Automatic Extraction of Road Information Using the Object-OrientedTechnology

Road information is rich in urban districts and mining areas. With the increase in spatial resolution and spectral resolution of remote sensing data, it is possible to extract information of narrow roads. However, the traditional manual extraction method using high-spatial-resolution data has shortcomings of low accuracy and low efficiency. Considering the features of SPOT-5 and Gaofen-1 data and the actual road situation of the study areas, the object-oriented method is used in this paper. The main advantage of this method is overcoming the limit of road extraction only using spectral information. A comparison with the results of the traditional supervised classification based on pixels proves that the objectoriented method improves the accuracy by 10% and provides better road information results. In addition, it is a more effective method to extract information for geographical condition monitoring.

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