Automatic Road Centerline Extraction from Imagery Using Road GPS Data [PDF]
Remote Sensing, 2014 Road centerline extraction from imagery constitutes a key element in numerous geospatial applications, which has been addressed through a variety of approaches.
Chuqing Cao, Ying Sun
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MRENet: Simultaneous Extraction of Road Surface and Road Centerline in Complex Urban Scenes from Very High-Resolution Images [PDF]
Remote Sensing, 2021 Automatic extraction of the road surface and road centerline from very high-resolution (VHR) remote sensing images has always been a challenging task in the field of feature extraction.
Zhenfeng Shao +3 more
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Road Extraction from Very High Resolution Images Using Weakly labeled OpenStreetMap Centerline [PDF]
ISPRS International Journal of Geo-Information, 2019 Road networks play a significant role in modern city management. It is necessary to continually extract current road structure, as it changes rapidly with the development of the city.
Songbing Wu +5 more
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An automatic method for road centerline extraction from post-earthquake aerial images
Geodesy and Geodynamics, 2019 Road vector database plays an important role in post-earthquake relief, rescue and reconstruction. However, due to data privacy policy, it is difficult for general users to obtain high-precision and complete vector data of road network. The OpenStreetMap
Zhumei Liu, Jingfa Zhang, Xue Li
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Road Centerline Extraction from Very-High-Resolution Aerial Image and LiDAR Data Based on Road Connectivity [PDF]
Remote Sensing, 2018 The road networks provide key information for a broad range of applications such as urban planning, urban management, and navigation. The fast-developing technology of remote sensing that acquires high-resolution observational data of the land surface ...
Zhiqiang Zhang +3 more
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A Self-Supervised Learning Framework for Road Centerline Extraction From High-Resolution Remote Sensing Images [PDF]
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Road extraction from the high-resolution remote sensing image is significant for the land planning, vehicle navigation, etc. The existing road extraction methods normally need many preprocessing and subsequent optimization steps.
Qing Guo, Zhipan Wang
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Simultaneous Extraction of Road and Centerline from Aerial Images Using a Deep Convolutional Neural Network [PDF]
ISPRS International Journal of Geo-Information, 2021 The extraction of roads and centerlines from aerial imagery is considered an important topic because it contributes to different fields, such as urban planning, transportation engineering, and disaster mitigation. Many researchers have studied this topic
Tamara Alshaikhli +2 more
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AUTOMATIC CENTERLINE EXTRACTION OF COVERD ROADS BY SURROUNDING OBJECTS FROM HIGH RESOLUTION SATELLITE IMAGES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees,
H. Kamangir, M. Momeni, M. Satari
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Extracting Centerlines From Dual-Line Roads Using Superpixel Segmentation [PDF]
IEEE Access, 2019 Extracting centerlines from dual-line roads is very important in urban spatial analysis and infrastructure planning. In recent decades, numerous algorithms for road centerline extraction based on the vector data have been proposed by various scholars ...
Yilang Shen, Tinghua Ai, Min Yang
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Lane Centerline Extraction Based on Surveyed Boundaries: An Efficient Approach Using Maximal Disks [PDF]
SensorsMaps of road layouts play an essential role in autonomous driving, and it is often advantageous to represent them in a compact form, using a sparse set of surveyed points of the lane boundaries.
Chenhui Yin +4 more
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