Using leaf area index (LAI) to assess vegetation response to drought in Yunnan province of China
- 83 Downloads
Climatic extremes such as drought have becoming a severe climate-related problem in many regions all over the world that can induce anomalies in vegetation condition. Growth and CO2 uptake by plants are constrained to a large extent by drought. Therefore, it is important to understand the spatial and temporal responses of vegetation to drought across the various land cover types and different regions. Leaf area index (LAI) derived from Global Land Surface Satellite (GLASS) data was used to evaluate the response of vegetation to drought occurrence across Yunnan Province, China (2001–2010). The meteorological drought was assessed based on Standardized Precipitation Index (SPI) values. Pearson’s correlation coefficients between LAI and SPI were examined across several timescales within six sub-regions of the Yunnan. Further, the drought-prone area was identified based on LAI anomaly values. Lag and cumulative effects of lack of precipitation on vegetation were evident, with significant correlations found using 3-, 6-, 9- and 12-month timescale. We found 9-month timescale has higher correlations compared to another timescale. Approximately 29.4% of Yunnan’s area was classified as drought-prone area, based on the LAI anomaly values. Most of this drought-prone area was distributed in the mountainous region of Yunnan. From the research, it is evident that GLASS LAI can be effectively used as an indicator for assessing drought conditions and it provide valuable information for drought risk defense and preparedness.
KeywordsMODIS Leaf area index distribution Standardized Precipitation Index (SPI) Drought Yunnan
Unable to display preview. Download preview PDF.
This study was a part of the Project on “Building Effective Water Governance in the Asian Highlands” supported by Canada’s International Development Research Centre (IDRC), National Science Foundation of China, Grant No. 31270524 and the CGIAR research programs on ‘Climate change adaptation and mitigation’ (CRP6.4). We greatly thank the Center for Global Change Data Processing and Analysis in China for providing the satellite remote sensing data.
- Arnell NW (2008) Climate change and drought. In: López-Francos A (ed.), Drought management: scientific and technological innovations. Zaragoza: CIHEAM. pp 13–19. Available online: http://om.ciheam.org/om/pdf/a80/00800 414.pdf, accessed on January 4, 2016Google Scholar
- Brando PM, Nepstad DC, Davidson EA, et al. (2008) Drought effects on litterfall, wood production and belowground carbon cycling in an Amazon forest: results of a throughfall reduction experiment. Philosophical Transactions of Royal Society B Biological Science 363:1839–1848. https://doi.org/10.1098/rstb.2007.0031CrossRefGoogle Scholar
- Dutta D, Kundu A, Patel NR, et al. (2015) Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI). The Egypt Journal of Remote Sensing and Space Science 18(1):53–63. https://doi.org/10.1016/j.ejrs.2015.03.006CrossRefGoogle Scholar
- Farooq M, Hussain M, Wahid A, Siddique KHM (2012) Drought stress in plants: an overview. In: Aroca R (ed), Plant Responses to Drought Stress, 1st edn. Springer-Verlag Berlin Heidelberg. pp 1–33. https://doi.org/10.1007/978-3-642-32653-0_1Google Scholar
- Gosling SN, Arnell NW (2013) A global assessment of the impact of climate change on water scarcity. Climatic Change 134(1):371–385. https://doi.org/10.1007/s10584-013-0853-xGoogle Scholar
- IPCC (2014) Climate change 2014 synthesis report. Contribution of working group I, II and III to the fifth assessment report of the Intergovernmental panel of Climate Change. Geneva, Switzerland. p 151Google Scholar
- Jiang H (1980) Distributional features and zonal regularity of vegetation in Yunnan. Acta Botanica Yunnanica 2(2):142–151.Google Scholar
- McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In: Proceedings of the 8th Conference on Applied Climatology. Anaheim, CA: American Meteorological Society. pp 179–184.Google Scholar
- Palmer WC (1965) Metorological drought. Washington, DC, US. p 65.Google Scholar
- Spanner MA, Pierce LL, Peterson DL, Running SW (1990) Remote sensing of temperate coniferous forest leaf area index The influence of canopy closure, understory vegetation and background reflectance. International Journal of Remote Sensing 11(1):95–111. https://doi.org/10.1080/0143116900 8955002CrossRefGoogle Scholar
- Zhang P, Anderson B, Barlow M, et al. (2004) Climate-related vegetation characteristics derived from Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index and normalized difference vegetation index. Journal of Geophysical Research 109: D20105. https://doi.org/10.1029/2004JD004720CrossRefGoogle Scholar
- Zhang Q, Kobayashi Y, Alipalo MH, Zheng Y (2012) Drying up: What to do about droughts in the People’s Republic of China, with a case study from Guiyang Municipality, Guizhou Province. Asian Development Bank, Mandaluyong City, Philipines. p 68.Google Scholar
- Zheng D, Li B (2008) Study on the eco-geographical regional system of China. The Commercial Press, Beijing, China.Google Scholar