Improving MODIS sea ice detectability using gray level co-occurrence matrix texture analysis method: A case study in the Bohai Sea
An effective methodology for Bohai Sea ice detection based on gray level co-occurrence matrix (GLCM) texture analysis is proposed using MODIS 250m imagery. The method determines texture measures for sea ice extraction by analyzing the discrepancy of textural features between sea ice and sea water. Sea ice extent and outer edge are recognized accurately by texture segmentation owing to significant differences in texture statistical features between ice and water. The texture analysis method can properly eliminate perturbations on sea ice extraction due to suspended sediment. It effectively solves the problem of spectral confusion and sea ice misassignment in the conventional gray-threshold segmentation and ratio-threshold segmentation methods. The method eliminates the need for threshold range setting for sea ice segmentation. Taking the Bohai Sea as an example, the results of the proposed method are validated using co-temporal HJ1B-CCD 30m imagery by visual interpretation, and the accuracy of the method are evaluated using confusion matrix. The results show that the proposed method is superior and more reliable for sea ice detection compared to conventional methods, providing an ideal tool for precise sea ice extraction.
sea ice detection texture analysis bohai sea glcm modis 250m imagery