This paper presented the research on land cover classification in area to the north-west of Beijing based on MODIS 16-day NDVI and 8-day LST time series datasets in 2002, 1:50000 DEM and some ancillary data. We first selected a land use/land cover classification system suitable to MODIS remote sensing data, the classification system was built based on remote sensing data after comparing and summarizing the features of different remote sensing data. Secondly, in order to improve the classification accuracy, we performed a PCA transform on the MODIS NDVI time series data to remove noises, and selected the first four components as the basic land cover classification data. Finally, combined with MODIS LST data, DEM and other ancillary data of study area, we applied fuzzy K-means non-supervised classifier to get the land cover automatic classification in area to the north-west of Beijing. After post-classification process of the original classification result, the last land cover classification map of area to the north-west of Beijing in 2002 was got. Compared with the manual interpretation classification result based on the ETM+ remote sensing data, we had a classification accuracy evaluation about MODIS data. The final classification result showed that the 250m MODIS NDVI time series data and the classification method used in the paper not only can suit to large-scale land cover classification, but also can have better classification accuracy. Based on the classification result of area to the north-west of Beijing, we had a statistic about the area of seven land cover types and analyzed their geographic distribution.