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Utilizing image texture to detect land-cover change in Mediterranean coastal wetlands

机译:利用图像纹理检测地中海沿岸湿地的土地覆盖变化

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摘要

Land-use/cover change dynamics were investigated in a Mediterranean coastal wetland. Change Vector Analysis (CVA) without and with image texture derived from the co-occurrence matrix and variogram were evaluated for detecting land-use/cover change. Three Landsat Thematic Mapper (TM) scenes recorded on July 1985, 1993 and 2005 were used, minimizing change detection error caused by seasonal differences. Images were geometrically, atmospherically and radiometri-cally corrected. CVA without and with texture measures were implemented and assessed using reference images generated by object-based supervised classification. These outputs were used for cross-classification to determine the 'from-to' change used to compare between techniques. The Landsat TM image bands together with the variogram yielded the most accurate change detection results, with Kappa statistics of 0.7619 and 0.7637 for the 1985-1993 and 1993-2005 image pairs, respectively.
机译:在地中海沿岸的湿地中调查了土地利用/土地覆盖变化的动态。为评估土地利用/土地覆被变化,评估了不包含和同时出现自共同矩阵和变异函数得出的图像纹理的变化矢量分析(CVA)。使用了三个分别于1985年7月,1993年和2005年记录的Landsat Thematic Mapper(TM)场景,最大程度地减少了由季节差异引起的变化检测误差。对图像进行了几何,大气和放射线校正。使用基于对象的监督分类生成的参考图像来实施和评估不带纹理措施和带纹理措施的CVA。这些输出用于交叉分类,以确定用于比较各种技术的“从-到”更改。 Landsat TM图像带和变异函数得出的变化检测结果最准确,1985-1993年和1993-2005年图像对的Kappa统计值分别为0.7619和0.7637。

著录项

  • 来源
    《International journal of remote sensing》 |2010年第12期|P.2793-2815|共23页
  • 作者单位

    Department of Landscape Architecture, Cukurova University, Adana, Turkey;

    rnDepartment of Landscape Architecture, Cukurova University, Adana, Turkey;

    rnSchool of Geography, University of Southampton, Highfield, Southampton, SO17 1BJ, UK;

    rnOffice of the Vice-Chancellor, Talbot Campus, Bournemouth University, Fern Barrow, Poole, Dorset, BH12 SBB, UK;

  • 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
  • 中图分类
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