Land Cover Classification Based on Typical Indices Combinations of MODIS NDVI Time Series
MODIS data has a high temporal and spectral resolution,and it can provide vegetation indices of high quality.By using MODIS NDVI time series with 250 m spatial resolution which were composite of 16 days in 2005,this work chose annual modulus of vector,maximum and minimum NDVI three indices to do classification.Training and validation samples were selected based on TM images and the 1:1,000,000 vegetation atlas of China.Then the land coverage map was generated using maximum likelihood classification (MLC) method.After post-classification process of the original classification result,the final land classification map of Keerqin sandy land was got in the end.The classification accuracy was assessed using validation samples and the result indicates that 250 m MODIS NDVI time series has advantage and potential in regional land coverage mapping.Also the classification method used in the paper could not only reduce the data amount and quicken the speed of classification,but also could reduce the disturbance of other invalidation information to classification and get better classification accuracy.
MODIS NDVI time series land cover classification modulus of vector maximum minimum
Du Zitao Zhan Yulin Wang Changyao
The State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing Applications,Chinese Academy of Sciences,Beijing,China,100101
国际会议
第16届国际地理信息科学与技术大会(16th International Conference on GeoInformatics and the Joint Conference)
广州
英文
2008-06-28（万方平台首次上网日期，不代表论文的发表时间）