长江科学院院报 ›› 2017, Vol. 34 ›› Issue (5): 141-145.DOI: 10.11988/ckyyb.20160208

• 信息技术应用 • 上一篇    下一篇

GIMMS和MODIS在黄土高原地区植被监测中的应用

邵霄怡1, 李奇虎2, 王书民1   

  1. 1.中国地震局 地震预测研究所,北京 100036;
    2.西安科技大学 测绘与技术学院,西安 710054
  • 收稿日期:2016-03-10 修回日期:2016-06-07 出版日期:2017-05-01 发布日期:2017-05-17
  • 作者简介:邵霄怡(1993-),女,陕西西安人,硕士研究生,主要从事遥感、测绘与地理信息方面的工作,(电话)18310548977(电子信箱)529674420@qq.com。
  • 基金资助:
    中国地震局地震预测研究所基本科研业务经费专项项目(2014IES0203)

Application of GIMMS and MODIS to Vegetation Monitoring in the Loess Plateau

SHAO Xiao-yi1, LI Qi-hu2, WANG Shu-min1   

  1. 1.Institute of Earthquake Science, China Earthquake Administration, Beijing 100036, China;
    2.School of Geometrics, Xi’an University of Science & Technology, Xi’an 710054, China
  • Received:2016-03-10 Revised:2016-06-07 Online:2017-05-01 Published:2017-05-17

摘要: 黄土高原地区生态环境脆弱,受季风气候的影响,四季分明,植被变化明显,为比较不同遥感数据的一致性提供了很好的试验场所。利用2001—2006年GIMMS NDVI和2001—2014年MODIS NDVI数据,分析了黄土高原地区植被变化情况,并从2种数据的空间分布特征、季节变化和时间分布特征3方面在黄土高原地区的差异进行了分析。结果表明:2种数据都反映了黄土高原地区西北部植被覆盖稀少,东南部植被覆盖较好的特点,MODIS数据在探测植被差异变化上较GIMMS数据敏感一些;从趋势上看植被指数逐年增加,秋季增加最快,表明近年来黄土高原地区植被恢复工作取得了明显的效果。与GIMMS数据相比,MODIS数据更适合于反映黄土高原地区植被的空间分布。

关键词: 归一化植被指数, 黄土高原, GIMMS, MODIS, 相关系数, 时间序列对比分析

Abstract: Loess Plateau is featured with fragile ecological environment. Affected by monsoon climate, it has obvious distinction among four seasons and apparent vegetation changes, which offer a good testing ground for researching the consistency of different remote sensing data. According to the Normalized Difference Vegetation Index (NDVI) derived from GIMMS in 2001-2006 and from MODIS in 2001-2014, we analyzed the variations of vegetation in the loess plateau. And furthermore we investigated the differences between the two data in aspects of spatial distribution, seasonal and annual variations of vegetation in the loess plateau of Shaanxi Province. Results suggest that data obtained by the two methods both reflect the scarce coverage in the northwest and good coverage in the southeast of the loess plateau. What’s more, MODIS data is sensitive to the variation of vegetation differences. In terms of the trend, vegetation index increased year by year, and the most rapid increment was in autumn, indicating that the vegetation restoration work in recent years has achieved remarkable result. Compared with GIMMS, MODIS is more suitable for reflecting the spatial distribution of vegetation cover in the loess plateau.

Key words: NDVI, loess plateau, GIMMS, MODIS, coefficient of correlation, comparative analysis of time series data

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