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.

中文翻译：

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用ALS点云对DSMA和BA方法进行涵洞修改的数字高程模型的精度比较

必须将源自机载激光扫描（ALS）点云的高分辨率数字高程模型（HR-DEM）转换为涵洞修改的DEM，以进行水文和地貌分析。为了生产涵洞改性的DEM，有关排水结构（DSs）（例如桥梁和涵洞）位置的信息至关重要。然而，DS映射技术，无论是与新方法的开发还是现有方法的应用设置有关，一直很复杂。因此，广域DS数据很少见，因此很难在广域容量中生产涵洞改性的DEM。备选地，突破算法（BA）方法是在没有DS数据的情况下获得涵洞修改的DEM的标准过程，从而在某种程度上解决了该问题。本文使用新开发的排水结构映射算法（DSMA）解决了该缺陷，该算法用于获得美国佛蒙特州36平方公里面积的涵洞改性DEM。基准DS数据用作评估DSMA方法与BA方法相比性能的标准参考。建立了一个一致的方法框架，使用DS数据获得涵洞改性的DEM，使用DSMA进行映射，然后将所得涵洞改性的DEM分别与BA方法进行比较。从涵洞修饰的DEM中发现的DS报告为真阳性（TP），假阳性（FP）和假阴性（FN）。基于源自两种方法的涵洞修改的DEM的TP，FP和FN，评估了误报率（FPR）（即佣金错误）和误报率（FNR）（即，遗漏误差）。我们的评估表明，新开发的基于DSMA的DS数据得出联邦公路管理局（FHWA）道路的FPR为0.05，非FHWA道路的FPR为0.12。FHWA道路的FNR为0.07，非FHWA道路的FNR为0.38。BA方法显示FHWA道路的FPR为0.28，非FHWA道路的FPR为0.62。同样，BA方法的FNR在FHWA道路上为0.32，在非FHWA道路上为0.61。基于FPR和FNR的统计数据表明，与基于BA的方法相比，基于DSMA的涵洞改性的DEM更准确，并且使用基于DSMA的DS数据生成涵体改性的DEM的配方框架是可靠的。非FHWA道路为12。FHWA道路的FNR为0.07，非FHWA道路的FNR为0.38。BA方法显示FHWA道路的FPR为0.28，非FHWA道路的FPR为0.62。同样，BA方法的FNR在FHWA道路上为0.32，在非FHWA道路上为0.61。基于FPR和FNR的统计数据表明，与基于BA的方法相比，基于DSMA的涵洞改性的DEM更准确，并且使用基于DSMA的DS数据生成涵体改性的DEM的配方框架是可靠的。非FHWA道路为12。FHWA道路的FNR为0.07，非FHWA道路的FNR为0.38。BA方法显示FHWA道路的FPR为0.28，非FHWA道路的FPR为0.62。同样，BA方法的FNR在FHWA道路上为0.32，在非FHWA道路上为0.61。基于FPR和FNR的统计数据表明，与基于BA的方法相比，基于DSMA的涵洞改性的DEM更准确，并且使用基于DSMA的DS数据生成涵体改性的DEM的配方框架是可靠的。