The recognition of road network from high‐resolution satellite remotely sensed data using image morphological characteristics-Reference-Cited by-同舟云学术

The recognition of road network from high‐resolution satellite remotely sensed data using image morphological characteristics

Published:2005-12-20 Issue:24 Volume:26 Page:5493-5508
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Zhu C.¹²³,Shi W.²,Pesaresi M.⁴,Liu l.¹,Chen** X.⁵,King B.²

Affiliation:

1. a Institute of Geodesy and Geophysics , Chinese Academy of Science , Wuhan, 430077, China

2. b Advanced Research Centre for Spatial Information Technology , Department of Land Surveying and Geo‐Informatics , The Hong Kong Polytechnic University , Hong Kong

3. c Zhengzhou Institute of Surveying and Mapping , Zhengzhou, 450052, China

4. d Inform S.r.l. , Environmental Technology Department , Digital Mapping Sector , I–35129 Padova, Italy

5. e State Key Laboratory of Information Engineering in Surveying , Mapping and Remote Sensing , Wuhan University , Wuhan, 430079, China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431160500300354

Reference30 articles.

1. Automatic finding of main roads in aerial images by using geometric-stochastic models and estimation

2. Road vectors update using SAR imagery: a snake-based method

3. Road detection in spaceborne SAR images using a genetic algorithm

4. Fuzzy fusion techniques for linear features detection in multitemporal SAR images

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