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利用NOAA-AVHRR数据分析1982-2001年间中国植被的动态变化

机译:利用NOAA-AVHRR数据分析1982-2001年间中国植被的动态变化

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摘要

The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period,China's vegetation cover had tended to increase, compared to the early 1980s; mean annual NDVI increased 3.8%. The agricultural regions (Henan, Hebei, Anhui and Shandong) and the west of China are marked by an increase, while the eastern coastal regions are marked by a decrease. The correlation between monthly NDVI and monthly precipitation/temperature in the period 1982 to 2001 is significantly positive ( R2 =0.80, R2=0.84); indicating the close coupling between climate conditions (precipitation and temperature) and land surface response patterns over China. Examination of NDVI time series reveals two periods: (1) 1982-1989, marked by low values below average NDVI and persistence of drought with a signature large-scale drought during the 1982 and 1989; and (2) 1990-2001, marked by a wetter trend with region-wide high values above average NDVI and a maximum level occurring in 1994 and 1998.
机译:作者从NOAA / AVHRR土地数据集获得了归一化差异植被指数(NDVI),以8公里和15天的间隔,调查中国1982年至2001年期间的植被变化。然后,GIS是用于检查中国降水与归一化差异植被指数(NDVI)之间的关系,并将NDVI的价值作为干旱监测的工具。结果表明,与20世纪80年代初期相比,中国的植被封面趋于增加;平均年度NDVI增加3.8%。农业地区(河南,河北,安徽和山东)和中国西部都标志着增加,而东部沿海地区则以减少为标志。 1982年至2001期间每月NDVI和月度降水/温度之间的相关性显着阳性(R2 = 0.80,R2 = 0.84);表明气候条件(降水温度)与中国土地面应答模式的紧密耦合。对NDVI时间序列的检查显示了两个时期:(1)1982-1989,标志着低于平均值的低值,1982年和1989年期间与签名大型干旱的干旱持续存在; (2)1990-2001,由潮湿的趋势标记,高于平均NDVI的高价值和1994年和1998年的最大水平。

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  • 来源
    《地球空间信息科学学报(英文版)》 |2009年第2期|146-153|共8页
  • 作者单位

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road,Wuhan 430079, China;

    General Organizations of Remote Sensing GORS, P. O. Box 12586, Damascus, Syria;

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  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类 P237.1;
  • 关键词

  • 入库时间 2022-08-19 04:09:42

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