Applicability Assessments of Close-Range Photogrammetry for Slope Face 3D Modelling

Abstract

The digital single lens reflex (DSLR) cameras have been widely accepted to use in slope face photogrammetry rather than the expensive metric camera used for aerial photogrammetry. 3D models generated from digital photogrammetry can approach those generated from terrestrial laser scanning in term of scale and level of detail. It is cost effective and has equipment portability. This paper presents and discusses the applicability of close-range digital photogrammetry to produce 3D models of rock slope faces. Five experiments of image capturing method were conducted to capture the photographs as the input data for processing. As a consideration, the appropriate baseline lengths to capture the slope face to get better result are around 1/6 to 1/8 of target distance. A fine quality of 3D model from data processing is obtained using strip method and convergent method with 80% overlapping in each photograph. A random camera positions with different distances from the slope face can also generate a good 3D model, however the entire target should be captured in each photograph. The accuracy of the models is generated by comparing the 3D models produced from photogrammetry with the 3D data obtained from laser scanner. The accuracy of 3D models is quite satisfactory with the mean error range from 0.008 to 0.018 m.

A Field-Based Method for Estimation of Overlap for Convergent Images for View Planning of Buildings

“…CRTP acquires overlapping images with ease and better control using low-cost consumer grade cameras and yet delivers high resolution surface models of above ground objects situated over small areas, where data acquisition is challenged due to unavailability of GPS signals, or occluded objects and terrain surface. Recent studies highlight applications for 3D mapping and modelling of building structures, geomorphologic structure, artefacts, heritage structure, tree diameter etc (Matthews, 2008;García-Gago et al 2014;Abbaszadeh and Rastiveisa, 2017;Mokroš et al, 2018;Baramsyah and Rich, 2019).…”