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Spatio-temporal pattern of urban land cover evolvement with urban renewal and expansion in Shanghai based on mixed-pixel classification for remote sensing imagery

机译:基于遥感影像混合像素分类的上海城市土地覆盖随更新和扩展的时空格局

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摘要

Research into pixel unmixing in remote sensing imagery led to the development of soft classification methods. In this article, we propose a possibilistic c repulsive medoids (PCRMdd) clustering algorithm which attempts to find c repulsive medoids as a minimal solution of a particular objective function. The PCRMdd algorithm is applied to predict the proportion of each land use class within a single pixel, and generate a set of endmember fraction images. The clustering results obtained on multi-temporal Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images of Shanghai city in China reveal the spatio-temporal pattern of Shanghai land use evolvement and urban land spatial sprawl in course of urbanization from 1989 to 2002. The spatial pattern of land use transformation with urban renewal and expansion indicates the urban land use structure is gradually optimized during vigorous urban renewal and large-scale development of Pudong area, which will have an active influence on improving urban space landscape and enhancing the quality of the ecological environment. In addition, accuracy analysis demonstrates that PCRMdd represents a robust and effective tool for mixed-pixel classification on remote sensing imagery to obtain reliable soft classification results and endmember spectral information in a noisy environment.
机译:对遥感图像像素分解的研究导致了软分类方法的发展。在本文中,我们提出了一种可能的c排斥类固醇(PCRMdd)聚类算法,该算法试图找到c排斥性类固醇作为特定目标函数的最小解。 PCRMdd算法用于预测单个像素内每个土地利用类别的比例,并生成一组端成员分数图像。在中国上海市的多时态Landsat专题地图(TM)/ Enhanced thematic Mapper Plus(ETM +)影像上获得的聚类结果揭示了1989年以来上海城市化过程中上海土地利用演变的时空格局和城市土地空间蔓延到2002年。随着城市更新和扩张的土地利用变化的空间格局表明,在浦东地区大力进行城市更新和大规模发展的过程中,城市土地利用结构逐渐优化,这将对改善城市空间景观和增强土地利用产生积极影响。生态环境的质量。此外,准确性分析表明,PCRMdd代表了一种强大而有效的工具,可用于在遥感影像上进行混合像素分类,从而在嘈杂的环境中获得可靠的软分类结果和端成员光谱信息。

著录项

  • 来源
    《International journal of remote sensing》 |2010年第24期|p.6095-6114|共20页
  • 作者单位

    Key Laboratory of Wave Scattering and Remote Sensing Information, Ministry of Education, Fudan University, Shanghai 200433, PR China,State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, PR China;

    Department of Geography, Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200062, PR China;

    State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, PR China;

    Department of Geography, Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200062, PR China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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