国土资源遥感Issue(1)：66-72,7.
变端元混合像元分解冬小麦种植面积测量方法
The Application of the Dynamic Endmember Linear Spectral Unmixing Model to Winter Wheat Area Estimation
摘要
Abstract
Linear spectral unmixing (LSU)is the most common method for solving mixed pixel problem;nevertheless, if the number of the pixels' endmember is regarded as unchangeable, the traditional pixel unmixing algorithm cannot attain a good result. In the light of the characteristic that pixels usually have the same composition as their neighboring pixels, the authors proposed a grid - based dynamic endmember linear spectral unmixing (DELSU) model. The land cover classification experiment was conducted with the adoption of the Landsat TM image as the experimental data. The abundance map of winter wheat derived from the visual interpretation of the QuickBird image was used for accuracy evaluation. The experimental results show that the use of the DELSU model could extract the area of winter wheat at a precision higher than that of the traditional maximum likelihood method and the LSU model. This model absorbs the traditional classification advantages and improves the measurement accuracy of the target features. As an improved method of LSU, DEISU is also applicable to the measurement of other land use/cover types.关键词
DELSU/LSU/格网/冬小麦/遥感Key words
DELSU/ LSU/ Grid/ Winter wheat/ Remote sensing分类
信息技术与安全科学引用本文复制引用
赵莲,张锦水,胡潭高,陈联裙,李乐..变端元混合像元分解冬小麦种植面积测量方法[J].国土资源遥感,2011,(1):66-72,7.基金项目
农业部资源遥感与数字农业重点实验室开放基金项目(编号:RDA0807)和国家高技术研究发展计划资助项目(编号:2006AA120103、2006AA120101)共同资助. （编号:RDA0807）
