| Research on extracting method of micro-scale remote sensing information combination and application in coastal zone |
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| 作者姓名： | YANGXiaomei ZHOUChenghu GONGJianming GAOZhenyu |
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| 作者单位： | Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China |
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| 基金项目： | The “973” Project of China under contract No 2006CB701305;;the “863” Project of China under contract No2009AA12Z148;;the National Natural Science Foundation of China under contract No 40971224 |
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| 摘 要： | 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 cannot meet the needs of this development trend. The paper attempts to present an information extraction approach in terms of image segmentation based on an object-oriented algorithm for high-resolution remote sensing images. An aim of the author’ research is to establis...
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| 关 键 词： | 提取方法 沿海地区 遥感信息 图像分割算法 海水养殖池塘 应用 微型 数据挖掘技术 |
| 收稿时间： | 2008/5/27 0:00:00 |
| 修稿时间： | 2008/10/16 0:00:00 |
Research on extracting method of micro-scale remote sensing information combination and application in coastal zone |
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| YANGXiaomei,ZHOUChenghu,GONGJianming,GAOZhenyu.Research on extracting method of micro-scale remote sensing information combination and application in coastal zone[J].Acta Oceanologica Sinica,2009,28(5):30-38. |
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| Authors: | YANG Xiaomei ZHOU Chenghu GONG Jianming and GAO Zhenyu |
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| Institution: | Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China |
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| 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 cannot meet the needs of this development trend.The paper attempts to present an information extraction approach in terms of image segmentation based on an object-oriented algorithm for high-resolution remote sensing images. An aim of the author' research is to establish an identification system of "pixel-primitive-object". Through extraction and combination of micro-scale coastal zone features, some objects are classified or recognized, e.g., tidal flat, water line, sea wall, and mariculture pond. Firstly, the authors extract various internal features of relatively homogeneous primitive objects using an image segmentation algorithm based on both spectral and shape information. Secondly, the features of those primitives are analyzed to ascertain an optimal object by adopting certain feature rules. The results from this research indicate that our model is practical to realize and the extraction accuracy of the coastal information is significantly improved as compared with the traditional approaches. Therefore, this study provides a potential way to serve the author' highly dynamic coastal zones for monitoring,management, development and utilization. |
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| Keywords: | Object-oriented Image Segmentation Coastal Zone Information Extraction |
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