海岸线遥感信息提取的元胞自动机方法及其应用

从遥感资料中准确提取海岸线信息,是海岛海岸带遥感调查与海岸带综合管理的重要内容。为了对多类型海岸线进行准确提取,基于"自下而上"演化的元胞自动机方法,结合遥感图像方向信息权重,构建了一种新的岸线提取算法,并在Matlab环境下开发实现包括均值平滑、海陆分离、离散地物去除和目标追踪的功能。以Landsat ETM+遥感影像作为数据源,分别对人工海岸上海市长兴岛-横沙岛和淤泥质海岸上海市崇明东滩岸线进行了检测,验证了该岸线信息提取的元胞自动机算法。研究表明,基于元胞自动机的岸线提取方法,能够以较高精度提取人工海岸和淤泥质海岸的岸线信息。

Cellular automata approach to extract shoreline from remote sensing imageries and its application

Extraction shoreline information from remotely sensed imagery is important for islands investigation With remote sensing and the coastal comprehensive management. In order to accurately extract the information of shorelines,a new algorithm was developed based on a "bottom-up" approach cellular automata (CA) by considering the direction information of images. The algorithm was developed under a Matlab environment,which includes functions such as mean smooth,land/water segmentation,discrete objects removal,and shoreline tracing.Using the proposed algorithm,the shorelines of an artificially coast at the Changxing-Hengsha islands of Shanghai and a muddy coast at Chongming Dongtan of Shanghai were extracted from Landsat ETM+ images.The results demonstrate that the CA based shoreline extractor can accurately detect shoreline information of different coast types (e.g.artificially coast and muddy coast) from remote sensing images.