Study on Fuzzy DTCC Method for River Main-Stream Interpretation from Remote Sensing Image

• Published in: 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM) pp. 1 - 4
• Main Authors: Han, Lin, Zhang, Yanning, She, Hongwei, Liu, Xuegong, Chen, Liang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-09-2010
• Subjects: Correlation; Earth; Floods; Heuristic algorithms; Remote sensing; Rivers; Satellites
• ISBN: 1424437083; 9781424437085
• ISSN: 2161-9646
• DOI: 10.1109/WICOM.2010.5600671

Yellow River is well known as sediment-laden river in the world with main-stream quickly change in its lower channel, so main-stream should be understood timely at flood season. Remote sensing is a primary approach to get main-stream information timely, however it has still some difficulties in interpreting it on image. DTCC (Dynamic Transmission Cross-Correlation) algorithm has been successfully described river flows with direction and continuity, as well as its surface phenomena having similarity alone flow direction. However, with water flow uncertainty similarity and the suboptimal path in flow direction, the DTCC interpretation results have some errors in some reaches. In this paper, a Fuzzy Dynamic Transmission Cross-correlation (FDTC) algorithm was proposed to interpret the river main-stream information based on fuzzy evaluation to flow similarity and fuzzy comprehensive selection in flow direction. The algorithm was applied on TM image in the lower of Yellow River and the results show that the FDTC method has an obviously improvement on main-stream interpretation.