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利用面向对象方法提取湿地信息 被引量:29

THE OBJECT-ORIENTED METHOD FOR WETLAND INFORMATION EXTRACTION
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摘要 利用面向对象方法和ETM数据提取湿地信息。选取的试验区位于黄河源区,提取的湿地信息包括沼泽湿地和湖泊湿地。该方法通过图像分割、类型划分、特征选取与分类以及精度评价等4个步骤实现。试验结果表明,面向对象方法能够有效提取湿地信息,提取的图斑边界平滑,避免了椒盐状破碎图斑。该方法可以推广应用到其它地区,它在一定程度上能提高信息提取自动化程度,减少工作量,提高工作效率。 This paper deals with the utilization of the object - oriented method to extract wetland information from the Landsat ETM image. The test area is located in the source area of the Yellow River, and the wetland informa- tion extracted includes that of swamps and lakes. The object - oriented method consists of four steps, i.e. , image segmentation, class hierarchy building, feature choice and classification, and precision evaluation. The test results show that the object - oriented method can effectively extract wetland information with smooth borders and avoid the pepper shape effect. With some adjustment the method can be widely applied to other areas. It can raise the auto- mation degree of information extraction, reduce artificial workload and improve working efficiency.
出处 《国土资源遥感》 CSCD 2008年第1期79-82,I0005,共5页 Remote Sensing for Land & Resources
关键词 面向对象方法 ETM数据 湿地 信息提取 Object - oriented method ETM image Wetland Information extraction
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参考文献7

  • 1孙丹峰,林培.自适应模糊规则分类方法及在TM土地覆盖分类中的应用研究[J].国土资源遥感,2000,12(1):44-50. 被引量:3
  • 2Argialas D, Tzotsos A. Automatic Extraction of Physiographic Features and Alluvial Fans in Nevada, USA from Digital Elevation Models and Satellite Imagery Through Multiresolution Segmentation and Object - oriented Classification [ A ]. Proceedings of ASPRS 2006 Annual Conference[C]. Reno, Nevada, 2006.
  • 3Lennarts S P, Congalton R G. Classifying and Mapping Forest Cover Types Using Ikones Imagery in the Northeastern United States [ A ]. Proceedings of the ASPRS 2004 Annual Conference I C]. Denver, USA, 2004.
  • 4Richards J A. Remote Sensing and Digital Image Analysis: An In troduction[M]. Berlin: Springer, 1999.
  • 5Baatz M, et al. eCognition User Guide [ Z ]. Munich: Definiens Imaging GmbH, 2002.
  • 6Ballard A, Brown C M , Computer Vision[M]. Englewood Cliffs, NJ: Prentice - Hall Inc. 1982.
  • 7Van der Sande C J, et al. A Segmentation and Classification Approach of IKONOS - 2 Imagery for Land Cover Mapping to Assist flood Risk and Flood Damage Assessment [ J ]. International Journal of Applied Earth Observation and Geoinformation, 2003, (4) : 217 -229.

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