In SOM algorithm it will create a map in output layer in which the cells are labeled class ID

e.g.1

2

3

etc.It’s curial for correctly classifying the data to make map.In this paper

we focus our interests on analyzing the map and the process of creating map to improve the SOM.We take three measures to change the map.We can classify the pure pixels and find the mixed pixels through the changed map.Furthermore

we can process the unclassified pixels from the view of linear spectral mixture analysis（LSMA）.Furthermore

we consider the two constraints: unnegative and the sum one

so the constraint spectral mixture analysis（CSMA） is applied in this paper.After CSMA

we assign the class ID to the endmember which has largest proportion in the mixed pixel.So

the spectral unmixing classification based on category proportion is performed to the unclassified pixels.Thus

we can get the extreme classification combining the former results.The experiment shows that the classification combined SOM with LSMA can get better classification results and well improve the classification accuracy.