摘要
机场净空是保障航空器安全运行的基本条件,超高建筑物导致机场运行及管理日益困难。因此,本文提出了一套利用现代遥感手段进行机场净空区建筑物三维动态监测的方法。首先利用机器学习的方法对高分辨率光学遥感影像进行建筑物变化检测,获取新增建筑物的空间分布;然后基于GIS空间数据库和SAR传感器参数进行建筑物高度的估计,并以天津某小区为例进行算法验证;最终建筑物高程反演精度可以达到1 m,有效验证了本文算法的有效性。
Airport clearance is the basic condition to ensure the safe operation of aircraft,super-high buildings make it difficult to operate and manage the airport.Traditional airport clearance obstacle acquisition methods have some shortcomings,such as slow mapping speed,low accuracy,difficulty in updating,and users can not quickly obtain the required information.In view of this,this paper presents a set of three-dimensional dynamic monitoring method for airport clearance buildings by using remote sensing data.Firstly,this method uses machine learning method to detect building changes in high resolution optical remote sensing images.Then uses high resolution synthetic aperture radar(SAR)images to retrieve building heights.Finally,the accuracy of building elevation inversion can reach the index of 1 meter,which effectively verifies the effectiveness of the calculation points in this paper.
作者
杨盛华
尹洋
郭欣萌
张月
杨魁
田英杰
YANG Shenghua;YIN Yang;GUO Xinmeng;ZHANG Yue;YANG Kui;TIAN Yingjie(Tianjin Binhai International Airport,Tianjin300300,China;Tianjin Institute of Surveying and Mapping,Tianjin300381,China)
出处
《测绘通报》
CSCD
北大核心
2019年第S1期105-109,共5页
Bulletin of Surveying and Mapping
关键词
机场净空
多源遥感
建筑物变化监测
建筑物高度提取
高程反演精度
airport clearance
multi-source remote sensing
building change monitoring
building height extraction
elevation inversion accuracy
