海岸带遥感微尺度信息及其组合挖掘提取和方法应用研究

杨晓梅; 龚剑明; 高振宇

海岸带遥感微尺度信息及其组合挖掘提取和方法应用研究

中国科学院地理科学与资源研究所, 资源与环境信息系统国家重点实验室, 北京, 100101

基金项目: 国家“八六三”项目(2009AA12Z148);资源与环境信息系统国家重点实验室自主创新团队计划(088RA400SA)

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出版历程
- 收稿日期: 2009-01-05
- 修回日期: 2009-03-09

The research on extracting method of microscale remote sensing information combination and application in coastal zone

State Key Laboratory of Resource and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

摘要

摘要: 基于海岸带高分辨率信息需求理论支持下的信息挖掘技术,面对我国海岸带可持续发展的需求,以中高分辨率遥感影像为数据源,以滩涂、水边线、海堤、养殖场等海岸带地物为专题信息挖掘提取实例,建立了"像元→基元→目标"的识别方法体系,针对面向对象的信息提取分析方法进行研究。即首先通过采用光谱和形状相结合的分割算法来获取内部特征相对均一的一系列基元对象,再通过对基元对象的典型特征进行分析和判别来实现目标提取。结果表明,该方法是可行的,它提高了遥感影像信息的识别精度,为动态性很强的海岸带地物信息挖掘提取提供了研究思路,在海岸带监测、管理、开发和利用,编制现实性很强的海岸带专题图等应用领域展现了该研究示例的科学性和实际意义。
- 面向对象 /
- 图像分割 /
- 海岸带 /
- 信息提取
Abstract: Due to the need of rapid and sustainable development in China's coastal zones, the high-resolution information theory using data mining technology becomes an urgent research focus.However, the traditional pixel-based image analysis methods cannotmeet the needs of this development trend.Attempt is to present an information extraction approach in terms of image segmentation based on an object-orientedal-gorithm for high-resolution remote sensing images.The aim of research is to establish an identification system of "pixel-primitive-object".Through extraction and combination of microscale coastal zone features, some objects are classified or recognized, e.g., beach, coast line, sea wall, and mariculture pond.First, various internal characteristics of relatively homogeneous primitive objects are extracted using an image segmentation algorithm based on both spectral and shape information.Second, the features of those primitives are analyzed to ascertain an optimal object by adopting certain feature rules.Results indicate that the model is practical to realize and the extraction accuracy of the coastal information is significantly improved compared with the traditional approaches.Therefore, this model provides a potential way to serve highly dynamic coastal zones for monitoring, management, development and utilization.
- object-oriented /
- image segmentation /
- coastal zone /
- information extraction

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