基于MODIS遥感数据的混合像元分解技术研究和应用

Pixel Unmixing Technology of MODIS Remote Sensing Data

使用郑州市MODIS(Moderate-Resolution Imaging Spectroradiometer)遥感数据,运用线性混合模型,对MODIS遥感数据进行混合像元分解技术研究。探讨了MODIS遥感数据的预处理、线性光谱分解模型、图像端元组分反射率的求取方法。把结果与分辨率较高的Landsat ETM+图像分类结果进行对比,并根据得到的均方根误差(RMS;Root Mean Square)进行分析表明,利用这种像元分解方法得到的结果较为理想,MODIS数据可以有效地应用于遥感动态监测和土地覆盖分类研究。

MODIS（ Moderate-Resolution Imaging Spectroradiometer） remote sensing data have higher radiometric sensitivity ,but its lower spatial resolution always causes the pixel＇s impurity, normal classification methods of land cover can not solve this problem. In order to achieve the classification of land cover a line spectral mixture model was used in MODIS data pixel unmixing of Zhengzhou area. The preprocessing of MODIS data, line spectral mixture model （LSMM）, and methods for solving image end-member＇s reflectance were also discussed. The classification result was compared with the class map derived from Landsat ETM ＋ data. The RMS shows that the pixel unmixing method has good resuits and the MODIS data can be effectively applied to remote sensing dynamic monitoring, and land cover classification.