Accuracy Comparison on Culvert-Modified Digital Elevation Models of DSMA and BA Methods Using ALS Point Clouds

Abstract

High-resolution digital elevation models (HR-DEMs) originating from airborne laser scanning (ALS) point clouds must be transformed into Culvert-modified DEMs for hydrological and geomorphological analysis. To produce a culvert-modified DEM, information on the locations of drainage structures (DSs) (e.g., bridges and culverts) is essential. Nevertheless, DS mapping techniques, whether in connection with the development of new methods or an application setting of existing methods, have always been complicated. Consequently, wide area DS data are rare, making it challenging to produce a culvert-modified DEM in a wide area capacity. Alternatively, the breach algorithm (BA) method is a standard procedure to obtain culvert-modified DEMs in the absence of DS data, solving the problem to some extent. This paper addresses this shortcoming using a newly developed drainage structure mapping algorithm (DSMA) for obtaining a culvert-modified DEM for an area of 36 km² in Vermont, USA. Benchmark DS data are used as a standard reference to assess the performance of the DSMA method compared to the BA method. A consistent methodological framework is formulated to obtain a culvert-modified DEM using DS data, mapped using the DSMA and resultant culvert-modified DEM is then compared with BA method respectively. The DSs found from the culvert-modified DEMs were reported as true positive (TP), false positive (FP), and false negative (FN). Based on TP, FP, and FN originating from the culvert-modified DEMs of both methods, the evaluation metrics of the false positive rate (FPR) (i.e., the commission error) and false negative rate (FNR) (i.e., the omission error) were computed. Our evaluation showed that the newly developed DSMA-based DS data resulted in an FPR of 0.05 with federal highway authorities (FHWA) roads and 0.12 with non-FHWA roads. The FNR with FHWA roads was 0.07, and with non-FHWA roads, it was 0.38. The BA method showed an FPR of 0.28 with FHWA roads and 0.62 with non-FHWA roads. Similarly, the FNR for the BA method was 0.32 with FHWA roads and 0.61 with non-FHWA roads. The statistics based on the FPR and FNR showed that the DSMA-based culvert-modified DEM was more accurate compared with the BA method, and the formulated framework for producing culvert-modified DEMs using DSMA-based DS data was robust.

Perceived Usefulness of Airborne LiDAR Technology in Road Design and Management: A Review

“…A study was also conducted by B. Bigdeli et al [93] that used Invasive Weed Optimization presented for LiDAR point interpolation to improve accuracy when creating a DTM at the forested canopy and steep terrain. In addition, the study by N. Fareed and C. Wang [94], which incorporates Drainage Structure Mapping Algorithm, proposed that culvert modified DEMs could be obtained for hydrological studies on highways. Meanwhile, R. Pu and S. Landry [95] used multi-seasonal Pléiades satellite imagery and airborne LiDAR data to provide accurate tree mapping to maintain a sustainable development area.…”

“…Then, He et al [104] used an extraction from LiDAR points to provide up-to-date data for transportation networks, particularly highway assets (traffic sign, light pole, bridge, culvert, and billboard). N. Fareed and C. Wang [94] in their study used the Drainage Structure Mapping algorithm to obtain information about the location of drainage structures such as bridges and culverts. Meanwhile, M.Javanmardi et al [105] utilized histogram height information along a road to detect traffic signs by looking into coloured images representing traffic signs.…”

A Kriging Method for the Estimation of ALS Point-Cloud Accuracy without Ground Truth

“…For example, the government of Québec province in Canada has organized several acquisition campaigns since 2015 to obtain a coverage of the southern part of the province, at a density of at least 2.5 points/m 2 [1]. The data are used to generate several products such as high-resolution digital terrain models (DTM) and digital surface models (DSM) [2][3][4], from which other products such as slope maps, canopy-height models and hydrological maps are derived.…”

Factors Influencing the Use of Geospatial Technology with LiDAR for Road Design: Case of Malaysia

“…DTM are also useful in providing information for the construction of slope protection in road areas with high slopes [18,19]. Meanwhile, the Digital Elevation Model (DEM) information obtained from LiDAR can be utilised in determining the drainage structure of the road [20].…”