Integration of NOAA-AVHRR data and geographical factors for China vegetation classification

Integration of remotely-sensed and non-remotely-sensed information becomes an effective approach for vegetation classification. In this paper, vegetation in China is comprehensively classified by integration of NOAA-AVHRR data and geographical factors, such as temperature, precipitation and DEM. The procedure of comprehensive vegetation classification is chiefly composed of four steps: feature selection of NOAA data, creation of geographic information image, data integration and image comprehensive classification. Precision test and error analysis indicate a higher precision of the classification result.