# Review on Active and Passive Remote Sensing Techniques for Road Extraction
## 3 Road Extraction Based on Different Data Sources
### Road Extraction Based on SAR Images  
#### 3.3.1 Main Methods  
In general, roads in SAR images appear as dark linear features. However, the differential orientation of roads and antennas influences the ability of SAR to identify roads. In traditional heuristic methods, road segments are often extracted using an edge/line detector. Then, a graph is generated from the segments and optimised, and the segments are connected to develop a coherent road network. Recently, data-driven deep learning-based semantic segmentation methods have been reported. Moreover, road junctions and bridges are important parts of road networks and have been the topic of some previous studies. Road network extraction from SAR images has been reported in various studies [199; 200; 201]. In [200], two local line detectors were used, and the results were fused to find candidates for road segments. The road segments were connected using a Markov ran \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Platform** & **Characteristic** & **References** \\ \hline Traditional process & & & \\ includes the spectral information & & & \\ Spectral mixture and & & & \\ Q-tree filter & & & \\ Pixel & & & \\ to pixel classification & & & \\ Spectral angle mapper & Airborne & & \\ Computing the angle from & & & \\ spectral response & UAV & Detect pavement roads & [198; 2019] \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Summary of road extraction using hyperspectral images. dom field, and an active contour model (snake) was used for the postprocessing. In [200], this method was applied on dense urban areas, and very-high-resolution data and different flight directions were combined to improve the results. In [201], constant false alarm rate detection, morphological filtering, segmentation and Hough transformation were integrated to recognise roads in high-resolution polarimetric airborne SAR images. The strong backscattering from fences was used to detect bridges, and then the roads were recognised using a Hough transformation  
The fusion of different SAR datasets and algorithms in early studies improved road extraction accuracy. In [202], different preprocessing algorithms, road extractors and different images of the same area were fused, and a multiscale approach was used for road extraction. For SAR, a combination of different view angles is also proposed. [PERSON] [203] extracted road networks by combining the line extractor results with two classification results. [PERSON] [204] detected rural and urban areas and then fused a road extractor for rural areas to develop an extractor designed for urban areas. The latest reported studies used new high-resolution data, usually from the TerraSAR-X or GaoFen-3 satellites. In [205], multiscale geometric analysis was performed on vectorised detector responses for road network grouping using two TerraSAR-X datasets. In [206], a method suitable for analysing SAR images of different resolutions was proposed. A weighted ratio line detector was developed to extract the road ratio and direction information. The road network was constructed using a region-growing method and tested using four SAR datasets obtained from different study areas. [PERSON] [207] extracted road networks based on a network snake model and three TerraSAR-X images. [PERSON] [208] introduced an algorithm in which road segment extraction and network optimisation were performed simultaneously using a Bayesian framework, multiscale feature extractor and CRF; for this analysis, [PERSON] used the TerraSAR-X and airborne SAR data. [PERSON] [209] proposed a method based on vector Radon transformation, and promising results were presented for six SAR images of different resolutions, bands and polarisations; these images were obtained from airborne SAR, GaoFen-3 and TerraSAR-X. In general, for road extraction from new very-high-spatial-resolution (VHR) data, completeness of 74-93% and correctness of 70-94% have been reported, depending mostly on the study site.