal, H.N. Bulley, et al. 2017. Assessing driving forces of land use and land cover change by a mixed-method approach in north-eastern Ghana, West Africa. Journal of Environmental Management 196: 411–442.

    Article  Google Scholar 

  • Lambin, E.F., and P. Meyfroidt. 2010. Land use transitions: Socio-ecological feedback versus socio-economic change. Land Use Policy 27 (2): 108–118.

    Article  Google Scholar 

  • Lawler, J.J., D.J. Lewis, E. Nelson, et al. 2014. Projected land-use change impacts on ecosystem services in the united states. Proceedings of the National Academy of Sciences of the United States of America 111 (20): 7492.

    Article  CAS  Google Scholar 

  • Lhasa City Agricultural and Pastoral Bureau. 1993. Land Resources in Lhasa City, 16–17. Beijing: China Agricultural Science and Technology Press.

    Google Scholar 

  • Lin, R., C. Li, and Y. Zhang. 2001. Climatic Resources for Agriculture in Lhasa, Tibet, 19–68. Beijing: Meteorological Press.

    Google Scholar 

  • Loveland, T.R., and A.S. Belward. 1997a. The international geosphere biosphere programme data and information system global land cover data set (DISCover). Acta Astronautica 41 (410): 681–689.

    Article  Google Scholar 

  • ———. 1997b. The IGBP-DIS global 1 km land cover data set, DISCover: Results. International Journal of Remote Sensing 18: 3289–3295.

    Article  Google Scholar 

  • Loveland, T.R., B.C. Reed, J.F. Brown, et al. 2000. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. International Journal of Remote Sensing 21: 1303–1330.

    Article  Google Scholar 

  • Mahmood, R., R.A. Pielke, K.G. Hubbard, et al. 2014. Land cover changes and their biogeophysical effects on climate. International Journal of Climatology 34 (4): 929–953.

    Article  Google Scholar 

  • Menenti, M., S. Azzali, A. de Vries, et al. 1993a. Vegetation monitoring in Southern Africa using temporal Fourier analysis of AVHRR/NDVI observations. In Proceedings, International Symposium on Remote Sensing in Arid and Semi-Arid Regions, 287–294. Lanzhou: LIGG.

    Google Scholar 

  • Menenti, M., S. Azzali, W. Verhoef, et al. 1993b. Mapping agro-ecological zones and time lag in vegetation growth by means of Fourier analysis of time series of NDVI images. Advances in Space Research 13 (5): 233–237.

    Article  Google Scholar 

  • Milich, L., and E. Weiss. 2000. GAC NDVI images: Relationship to rainfall and potential evaporation in the grazing lands of the Gourma (northern Sahel) and in the croplands of the Niger-Nigeria border (southern Sahel). International Journal of Remote Sensing 21: 261–280.

    Article  Google Scholar 

  • Moody, A., and D.M. Johnson. 2001. Land-surface phonologies from AVHRR using the discrete Fourier transform. Remote Sensing of Environment 75: 305–323.

    Article  Google Scholar 

  • NOAA GVI User’s Guide. 2001. http://www2.ncdc.noaa.gov/docs.

  • Olsson, L., and L. Eklundh. 1994. Fourier series for analysis of temporal sequences of satellite sensor imagery. International Journal of Remote Sensing 15: 3735–3741.

    Article  Google Scholar 

  • Penner, J.E. 1994. Atmospheric chemistry and air quality. In Changes in Land Use and Land Cover: A Global Perspective, ed. W.B. Meyer and B.L. Turner II, 175–209. Cambridge: Cambridge University Press.

    Google Scholar 

  • Pfeifer, M., M. Disney, T. Quaife, et al. 2012. Terrestrial ecosystems from space: A review of earth observation products for macroecology applications. Global Ecology and Biogeography 21: 603–624.

    Article  Google Scholar 

  • Piao, S., J. Fang, H. Liu, et al. 2005. NDVI-indicated decline in desertification in China in the past two decades. Geophysical Research Letters 32: L06402. https://doi.org/10.1029/2004GL021764.

    Article  Google Scholar 

  • Potter, C.S., and V. Brooks. 1998. Global analysis of empirical relations between annual climate and seasonality of NDVI. International Journal of Remote Sensing 19: 2921–2948.

    Article  Google Scholar 

  • Richard, Y., and I. Poccard. 1998. A statistical study of NDVI sensitivity to seasonal and interannual rainfall variations in Southern Africa. International Journal of Remote Sensing 19: 2907–2920.

    Article  Google Scholar 

  • Roerink, G.J., M. Menenti, W. Soepboer, et al. 2003. Assessment of climate impact on vegetation dynamics by using remote sensing. Physics and Chemistry of the Earth 28: 103–109.

    Article  Google Scholar 

  • Rogers, D.J., S.I. Hay, and M.J. Packer. 1996. Predicting the distribution of tsetse flies in West Africa using temporal Fourier processed meteorological satellite data. Annals of Tropical Medicine and Parasitology 90: 225–241.

    Article  CAS  Google Scholar 

  • Sellers, P.J., S.O. Tucker, G.J. Collatz, et al. 1994. A global 1 by 1 NDVI data set for climate Studies. Part 2: The generation of global fields of terrestrial biophysical parameters from the NDVI. International Journal of Remote Sensing 15 (17): 3519–3545.

    Article  Google Scholar 

  • Stöckli, R., and P.L. Vidale. 2004. European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset. International Journal of Remote Sensing 25: 3303–3330.

    Article  Google Scholar 

  • Tolessa, T., F. Senbeta, and M. Kidane. 2017. The impact of land use/land cover change on ecosystem services in the central highlands of Ethiopia. Ecosystem Services 23: 47–54.

    Article  Google Scholar 

  • Tucker, C.J., R.G. Townshend, and T.E. Goff. 1985. African land-cover classification using satellite data. Science 227 (4685): 369–375.

    Article  CAS  Google Scholar 

  • Tucker, C.J., J.E. Pinzon, M.E. Brown, et al. 2005. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing 26 (20): 4485–4498.

    Article  Google Scholar 

  • Turner, B.L., D. Skole, S. Sanderson, et al. 1995. Land-Use and Land-Cover Change (LUCC): Science/Research Plan. IGBP Report No. 35, HDP Report No.7, Stockholm, Geneva.

    Google Scholar 

  • Weng, Q. 2002. Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. Journal of Environmental Management 64: 273–284.

    Article  Google Scholar 

  • Yin, H., D. Pflugmacher, A. Li, et al. 2018. Land use and land cover change in inner Mongolia-understanding the effects of china’s re-vegetation programs. Remote Sensing of Environment 204: 918–930.

    Article  Google Scholar 

  • Zhang, H.K., and D.P. Roy. 2017. Using the 500 m MODIS land cover product to derive a consistent continental scale 30 m Landsat land cover classification. Remote Sensing of Environment 197: 15–34.

    Article  Google Scholar 

Download references

Acknowledgment

This chapter is derived in part from the author’s article published in Arctic, Antarctic, and Alpine Research on January 28, 2018, available online: https://doi.org/10.1657/1523-0430(07-501)[CHU]2.0.CO;2.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Chu, D. (2020). Land-Cover Change. In: Remote Sensing of Land Use and Land Cover in Mountain Region. Springer, Singapore. https://doi.org/10.1007/978-981-13-7580-4_7

Download citation

Publish with us

Policies and ethics