A multi-constraint combined method for road extraction from airborne laser scanning data. (December 2021) - Yadav, Manohar
Highlights: A multi-constraint combined method for ALS-data based road network extraction. Radiometric, geometric and statistical constraints-based road extraction. Height and intensity-based similarity measures for regions formation. Accurate road extraction even in the presence of attached areas to the road, holes in the road and shadows. Road network extraction: average correctness 93% in different test sites. Abstract: Airborne laser scanning (ALS) is a state-of-the-art technique for fast and accurate acquisition of road network information. In this paper, an ALS data-based road extraction method, with four well-designed steps namely pre-processing, intensity-based filtering, quadrant-based region growing, and road candidate regions extraction is proposed. The contributions of this paper are mainly concentrated in last three steps, where radiometric, geometric and statistical constraints are combined to differentiate road and non-road points. The proposed method is straightforward to implement, where complex cases, such as removal of attached areas to the road, extraction of road surfaces surround the irregular data gaps left by vehicles and trees are effectively dealt. The method performance was evaluated using two datasets having complex cases and road network was extracted at average completeness, correctness and quality of 84.3%, 93% and 79.2%, respectively. The method achieves significant improvement in comparison with several state-of-the-art methods.