“高分一号”卫星遥感影像面向对象的水边线提取

发布时间：2018-02-11 11:43

本文关键词： 面向对象方法水边线提取岸线类型 “高分一号”卫星遥感应用　出处：《航天返回与遥感》2017年04期 　论文类型：期刊论文

【摘要】：水边线提取对揭示沿海地区自然资源管理状况和人工海域使用程度具有重要的指示作用。文章以津冀地区沿海城市海岸带为例,选取"高分一号"卫星数据为遥感数据源,首先对数据进行了辐射校正、几何校正、影像融合和裁剪等处理,然后采用面向对象的目标提取技术自动提取了研究区内大范围的水边线,并在充分了解不同海岸类型的遥感解译标志的基础上对提取的岸线进行了分类。结果显示研究区的岸线类型主要以砂砾质岸线、养殖/盐田岸线和港口码头岸线为主。在分类结果的精度验证过程中,以与"高分一号"卫星相近时期的亚米级遥感影像为底图,以目视解译的方式从中提取高精度的海岸线,并将目视解译的结果与从"高分一号"卫星数据中提取到的岸线进行对比。通过比较发现,两者位置、长度等基本吻合,从而证明了该海岸线提取方法对高分辨率遥感影像的有效性。该方法为基于"高分一号"卫星遥感数据进行大范围海岸的水边线提取提供了技术支撑,也为实现中国海岸线的定期自动更新奠定了基础。
[Abstract]:The extraction of waterfront plays an important role in revealing the management of natural resources and the use of artificial sea areas in coastal areas. Taking the coastal zone of coastal cities in Tianjin-Hebei region as an example, the satellite data of "Gao Fen No. 1" is selected as the remote sensing data source. First of all, the data are processed with radiometric correction, geometric correction, image fusion and clipping, and then the wide range of water edges in the study area are automatically extracted by object oriented object extraction technology. The extracted shoreline was classified on the basis of fully understanding the remote sensing interpretation marks of different coastal types. The results showed that the main shoreline types in the study area were sandy and gravel shoreline. Farming / salt field shoreline and port wharf shoreline are dominant. In the process of accuracy verification of classification results, the high-precision shoreline is extracted from the sub-rice remote sensing images of the period close to the Gaofen 1 satellite as the base map, and the coastline is extracted by visual interpretation. The results of visual interpretation are compared with the shoreline extracted from Gaofen 1 satellite data. Through comparison, it is found that the positions and lengths of the two are basically consistent. It is proved that this method is effective for high resolution remote sensing images, and it provides technical support for the extraction of waterfront in a large area of coast based on the satellite remote sensing data of "Gao Fen 1". Also for the realization of China's coastline regular automatic updating laid the foundation.
【作者单位】：山东科技大学测绘科学与工程学院;中国科学院遥感与数字地球研究所数字地球重点实验室;国家海洋技术中心;
【基金】：中国科学院“百人项目”(Y34005101A,Y2ZZ03101B) 中国科学技术部国家科技支撑计划专题(2015BAB05B05-02) 高分辨率对地观测系统重大专项(30-Y20A37-9003-15/17) 中国科学院重点部署项目(ZDRW-ZS-2016-6-1-3) 国家海洋局项目(Y21702011)
【分类号】：P715.7

【相似文献】