高分遥感在黄河流域水土流失动态监测中的应用
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国家重点研发计划项目“黄河水沙变化机理与趋势预测”(2016YFC0402403);全国水土流失动态监测与公告项目(1261520154801)


Application of High Resolution Remote Sensing Technology in Dynamic Monitoring of Soil and Water Loss in Yellow River Basin
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    摘要:

    [目的]总结和分析黄河流域水土流失动态监测项目所采用的遥感监测技术,为流域水土流失动态监测探索和推广一种崭新、高效的方法。[方法]基于资源3号高分辨率卫星影像,采用面向对象的影像分类方法对准格尔旗2014年的土地利用信息进行半自动分类,并构建植被覆盖度回归模型,对项目区植被覆盖度进行反演研究。[结果]面向对象的土地利用半自动分类结果和植被覆盖度回归模型反演结果,其野外验证精度达到90%以上,满足水土流失动态监测高解析度和高精确度基础数据获取的需求。[结论]面向对象的土地利用分类方法和植被覆盖度回归模型计算,能够有效避免传统人工目视解译导致的成果误差,节约人力成本和时间成本,提高数据获取的精度和效率。

    Abstract:

    [Objective] To summarize remote sensing monitoring techniques used in dynamic monitoring project of soil and water loss in Yellow River basin in order to explore a new and efficient approach for soil and water loss monitoring.[Methods] Based on resource 3 high-resolution satellite images, the object-oriented image classification approach was used to make semi-automatic classification of land utilization in Jungar Banner in 2014. The vegetation regression models were constructed to study the inversion of vegetation coverage in the project area.[Results] Based on semi-automatic classification of land utilization and the regression model of vegetation coverage, the experiment showed that the accuracy of field verification reached more than 90%, which satisfied the demand of high resolution and accuracy data acquisition for soil erosion monitoring.[Conclusion] The object-oriented image classification of land utilization and regression model of vegetation coverage can not only effectively avoid the error caused by artificial visual interpretation and save cost, but also improve the accuracy and efficiency for data acquisition.

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屈创,张春亮,王丽云,岳本江,刘晓燕.高分遥感在黄河流域水土流失动态监测中的应用[J].水土保持通报,2018,38(1):116-121

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  • 收稿日期:2017-08-31
  • 最后修改日期:2017-11-15
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  • 在线发布日期: 2018-03-08
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