The Application of the Dynamic Endmember Linear Spectral Unmixing Model to Winter Wheat Area Estimation

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,DELSU is also applicable to the measurement of other land use/cover types.