## 1 Introduction  
Topographical and geological investigations are essential in every stage of the life cycle of an infrastructure; these stages are the feasibility study, planning, design, construction, operation, and rehabilitation. Results of such investigations not only affect the selection of alignment and method of construction but also provide important information concerning factors that affect structural deterioration or damage and associated maintenance measures [1, 2, 3, 4]. The enhancement of our understanding of topographic and geological information about a site where infrastructure is to be located is a critical aspect of some strategies for adapting to climate change. The development of a landform is affected geologically by tectonic activities and the interaction between strata and the environment; the spatial distribution and characteristics of a landform, such as rivers, ridges, terraces, creeks, cliffs, or steep overhangs, are manifestations of the long-term evolution of particular geological and environmental conditions [5, 6]. Topographical data are indispensable to geological mapping. Fine topographical data are frequently used to estimate the extension of different rock layers, to determine the existence of geological structures, collapsed areas or the spatial distribution of deep-seated gravitational deformation slopes and thus to provide a basis for the interpretation of the results of geological surveys. Topographic survey and mapping techniques have advanced greatly in recent years. In particular, topographic surveys and mapping using airborne-based light detection and the ranging technique (hereafter referred to as airborne-based LiDAR surveying and mapping) use multiple echoes of light waves, which partly penetrate vegetation to obtain information about the ground geometry in the form of a large number of fine point clouds. The point clouds provide geometric information about the surface of the ground and associated objects and substantially improve the resolution of topographic data by supporting metric-level or even more refined ground elevation models, which not only improve the accuracy of the map data but also change the method of survey and mapping [7; 8; 9]. Highly precise topographical data have improved the interpretation of large-scale geological structures, processes at the earth's surface, the associated development of landform features, and the surveying and corresponding production of geological maps [10; 11; 12; 13; 14]. [PERSON] and [PERSON] [15] identified the tectonic morphologies of the San Andreas Fault (SAF) using a digital elevation model (DEM) with a resolution from 0.25 to 0.5 m. They identified landforms such as benches, troughs, scarps, and aligned ridges in the 15 km long portion of the south-central SAF along the southern Cholame segment to understand the recurring earthquake slip. [PERSON] et al. [16] identified the dextral strike-slip principal slip zone (PSZ) of the Hurunui segment of the Hope Fault, based on a series of previously unrecognized 69 individual fault strands on a DEM that was generated using LiDAR-surveyed topographic data. Studies by [PERSON] et al. and others [10; 15; 16; 17; 18] have proved that LiDAR-surveyed data can be used to map geological structures under a forest cover in detail. Many investigations have focused on the use of DEMs generated by LiDAR surveying and mapping (hereafter referred to as LiDAR DEM) to interpret the geomorphic features of landslides [19; 20; 21; 22; 23; 24] and to measure the attitudes of strata [25; 26; 27] and tracking fault traces [28; 29; 30; 31; 32], to improve the accuracy of geological maps. However, examples of comparisons of the results of conventional field surveying and mapping with interpretations based on LiDAR DEM, or with geological features that have been revealed by underground excavation, are scarce.