| Autor: |
Jianxin Jia, Haibin Sun, Changhui Jiang, Kirsi Karila, Mika Karjalainen, Eero Ahokas, Ehsan Khoramshahi, Peilun Hu, Chen Chen, Tianru Xue, Tinghuai Wang, Yuwei Chen, Juha Hyyppä |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Remote Sensing, Vol 13, Iss 21, p 4235 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2072-4292 |
| DOI: |
10.3390/rs13214235 |
| Popis: |
Digital maps of road networks are a vital part of digital cities and intelligent transportation. In this paper, we provide a comprehensive review on road extraction based on various remote sensing data sources, including high-resolution images, hyperspectral images, synthetic aperture radar images, and light detection and ranging. This review is divided into three parts. Part 1 provides an overview of the existing data acquisition techniques for road extraction, including data acquisition methods, typical sensors, application status, and prospects. Part 2 underlines the main road extraction methods based on four data sources. In this section, road extraction methods based on different data sources are described and analysed in detail. Part 3 presents the combined application of multisource data for road extraction. Evidently, different data acquisition techniques have unique advantages, and the combination of multiple sources can improve the accuracy of road extraction. The main aim of this review is to provide a comprehensive reference for research on existing road extraction technologies. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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