Abstract:

Utilize 7 Arctic SAR images and level ice thickness from 6th Arctic Survey，calculate texture feature through gray level co-occurrence matrix(GLCM)，confirm suitable GLCM parameters for thickness retrieval，analyze the relationship between sea-ice thickness and texture feature，validate the possibility of sea-ice thickness retrieval from texture feature. Then confirm fitting equation depending on the most suitable texture feature. When validated，the sea-ice thickness retrieval from the empirical equation agrees well with the in-situ data，the average relative error is 13.7%. This value is smaller compared with the commonly used method that only depend on backscattering coefficient，confirm the role of texture feature in sea-ice thickness retrieval.

Key words: Arctic, sea-ice thickness, gray level co-occurrence matrix(GLCM), texture feature