任宏昌,张祖强,史学丽.2003—2009年中国地区叶面积指数变化特征分析.气象科学,,(): REN Hongchang,ZHANG Zuqiang,SHI Xueli.Analysis of Leaf Area Index Variations over China during 2003-2009.Journal of the Meteorological Sciences,,():
2003—2009年中国地区叶面积指数变化特征分析
Analysis of Leaf Area Index Variations over China during 2003-2009
投稿时间:2013-03-21  修订日期:2013-05-22
DOI:10.3969/2013jms.0055
中文关键词:  叶面积指数  MODIS  林区  气候相关
英文关键词:LAI  MODIS  Forest region  Climate correlation
基金项目:公益性行业(气象)科研专项(GYHY201106014);林业专项(200804001);国家高新技术研究发展计划(863计划)项目(2009AA122005)
作者单位E-mail
任宏昌 南京信息工程大学, 南京 210044  
张祖强 江苏省气象局, 南京 210009 zhangzq@cma.gov.cn 
史学丽 国家气候中心, 北京 100081  
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中文摘要:
      为了解2003—2009年中国的叶面积指数(Leaf Area Index,LAI)变化特征,以及不同数据产品的差别,利用基于MODIS数据反演的3组LAI 产品,比较分析了中国地区LAI 的时空变化特征及其与气候因子的相关。结果表明,3组数据具有总体一致的变化特点,增长区主要位于东北大兴安岭、华北、华中和西南等地;减少区则位于四川盆地、江南以及华南东部;但在云贵川和青藏高原东南部等地有明显差异。在量值上,中科院地理所反演的LAI(LAI1)总体比NASA反演的LAI(LAI2)和北京师范大学反演的LAI(LAI3)偏小,它们在中国常绿阔叶林区的差别可达1.0以上。LAI1与同期降水和气温都有显著的相关,相关系数的空间分布一致,但LAI1的相关系数比LAI3和LAI2偏低。3组数据的差异主要与采用的遥感源数据和反演方法等不同有关。尽管不同LAI 数据产品局域和量值差异对定量分析有一定影响,但是它们在时空变化及与气候条件相关等方面的一致性证明了在气候及气候变化研究中的可用性。
英文摘要:
      By using three LAI products based on MODIS sensors, the spatial and temporal variations of LAI over China during 2003-2009 are analyzed, as well as its correlations with surface air temperature and precipitation. The results show that the LAI in the different datasets have consistent spatial patterns in seasonal evolution and linear trends. The LAI has increased in the Daxinganling Mts. of Northeastern China, North China, Central China and southwest China, and decreased in the Sichuan Basin, regions south of the Yangtze River Valley, and east of South China. Distinct regional inconsistency is found mainly in the Yunnan, Guizhou and Sichuan provinces and southeast Tibetan plateau. The LAI calculated by China Academy of Science (LAI1) is generally smaller than those by NASA(LAI2) and Beijing Normal University (LAI3), with differences larger than 1.0 in the evergreen broadleaf forest region. For the relationships with climate factors, LAI1 show significant correlation with precipitation and surface air temperature. The correlation coefficients show similar spatial pattern with differences on magnitude. The discrepancies among them are mainly due to the different data sources and retrieval methods. The consistency and similarity among the three datasets show their availabilities in qualitative applications though the differences on magnitude and regional features may have impacts on quantitative analyses.
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