Monitoring road infrastructures from satellite images in Greater Maputo: an object-oriented classification approach

Arianna Burzacchi, Matteo Landrò, Simone Vantini
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Abstract

The information about pavement surface type is rarely available in road network databases of developing countries although it represents a cornerstone of the design of efficient mobility systems. This research develops an automatic classification pipeline for road pavement which makes use of satellite images to recognize road segments as paved or unpaved. The proposed methodology is based on an object-oriented approach, so that each road is classified by looking at the distribution of its pixels in the RGB space. The proposed approach is proven to be accurate, inexpensive, and readily replicable in other cities.
从卫星图像监测大马普托地区的道路基础设施:面向对象的分类方法
尽管路面类型是设计高效交通系统的基石,但发展中国家的道路网络数据库中却很少有路面类型的信息。本研究开发了道路路面自动分类管道,利用卫星图像识别铺设路面或未铺设路面的路段。所提出的方法基于面向对象的方法,因此每条道路都是通过查看其像素在 RGB 空间中的分布来进行分类的。事实证明,所提出的方法准确、成本低廉,并可在其他城市推广。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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