Multi-source data complex classification of grassland in Inner Mongolia based on MODIS EVI - ZHAO Bing-ru; MA Long (浙江大学学报. 农业与生命科学版, 2007)
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.