Road Detection from Remote Sensing Images using Impervious Surface Characteristics: Review and Implication
Other literature type
Singh, P. P.
Garg, R. D.
(issn: 2194-9034, eissn: 2194-9034)
The extraction of road network is an emerging area in information extraction from high-resolution satellite images (HRSI). It is also
an interesting field that incorporates various tactics to achieve road network. The process of road detection from remote sensing
images is quite complex, due to the presence of various noises. These noises could be the vehicles, crossing lines and toll bridges.
Few small and large false road segments interrupt the extraction of road segments that happens due to the similar spectral behavior
in heterogeneous objects. To achieve a better level of accuracy, numerous factors play their important role, such as spectral data of
satellite sensor and the information related to land surface area. Therefore the interpretation varies on processing of images with
different heuristic parameters. These parameters have tuned according to the road characteristics of the terrain in satellite images.
There are several approaches proposed and implemented to extract the roads from HRSI comprising a single or hybrid method. This
kind of hybrid approach has also improved the accuracy of road extraction in comparison to a single approach. Some characteristics
related to impervious and non-impervious surfaces are used as salient features that help to improve the extraction of road area only
in the correct manner. These characteristics also used to utilize the spatial, spectral and texture features to increase the accuracy of
classified results. Therefore, aforesaid characteristics have been utilized in combination of road spectral properties to extract road
network only with improved accuracy. This evaluated road network is quite accurate with the help of these defined methodologies.