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Land Cover Classification in Heihe River Basin with Time Series - MODIS NDVI Data

机译:Heihe River盆地土地覆盖分类与时间序列 - Modis NDVI数据

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Normalized Difference Vegetation Index (NDVI) is a very important vegetation index, which has been widely applied in research regarding global environmental and climatic change. In this work, 16-Day L3 Global 1km SIN Grid NDVI data sets in Heihe River Basin from MODIS vegetation index (VI) products (MOD13A2) during 2003-2005 are extracted and used for generating a one-year new NDVI data based on a simple three-point smoothing technique which can generally capture the annual feature of vegetation change. Then we obtain the independent component images by performing Independent Component Analysis (ICA) transform on the smoothing NDVI data as a feature extractor. Then a support vector machine (SVM) is utilized to construct classifiers based on the ICA-extracted new features for land cover classification and a land cover map of Heihe River Basin was obtained. At last, the accuracy assessment results prove that the classification framework proposed in this paper is efficient.
机译:归一化差异植被指数(NDVI)是一种非常重要的植被指数,已广泛应用于全球环境和气候变化的研究。在这项工作中,从Modis植被指数(VI)产品(MOD13A2)的黑河河流域16天L3全球1KM SIN网格NDVI数据集被提取,并用于基于a的一年新的NDVI数据生成一项新的NDVI数据简单的三点平滑技术,通常可以捕获植被变化的年度特征。然后,我们通过在将平滑NDVI数据上执行独立的分量分析(ICA)转换作为特征提取器来获得独立的组件图像。然后利用支持向量机(SVM)根据土地覆盖分类的ICA提取的新功能,获得了黑河流域的陆地覆盖图。最后,准确评估结果证明了本文提出的分类框架是有效的。

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