JOURNAL ARTICLE

Automatic road network extraction using high resolution multi-temporal satellite images

Abstract

Automated road network extraction from remotely sensed imagery is of importance in the context of road databases creation, refinement and updating. Substantial amount of research has been carried out to extract road network from satellite imagery in the photogrammetric and computer vision communities. However, little research has been conducted on utility of multi-temporal satellite images in the context of road extraction. This paper first proposes a simple scheme to detect vehicles using high resolution multi-temporal images of a geographic location and uses the detected road seeds in Fourier descriptor based road tracking algorithm to extract the road network. Performance of the proposed method on CARTOSAT-2 images is discussed.

Keywords:
Computer science Photogrammetry Context (archaeology) Artificial intelligence Computer vision Satellite Remote sensing Satellite imagery Extraction (chemistry) Feature extraction Image resolution Tracking (education) Geography Engineering

Metrics

8
Cited By
1.34
FWCI (Field Weighted Citation Impact)
9
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Automated Road and Building Extraction
Physical Sciences →  Engineering →  Ocean Engineering
Remote Sensing and LiDAR Applications
Physical Sciences →  Environmental Science →  Environmental Engineering
Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology

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