The Identification of Grassland Types in the Source Region of the Yarlung Zangbo River Based on Spectral Features
SUN Ming1,2, SHEN Wei-shou1, XIE Min3, LI Hai-dong1, GAO Fei4
1. Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, China; 2. Institute of Meteorological Disaster Mitigation of Guangxi/Remote Sensing Applying and Experiment Base of National Meteorological Satellite Center, Nanning 530022, China; 3. Guangxi Climate Center, Nanning 530022, China; 4. Qinhuai River Hydraulic Management Agency of Jiangsu Province, Nanjing 210001, China
Abstract：With the Landsat5 TM images of the source region of the Yarlung Zangbo River as the datum source,according to the different features of spectral combination of the grassland,and in combination with the 1:1 000 000 vegetation type map as well as DEM and NDVI data,the authors set up the rules of grass identification and conducted researches on grass recognition based on decision tree classification. Some conclusions have been reached: 1 Due to difference in habitat types,good results of identifying grass can only be achieved by using different spectral combination features; 2 Compared with traditional supervised classification,the decision tree classification based on spectral combination features has higher precision of identification,the overall classification accuracy has been improved by 15.4% and the Kappa coefficient has been increased by 0.225; 3 In the region with elevation ranging from 4 400 m to 5 000 m,the grassland area of Orinus thoroldii is the largest,followed by the mixed meadow of Kobresia humilis and Kobresia pygmaea,and then by the bush of Caragana versicolor and Potentilla fruticos, with Kobresia littledalei having the smallest area.
孙明, 沈渭寿, 谢敏, 李海东, 高菲. 基于光谱特征的雅鲁藏布江源区草地类型识别[J]. 国土资源遥感, 2012, 24(1): 83-89.
SUN Ming, SHEN Wei-shou, XIE Min, LI Hai-dong, GAO Fei. The Identification of Grassland Types in the Source Region of the Yarlung Zangbo River Based on Spectral Features. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(1): 83-89.