湖北农业科学 ›› 2021, Vol. 60 ›› Issue (23): 148-152.doi: 10.14088/j.cnki.issn0439-8114.2021.23.033

• 信息工程 • 上一篇    下一篇

基于建筑遥感指数与面向对象的高分影像农村建筑物信息提取

马海荣, 沈祥成, 罗治情, 陈聘婷, 官波   

  1. 湖北省农业科学院农业经济技术研究所/湖北省农业科技创新中心农业经济技术研究分中心/湖北省乡村振兴研究院,武汉 430064
  • 收稿日期:2021-07-05 出版日期:2021-12-10 发布日期:2021-12-21
  • 作者简介:马海荣(1986-),女,山东菏泽人,助理研究员,博士,主要从事遥感技术农业应用研究,(电话)15002778923(电子信箱)mahairong1008@126.com。
  • 基金资助:
    湖北省农业科技创新中心“农业经济与信息研究”团队项目(2019-620-000-001-29)

Rural building information extraction based on built-up index and object oriented image

MA Hai-rong, SHEN Xiang-cheng, LUO Zhi-qing, CHEN Pin-ting, GUAN Bo   

  1. Institute of Agricultural Economic and Technological, Hubei Academy of Agricultural Sciences/Hubei Agricultural Science and Technology Innovation Center Agricultural Economic and Technological Research Sub-Center/Hubei Rural Revitalization Research Institute,Wuhan 430064,China
  • Received:2021-07-05 Online:2021-12-10 Published:2021-12-21

摘要: 基于高空间分辨率遥感影像获取农村建筑物的面积和分布信息,对农村基础地理数据的获取、农村土地利用规划、监测农村土地变化和居民点用地合理性评价具有重要意义。研究基于高景1号卫星影像,提出了一种基于建筑物遥感特征指数与面向对象方法的农村建筑物信息提取方法。首先构建两个建筑遥感指数对农村建筑信息进行初步提取,然后利用面向对象分割结果对初步提取结果进行优化。结果表明,该方法可以有效提取农村建筑物信息。

关键词: 面向对象影像, 建筑遥感指数, 高分辨率遥感影像, 农村建筑

Abstract: Timely and accurately acquisition of the area and spatial distribution of rural building information would be valuable for acquisition of rural basic geographic data, rural land use planning, monitoring of rural land change and rationality evaluation of residential land use. Based on the Superview-1 satellite images, we propose a rural building information extraction method based on build-up remote sensing index and object-oriented image segmentation method. Firstly, we constructed two building remote sensing indexes and obtained the preliminary extraction results by threshold segmentation of the build-up index. Then the preliminary extraction results were optimized by the object-oriented segmentation results. The results showed that based on the method we proposed it can effectively extract the information of rural buildings.

Key words: object oriented image, built-up index, high resolution remote sensing image, rural building

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