...
首页> 外文期刊>International journal of remote sensing >Seasonal multitemporal land-cover classification and change detection analysis of Bochum, Germany, using multitemporal Landsat TM data
【24h】

Seasonal multitemporal land-cover classification and change detection analysis of Bochum, Germany, using multitemporal Landsat TM data

机译:使用多时相Landsat TM数据对德国波鸿进行季节性多时相土地覆盖分类和变化检测分析

获取原文
获取原文并翻译 | 示例
           

摘要

The 40-year Landsat time series makes it possible to continuously map and examine land-cover changes. By using images from two dates in each classification year, we can improve the classification accuracy of monotemporal approaches for each year and reduce the misclassification problem between bare lands or impervious surface and vegetation cover types. Two pairs of multitemporal cloud-free Landsat Thematic Mapper images (the first pair from 1 May and 9 June 1986 and the second from 4 June 2010 and 20 April 2011) were selected from the area of the city of Bochum, Germany. The multitemporal image sets were classified separately using the maximum likelihood classification algorithm. The overall accuracies of the monotemporal classifications for 1 May and 9 June 1986 were, respectively, 77.1 and 75.4% while the overall accuracy of the multitemporal classification for 1986 was 82.1%. The overall accuracies of the monotemporal classification for 4 June 2010 and 20 April 2011 were, respectively, 81.4 and 77.9%, while the overall accuracy of the multitemporal classification for 2010/2011 was 88.2%. Post-classification comparison change detection was used to determine change in land-cover type. The proportion of urban area increased from 55.3 to 61.1% for the whole area, while that of agricultural land decreased from 24.8 to 21.8% and bare land from 3.6 to 0.2%. Forest and water bodies remained almost unchanged between 1986 and 2011.
机译:Landsat 40年的时间序列使连续绘制和检查土地覆盖变化成为可能。通过使用每个分类年度中两个日期的图像,我们可以提高每年的单时间方法的分类准确性,并减少裸露土地或不透水地表与植被覆盖类型之间的分类错误问题。从德国波鸿市地区选择了两对多时间无云Landsat专题制图仪图像(第一对是1986年5月1日和6月9日,第二对是2010年6月4日和2011年4月20日)。使用最大似然分类算法分别对多时间图像集进行分类。 1986年5月1日和6月9日的单时相分类的总准确度分别为77.1%和75.4%,而1986年多时相分类的整体准确度为82.1%。 2010年6月4日和2011年4月20日的单时相分类的总体准确度分别为81.4%和77.9%,而2010/2011年的多时相分类的整体准确性为88.2%。分类后比较变化检测用于确定土地覆盖类型的变化。整个城市的面积比例从55.3%上升到61.1%,而农用地的比例从24.8%下降到21.8%,光地从3.6%下降到0.2%。在1986年至2011年之间,森林和水体几乎保持不变。

著录项

  • 来源
    《International journal of remote sensing》 |2016年第15期|3439-3454|共16页
  • 作者

    Henits L.; Juergens C.; Mucsi L.;

  • 作者单位

    Univ Szeged, Dept Phys Geog & Geoinformat, Szeged, Hungary|Inst Geodesy Cartog & Remote Sensing, Dept Environm Applicat Remote Sensing, Budapest, Hungary;

    Ruhr Univ Bochum, Fac Geosci, Bochum, Germany;

    Univ Szeged, Dept Phys Geog & Geoinformat, Szeged, Hungary;

  • 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
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号