Spatial and temporal variation of global LAI during 1981–2006

doi:10.1007/s11442-010-0323-6

Abstract

Abstract:

Earth is always changing. Knowledge about where changes happened is the first step for us to understand how these changes affect our lives. In this paper, we use a long-term leaf area index data (LAI) to identify where changes happened and where has experienced the strongest change around the globe during 1981–2006. Results show that, over the past 26 years, LAI has generally increased at a rate of 0.0013 per year around the globe. The strongest increasing trend is around 0.0032 per year in the middle and northern high latitudes (north of 30°N). LAI has prominently increased in Europe, Siberia, Indian Peninsula, America and south Canada, South region of Sahara, southwest corner of Australia and Kgalagadi Basin; while noticeably decreased in Southeast Asia, southeastern China, central Africa, central and southern South America and arctic areas in North America.

Key words: global change, leaf area index, spatiotemporal variation, hot-spot areas

LIU Siliang, LIU Ronggao, LIU Yang. Spatial and temporal variation of global LAI during 1981–2006[J].Journal of Geographical Sciences, 2010, 20(3): 323-332.

References

[1] Achard F, Eva H D, Stibig H J et al., 2002. Determination of deforestation rates of the world’s humid tropical forests. Science, 297(5583): 999–1002.

[2] Buermann W, Wang Y J, Dong J R et al., 2002. Analysis of a multiyear global vegetation leaf area index data set. Journal of Geophysical Research-Atmospheres, 107(D22): 4646.

[3] Chen J M, Black T A, 1992. Defining leaf area index for non-flat leaves. Plant Cell and Environment, 15(4): 421–429.

[4] Cuomo V, Lanfredi M, Lasaponara R et al., 2001. Detection of interannual variation of vegetation in middle and southern Italy during 1985–1999 with 1 km NOAA AVHRR NDVI data. Journal of Geophysical Research- Atmospheres, 106(D16): 17863–17876.

[5] Deng F, Chen J M, Plummer S et al., 2006. Algorithm for global leaf area index retrieval using satellite imagery. IEEE Transactions on Geoscience and Remote Sensing, 44(8): 2219–2229.

[6] Donohue R J, McVicar T R, Roderick M L, 2009. Climate-related trends in Australian vegetation cover as inferred from satellite observations, 1981–2006. Global Change Biology, 15(4): 1025–1039.

[7] Funk C C, Brown M E, 2006. Intra-seasonal NDVI change projections in semi-arid Africa. Remote Sensing of Environment, 101(2): 249–256.

[8] Goetz S J, Bunn A G, Fiske G J et al., 2005. Satellite-observed photosynthetic trends across boreal North America associated with climate and fire disturbance. Proceedings of the National Academy of Sciences of the United States of America, 102(38): 13521–13525.

[9] Gu L H, Baldocchi D D, Wofsy S C et al., 2003. Response of a deciduous forest to the Mount Pinatubo eruption: Enhanced photosynthesis. Science, 299(5615): 2035–2038.

[10] Hansen M C, Defries R S, Townshend J R G et al., 2000. Global land cover classification at 1km spatial resolution using a classification tree approach. International Journal of Remote Sensing, 21(6/7): 1331–1364. Herrmann S M, Anyamba A, Tucker C J, 2005. Recent trends in vegetation dynamics in the African Sahel and their relationship to climate. Global Environmental Change-Human and Policy Dimensions, 15(4): 394–404.

[11] Jeyaseelan A T, Roy P S, Young S S, 2007. Persistent changes in NDVI between 1982 and 2003 over India using AVHRR GIMMS (global inventory Modeling and mapping studies) data. International Journal of Remote Sensing, 28(21): 4927–4946.

[12] Koenig R, 2008. Critical time for African rainforests. Science, 320(5882): 1439–1441. Liu R, Chen J M, Liu J et al., 2007. Application of a new leaf area index algorithm to China’s landmass using MODIS data for carbon cycle research. Journal of Environmental Management, 85(3): 649–658.

[13] Los S O, 1998. Estimation of the ratio of sensor degradation between NOAA AVHRR channels 1 and 2 from monthly NDVI composites. IEEE Transactions on Geoscience and Remote Sensing, 36(1): 206–213.

[14] Lucht W, Prentice I C, Myneni R B, 2002. Climatic control of the high-latitude vegetation greening trend and Pinatubo effect. Science, 296(5573): 1687–1689.

[15] Myneni R B, Keeling C D, Tucker C J, 1997. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature, 386(6626): 698–702.

[16] Myneni R B, Tucker C J, Asrar G et al., 1998. Interannual variations in satellite-sensed vegetation index data from 1981 to 1991. Journal of Geophysical Research-Atmospheres, 103(D6): 6145–6160.

[17] Paruelo J M, Garbulsky M F, Guerschman J P et al., 2004. Two decades of Normalized Difference Vegetation Index changes in South America: Identifying the imprint of global change. International Journal of Remote Sensing, 25(14): 2793–2806.

[18] Pouliot D, Latifovic R, Olthof I, 2009. Trends in vegetation NDVI from 1 km AVHRR data over Canada for the period 1985–2006. International Journal of Remote Sensing, 30(1): 149–168.

[19] Sastry N, 2002. Forest fires, air pollution, and mortality in Southeast Asia. Demography, 39(1): 1–23.

[20] Self S, Mouginismark P J, 1995. Volcanic eruptions, predictions, hazard assessment, remote sensing, and social implications. Reviews of Geophysics, 33: 257–262.

[21] Slayback D A, Pinzon J E, Los S O et al., 2003. Northern hemisphere photosynthetic trends 1982–99. Global Change Biology, 9(1): 1–15.

[22] Soares B S, Nepstad D C, Curran L M et al., 2006. Modelling conservation in the Amazon basin. Nature, 440(708 3): 520–523.

[23] Sobrino J A, Julien Y, Atitar M et al., 2008. NOAA-AVHRR orbital drift correction from solar zenithal angle data. IEEE Transactions on Geoscience and Remote Sensing, 46(12): 4014–4019.

[24] Trishchenko A P, Cihlar J, Li Z Q, 2002. Effects of spectral response function on surface reflectance and NDVI measured with moderate resolution satellite sensors. Remote Sensing of Environment, 81(1): 1–18.

[25] Tucker C J, Pinzon J E, Brown M E 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.

[26] Xiao J, Moody A, 2005. Geographical distribution of global greening trends and their climatic correlates: 1982–1998. International Journal of Remote Sensing, 26(11): 2371–2390.

[27] Zhang Y X, Song C H, 2006. Impacts of afforestation, deforestation, and reforestation on forest cover in China from 1949 to 2003. Journal of Forestry, 104(7): 383–387.

[28] Zhou L, Kaufmann R K, Tian Y et al., 2003. Relation between interannual variations in satellite measures of northern forest greenness and climate between 1982 and 1999. Journal of Geophysical Research-Atmospheres, 108(D1): 4004.

[29] Zhou L M, 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-Atmospheres, 106(D17): 20069–20083.