The problems of pixel mixture are the main obstacles of quantitative remote sensing. In this paper

we classify the problems of pixel mixture into two groups: mixture in class and mixture between classes. and focus our study on the former. The key problem of subpixel unmixing is to determine the component spectra. Many methods have been developed to determine the component spectra. However

most of these methods base on the assumption that pure component signatures can be found from the image itself. Obviously

this assumption is not correct for pixel mixture in class. In this paper

a new method to combine hyperspectral and multiangular data together to retrieve subpixel information is introduced. This method begins from the definition of the component signatures and tries to get a priori information from the data itself

so it′s more likely to acquire the "pure" endmember spectra and the subpixel information extracted by this method is more reliable than some other ways. To demonstrate the result of this method

we use BOREAS （the Boreal Ecosystem-Atmosphere Study） data to extract component signatures and the corresponding areal proportions in SSA（Southern Study Area）OJP（Old Jack Pine）site. The result is encouraging.