文献类型：会议论文

英文题名：A METHOD INTEGRATING GF-1 MULTI-SPECTRAL AND MODIS MULTI-TEMPORAL NDVI DATA FOR FOREST LAND COVER CLASSIFICATION

作者：Li, Zengyuan[1] Li, Xiaohong[1] Chen, Erxue[1] Li, Shiming[1]

第一作者：李增元

通信作者：Li, ZY[1]

机构：[1]Chinese Acad Forestry, Inst Forest Resources Informat Tech, Beijing, Peoples R China

会议论文集：36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

会议日期：JUL 10-15, 2016

会议地点：Beijing, PEOPLES R CHINA

语种：英文

外文关键词：GF-1 image; MODIS NDVI data; Random Forest; phenological features; forest land cover classification

年份：2016

摘要：In this paper a method was demonstrated that GF-1 multi-spectral and MODIS multi-temporal NDVI data were integrated for forest land cover classification. The test site is located in the central of the Xiaoxing'anling region in Heilongjiang province where covered the area of one scene of GF-1 image. The random forests algorithm was adopted to select the best features automatically which contains spectral, texture and shape features from GF-1 multi-spectral data and phenological features from multi-temporal MODIS NDVI data. A decision tree was used to supervise the classification result. Experimental results show that the overall classification accuracy and Kappa coefficient of the developed method combing multi-sources data can reach 89.46% and 0.874 respectively, with significant improvement compared with that using either GF-1 multi-spectral data or MODIS NDVI time series data alone, especially for the classification of evergreen forest.