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植被指数研究进展:从AVHRR-NDVI到MODIS-EVI
引用本文:王正兴,刘闯,HUETE Alfredo.植被指数研究进展:从AVHRR-NDVI到MODIS-EVI[J].生态学报,2003,23(5):979-987.
作者姓名:王正兴  刘闯  HUETE Alfredo
作者单位:1. 中国科学院地理科学与资源研究所全球变化信息研究中心,北京,100101
2. Department Soil, Water and Environmental Science, University of Arizona, Tucson, Arizona 85721 USA
基金项目:中国科学院知识创新工程资助项目 (CX1 0 G-E0 1 -0 7-0 1 )~~
摘    要:目前应用广泛的植被指数AVHRR—NDVI仍有一些缺陷。主要表现在:(1)在植被高覆盖区容易饱和。这除了红光通道就容易饱和外.主要是基于NIR/Red比值的NDVI算式本身存在容易饱和的缺陷;(2)没有考虑树冠背景对植被指数的影响;(3)NDVI的比值算式和最大值合成算法(MVC)确实消涂了某些内部和外部噪音。但最终的合成产品仍然有较多噪音;(4)MVC不能确保选择最小视角内的最佳像元。所有这此AVHRR—NDVI的局限性。在基于“中分辨率成像光谱仪(MODIS)”的“增强型植被指数(EVI)”产品中。都有不同程度改善。MODIS—EVI改善表现在:(1)大气校正包括大气分子、气溶胶、薄云、水汽和臭氧。而AVHRR—NDVI仅对瑞利散射和臭氧吸收做了校正;这样MODIS—EVI可以不采用基于比值的方法。因为比值算式是以植被指数饱和为代价来减少大气影响;(2)根据蓝光和红光对气溶胶散射存在差异的原理。采用“抗大气植被指数(ARVl)对残留气溶胶做进一步的处理;(3)采用“土壤调节植;波指数(SAVl)”减弱了树冠背景土壤变化对植被指数的影响;(4)综合ARVI和SAVI的理论基础。形成“增强型植被指数(EVI)”。它可以同时减少来自大气和土壤噪音的影响;(5)采用“限定视角内最大值合成法(CV—MVC)”。选择最小视角内的最佳像元。此外。目前正在试验的“双向反射分布函数(ERDF)合成法”。首先把不同视角换算为星下点像元反射值。然后采用CV—MVC合成。目的是进一步提高EVI对植被季节性变化的敏感性。总之。MODIS—EVI使植被指数与不同覆盖程度植被的线性关系得到明显改善。尤其在高覆盖区表现良好。

关 键 词:植被指数  AVHRR—NDVI  MODIS—EVI  覆盖程度  植被  植被生产力
文章编号:1000-0933(2003)05-0979-09
收稿时间:8/3/2002 12:00:00 AM
修稿时间:2003/3/20 0:00:00

From AVHRR-NDVI to MODIS-EVI: Advances in vegetation index research
WANG Zhengxing,LIU Chuang and HUETE Alfredo.From AVHRR-NDVI to MODIS-EVI: Advances in vegetation index research[J].Acta Ecologica Sinica,2003,23(5):979-987.
Authors:WANG Zhengxing  LIU Chuang and HUETE Alfredo
Institution:.Global Change Information and Research Center; Institute of Geographic Science and Natural Resources Research; Chinese Academy of Sciences; Beijing; China
Abstract:Global AVHRR-NDVI data sets have been widely applied to many fields from land cover change to the extraction of various biophysical vegetation parameters. Yet there still remain some limitations in the NDVI product: (1) NDVI saturates in well-vegetated areas, partly a result of saturation in the Red channel and partly due to the ratio-based NDVI equation; (2) The effect of canopy background on NDVI has not been considered; (3) The ratioing properties of the NDVI along with the Maximum Value Composite (MVC) procedure does remove some sources of internal and external noise, but there still remain significant noise in the final NDVI products; (4) The MVC cannot guarantee the selection of the clearest pixels and smallest view angles. All of these limitations are improved to some extent in the Enhanced Vegetation Index (EVI) product from the Moderate Resolution Imaging Spectroradiometer (MODIS). The MODIS-EVI has several advantages over the AVHRR-NDVI; (1) The MODIS atmosphere correction scheme includes the effect of atmospheric gases, aerosol, thin cirrus clouds, water vapor, and ozone, whereas there are only corrections for Rayleigh scattering and ozone absorption in the AVHRR-NDVI product. This reduces the need for ratio-based vegetation indices, such as the NDVI, that remove some atmospheric noise at the cost of saturation; (2) The influence of residual aerosol is removed by the Atmosphere Resistant Vegetation Index (ARVI), which is based on the difference of Red and Blue aerosol scattering; (3) The influence of the canopy background is reduced by the Soil Adjusted Vegetation Index (SAVI); (4) The concepts behind the ARVI and SAVI are coupled together to form the Enhanced Vegetation Index (EVI), which removes both atmosphere and background noise simultaneously and; (5) A Constrained-View Maximum Value Composite (CV-MVC) algorithm is applied to select the clearest pixels with smallest view angles and a BRDF compositing scheme is being tested to further improve the seasonal depiction of vegetation dynamics. The MODIS-EVI has improved its linearity with vegetation, particularly in well-vegetated regions.
Keywords:AVHRR-NDVI  MODIS  enhanced vegetation index  EVI
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