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Information extraction method on coastal wetland using TM data: A case study in Dongying, Shandong, China

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4 Author(s)
Kun Shang ; The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, CAS, Beijing, China ; Xiaohong Zhang ; Zhao Dong ; Xukai Zhang

As one of the most important ecosystems in the earth, wetlands need to be sufficiently protected from human interference. However, many wetlands in the world are degrading rapidly recent years, especially in China. The traditional method of monitoring wetlands by using field survey costs too much labor force and time. Nowadays, Remote Sensing data have been widely used in the researches of wetlands as the main data. This study was performed to propose an improved method of wetlands information extraction by using TM data. And an improved Maximum Likelihood method was proposed to obtain wetlands distribution more accurately with less noise. The wetlands distribution information and landscape parameters were extracted based on classification results of different years. Dongying City, located in the Yellow River delta, was chosen as the study area. The results showed the alteration of areas and landscape pattern of wetlands in Dongying from 2007 to 2010 and also revealed that this improved classification method could obtain wetlands distribution and landscape parameters effectively. The impact factors resulting in the wetlands alteration were also discussed to offer a reference for wetlands protection.

Published in:

Earth Observation and Remote Sensing Applications (EORSA), 2012 Second International Workshop on

Date of Conference:

8-11 June 2012