干旱气象

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三套 NDVI 长时间序列植被指数的对比——以玛曲为例

沙莎1郭铌1李耀辉1韩涛2   

  1. 1. 中国气象局兰州干旱气象研究所,甘肃省干旱气候变化与减灾重点实验室,中国气象局干旱气候变化与减灾重点实验室,甘肃 兰州 730020;
    2. 西北区域气候中心,甘肃 兰州 730020
  • 出版日期:2013-12-14 发布日期:2013-12-14
  • 作者简介:沙莎(1985 - ),女,汉族,辽宁沈阳人,助理工程师,硕士,主要从事 GIS、遥感的气象应用研究. E - mail:nuist_shasha@126. com
  • 基金资助:

    国家科技支撑计划(2009BAC53B02)、公益性行业(气象)科研专项项目(GYHY201006023)、科技部农业科技成果转化资金项目(2011GB24160005)共同资助

Contrast of the Long - term NDVI/MODIS,NDVI/GIMMS and NDVI/NSMC:a Case of Maqu

SHA Sha1GUO Ni1LI Yaohui1HAN Tao2   

  1. 1. Institute of Arid Meteorology,CMA/ Key Laboratory of Arid Climate Change and Reducing Disaster of Gansu Province/Key Open Laboratory of Arid Climate Change and Disaster Reduction of CMA,Lanzhou 730020,China;
    2. Regional Climate Center,Lanzhou 730020,China
  • Online:2013-12-14 Published:2013-12-14

摘要:

NDVI/MODIS、NDVI/GIMMS 和 NDVI/NSMC 是时间长度不同、空间分辨率相差甚远的3 套 ND-VI 数据集,如何集成应用这些不同时间长度、不同分辨率的数据进行相关研究,数据集间的比较是最基础的工作。本文以甘肃省甘南州玛曲县为例,用直方图、相关分析、趋势分析等方法研究了这3 套 NDVI产品数据集的相互关系。结果表明:1)NDVI/NSMC 与 NDVI/MODIS 的直方图具有类似的图像分布特征,但是 NDVI/MODIS 数据分布范围更大;2)3 套 NDVI 在数值上表现为 NDVI/MODIS > NDVI/GIMMS>NDVI/NSMC;3)3 套数据集空间图像特征一致,两两间均具有十分显著的空间相关性,其中 1 月份相对最弱,5、10 月份最强,三者相比 NDVI/NSMC 与 NDVI/MODIS 的空间相关性更强;4)1 ~3 月、5 ~8 月及年均的 NDVI/GIMMS 与 NDVI/NSMC 值存在显著的时间相关性,但两者逐年变化趋势存在较大差别,两者气候倾向率相差最大的高达 5 倍之多。NDVI/NSMC 数据集在处理过程中可能未进行大气订正及交叉定标,这是造成共同源的 NDVI/GIMMS 与 NDVI/NSMC 差异较大的重要原因。

关键词: NDVI/MODIS, NDVI/GIMMS, NDVI/NSMC, 长序列, 玛曲

Abstract:

NDVI/MODIS,NDVI/GIMMS and NDVI/NSMC are three NDVI datasets,due to their different lengths of time series and the giant difference in spatial resolution,the fundamental work should be done about comparing these datasets before applying these da-ta to carry out relevant research. This article took Maqu County of Gansu Province as an example,used the ways of histogram,correla-tion analysis,trend analysis and so on to research mutual relations of three NDVI datasets. The results are as follows:1)The histograms of NDVI/NSMC and NDVI/MODIS had the similar distribution feature,but the NDVI/ MODIS data distributed more wider than that of the former; 2)The numerical value of the three datasets were: NDVI/MODIS > NDVI/GIMMS > NDVI/NSMC; 3)Three datasets hadconsistent spatial image feature,there were very significant spatial correlation between any two of them,and in January the correlation was relatively weakest while in May and October it was strongest,among these datasets,NDVI/NSMC and NDVI/MODIS had more stronger spatial correlation; 4)The numerical value of NDVI/GIMMS and NDVI/NSMC from January to March,May to August and an-nual average values had remarkable temporal correlation,but both of them had big difference in yearly changed trend,and the differ-ence of the climate tendency rate of them reached up to 5 times. The dataset of NDVI/NSMC might miss the atmospheric correction andcross - calibration during the data processing,which was an important factor resulting in big difference for the homologous datasets ofNDVI/GIMMS and NDVI/NSMC.

Key words: NDVI/MODIS, NDVI/GIMMS, NDVI/NSMC, long - term series, Maqu County

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