Hasnain Bangash

This study aims to develop the application of photogrammetry for geological mapping in an open pit mine (Lindsays Pit located in Coolgardie, Western Australia). Several photographic surveys of the same pit were captured under different light conditions using different focal length lenses. Photogrammetry was applied to the photographs to match pixels, construct point clouds using a powerful bundle adjustment algorithm, then converts these point cloud into wireframe and textured three dimensional models. The three dimensional models are georeferenced using a method where UTM coordinates were accurately determined for ground control points, spread across the entire pit, using survey grade GPS.

ABSTRACT This contribution reviews the use of modern 3D photo-based surface reconstruction techniques for high fidelity surveys of trenches, rock exposures and hand specimens to highlight their potential for paleoseismology and structural geology. We outline the general approach to data acquisition and processing using ground-based photographs acquired from standard DSLR cameras, and illustrate the use of similar processing approaches on imagery from Unmanned Aerial Vehicles (UAVs). It is shown that digital map and trench data can be acquired at ultra-high resolution and in much shorter time intervals than would be normally achievable through conventional grid mapping. The resulting point clouds and textured models are inherently multidimensional (x, y, z, point orientation, colour, texture), archival and easily transformed into orthorectified photomosaics or digital elevation models (DEMs). We provide some examples for the use of such techniques in structural geology and paleoseismology while pointing the interested reader to free and commercial software packages for data processing, visualization and 3D interpretation. Photogrammetric models serve to act as an ideal electronic repository for critical outcrops and observations, similar to the electronic lab book approach employed in the biosciences. This paper also highlights future possibilities for rapid semi-automatic to automatic interpretation of the data and advances in technology.

Photogrammetry has revolutionised in the last decade, with the advent of computer vision techniques such as Structure from Motion (Westoby et al., 2012).These techniques now allow us to capture outcrops, in 3D, at high resolution simply with a digital camera and inexpensive software (e.g. AGISOFT PHOTOSCAN PRO).The objective of this study was to test the variables that make high quality photogrammetric models and develop a workflow for reliable geological mapping of legacy open pits, for the exploration geologist and mine geologist. The case study site is Lindsays Pit, Coolgardie, Western Australia.

ABSTRACT This contribution reviews the use of modern 3D photo-based surface reconstruction techniques for high fidelity surveys of trenches, rock exposures and hand specimens to highlight their potential for paleoseismology and structural geology. We outline the general approach to data acquisition and processing using ground-based photographs acquired from standard DSLR cameras, and illustrate the use of similar processing approaches on imagery from Unmanned Aerial Vehicles (UAVs). It is shown that digital map and trench data can be acquired at ultra-high resolution and in much shorter time intervals than would be normally achievable through conventional grid mapping. The resulting point clouds and textured models are inherently multidimensional (x, y, z, point orientation, colour, texture), archival and easily transformed into orthorectified photomosaics or digital elevation models (DEMs). We provide some examples for the use of such techniques in structural geology and paleoseismology while pointing the interested reader to free and commercial software packages for data processing, visualization and 3D interpretation. Photogrammetric models serve to act as an ideal electronic repository for critical outcrops and observations, similar to the electronic lab book approach employed in the biosciences. This paper also highlights future possibilities for rapid semi-automatic to automatic interpretation of the data and advances in technology.