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Multispectral airborne laser scanning (ALS) data have recently become available. The objective of this letter is to study the feasibility of these data for road mapping-for road detection and road surface classification. The results are compared with the results of traditional aerial ortho images using object-based image analysis and Random Forest classification. The results demonstrate that the multispectral ALS data are feasible for automatic road detection and a significant improvement compared to the use of optical aerial imagery is obtained. In a test using ALS data, 80.5% points representing roads were classified correctly. When aerial images were used, the percentage decreased to 71.6%.

Feasibility of Multispectral Airborne Laser Scanning Data for Road Mapping