基于MODIS EVI的内蒙古草地多源信息综合分类研究

利用遥感数据与非遥感数据相结合的方法对内蒙古草地进行分类研究.以MODIS EVI(MODIS增强型植被指数)数据为基础,计算得到MODIS EVI月度数据,分剐取其一、二、三主成分作为分类的前3个参数;引入研究区域同期的气温、降水、生物温度及DEM(数字高程)数据,通过克里金插值、主成分变换、重采样等方法确定分类的第4、第5个参数.在此基础上,应用ISODATA技术对草地进行分类.结果表明,该分类结果能够提供比AVHRR NDVI(AVHRR归一化植被指数)和MODIS NDVI(MODIS归一化植被指数)更丰富的分类信息,可以清晰识别到5大草地类,对草甸草原、典型草原和荒漠草原可以进一步识别到草地亚类.因此,MODIS EVI数据与非遥感数据结合的多源信息综合分类能提高草地分类的精度.

Multi-source data complex classification of grassland in Inner Mongolia based on MODIS EVI

The grassland in Inner Mongolia was classified using the method of integrating remote sensing data with non-remote sensing data.Based on daily MODIS enhanced vegetation index(EVI),monthly MODIS EVI was calculated,and was analyzed by principal component analysis(PCA) further,whose first three components were inputted as the first three parameters for classification.The fourth,fifth classification parameters were obtained by applying kriging interpolation,principal component analysis,and data resampling to temperature data,precipitation data,biotemperature data and DEM data.Based on these five parameters,the Inner Mongolia grassland was classified by using ISODATA.The results showed that the grassland classification of MODIS EVI provided more information than that of AVHRR NDVI and MODIS NDVI.This method could identify five classes of Inner Mongolia grassland clearly,and sub-classes of temperate meadow,temperate steppe and temperate desert steppe were also distinguished.Therefore the complex classification method of multi-source data integrating the MODIS EVI with non-remote sensing data can improved the precision of grassland classification obviously.