点云
激光雷达
地理
遥感
合成孔径雷达
航测
计算机科学
数据提取
人工智能
梅德林
政治学
法学
作者
Ziyi Chen,Liai Deng,Yong Luo,Dilong Li,José Marcato,Wesley Nunes Gonçalves,Abdul Nurunnabi,Jonathan Li,Cheng Wang,Deren Li
出处
期刊:International journal of applied earth observation and geoinformation
日期:2022-08-01
卷期号:112: 102833-102833
被引量:28
标识
DOI:10.1016/j.jag.2022.102833
摘要
Automated extraction of roads from remotely sensed data come forth various usages ranging from digital twins for smart cities, intelligent transportation, urban planning, autonomous driving, to emergency management. Many studies have focused on promoting the progress of methods for automated road extraction from aerial and satellite optical images, synthetic aperture radar (SAR) images, and LiDAR point clouds. In the past 10 years, no a more comprehensive survey on this topic could be found in literature. This paper attempts to provide a comprehensive survey on road extraction methods that use 2D earth observing images and 3D LiDAR point clouds. In this review, we first present a tree-structure that separate the literature into 2D and 3D. Then, further methodologies level classification is demonstrated both in 2D and 3D. In 2D and 3D, we introduce and analyze the literature published in the last ten years. Except for the methodologies, we also review the aspects of data commonly used. Finally, this paper explores the existing challenges and future trends.
科研通智能强力驱动
Strongly Powered by AbleSci AI