The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
A review of road extraction from remote sensing images
Open accessAbstract
As a significant role for traffic management, city planning, road monitoring, GPS navigation and map updating, the technology of road extraction from a remote sensing (RS) image has been a hot research topic in recent years. In this paper, after analyzing different road features and road models, the road extraction methods were classified into the classification-based methods, knowledge-based methods, mathematical morphology, active contour model, and dynamic programming. Firstly, the road features, road model, existing difficulties and interference factors for road extraction were analyzed. Secondly, the principle of road extraction, the advantages and disadvantages of various methods and research achievements were briefly highlighted. Then, the comparisons of the different road extraction algorithms were performed, including road features, test samples and shortcomings. Finally, the research results in recent years were summarized emphatically. It is obvious that only using one kind of road features is hard to get an excellent extraction effect. Hence, in order to get good results, the road extraction should combine multiple methods according to the real applications. In the future, how to realize the complete road extraction from a RS image is still an essential but challenging and important research topic.
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Cites
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Road Network Extraction and Intersection Detection From Aerial Images by Tracking Road Footprints
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Cited by
Mapping Roads in the Brazilian Amazon with Artificial Intelligence and Sentinel-2
Botelho, J., Costa, S. C. P., Ribeiro, J. G., & Souza, C. M. (2022) · Remote Sensing · doi:10.3390/rs14153625 · Cited by 43
Metadata
- Authors
- Wang, W., Yang, N., Zhang, Y., Wang, F., Cao, T., & Eklund, P.
- Venue
- Journal of Traffic and Transportation Engineering (English Edition)
- Publisher
- Elsevier BV
- Published
- 2016-06
- Volume
- 3
- Issue
- 3
- Pages
- 271-282
- ISSN
- 2095-7564 (ISSN-L)
- OpenAlex
- W2395811491
- Cited by
- 299
- References
- 18
- FWCI
- 27.33
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Wang, W., Yang, N., Zhang, Y., Wang, F., Cao, T., & Eklund, P. (2016). A review of road extraction from remote sensing images. Journal of Traffic and Transportation Engineering (English Edition). https://doi.org/10.1016/j.jtte.2016.05.005
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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