TY - JOUR

T1 - Straightforward reconstruction of 3d surfaces and topography with a camera

T2 - accuracy and geoscience application

AU - James, Michael

AU - Robson, Stuart

N1 - ©2012. American Geophysical Union. All Rights Reserved

PY - 2012/9

Y1 - 2012/9

N2 - Topographic measurements for detailed studies of processes such as erosion or mass movement are usually acquired by expensive laser scanners or rigorous photogrammetry. Here, we test and use an alternative technique based on freely available computer vision software which allows general geoscientists to easily create accurate 3D models from field photographs taken with a consumer-grade camera. The approach integrates structure-from-motion (SfM) and multi-view-stereo (MVS) algorithms and, in contrast to traditional photogrammetry techniques, it requires little expertise and few control measurements, and processing is automated. To assess the precision of the results, we compare SfM-MVS models spanning spatial scales of centimeters (a hand sample) to kilometers (the summit craters of Piton de la Fournaise volcano) with data acquired from laser scanning and formal close-range photogrammetry. The relative precision ratio achieved by SfM-MVS (measurement precision : observation distance) is limited by the straightforward camera calibration model used in the software, but generally exceeds 1:1000 (i.e. centimeter-level precision over measurement distances of 10s of meters). We apply SfM-MVS at an intermediate scale, to determine erosion rates along a ~50-m-long coastal cliff. Seven surveys carried out over a year indicate an average retreat rate of 0.70±0.05 m a-1. Sequential erosion maps (at ~0.05 m grid resolution) highlight the spatio-temporal variability in the retreat, with semivariogram analysis indicating a correlation between volume loss and length scale. Compared with a laser scanner survey of the same site, SfM-MVS produced comparable data and reduced data collection time by ~80%.

AB - Topographic measurements for detailed studies of processes such as erosion or mass movement are usually acquired by expensive laser scanners or rigorous photogrammetry. Here, we test and use an alternative technique based on freely available computer vision software which allows general geoscientists to easily create accurate 3D models from field photographs taken with a consumer-grade camera. The approach integrates structure-from-motion (SfM) and multi-view-stereo (MVS) algorithms and, in contrast to traditional photogrammetry techniques, it requires little expertise and few control measurements, and processing is automated. To assess the precision of the results, we compare SfM-MVS models spanning spatial scales of centimeters (a hand sample) to kilometers (the summit craters of Piton de la Fournaise volcano) with data acquired from laser scanning and formal close-range photogrammetry. The relative precision ratio achieved by SfM-MVS (measurement precision : observation distance) is limited by the straightforward camera calibration model used in the software, but generally exceeds 1:1000 (i.e. centimeter-level precision over measurement distances of 10s of meters). We apply SfM-MVS at an intermediate scale, to determine erosion rates along a ~50-m-long coastal cliff. Seven surveys carried out over a year indicate an average retreat rate of 0.70±0.05 m a-1. Sequential erosion maps (at ~0.05 m grid resolution) highlight the spatio-temporal variability in the retreat, with semivariogram analysis indicating a correlation between volume loss and length scale. Compared with a laser scanner survey of the same site, SfM-MVS produced comparable data and reduced data collection time by ~80%.

KW - structure from motion

KW - coastal erosion

KW - DEM

KW - 3D model

UR - http://www.scopus.com/inward/record.url?scp=84865436534&partnerID=8YFLogxK

U2 - 10.1029/2011JF002289

DO - 10.1029/2011JF002289

M3 - Journal article

AN - SCOPUS:84865436534

VL - 117

JO - Journal of Geophysical Research: Earth Surface

JF - Journal of Geophysical Research: Earth Surface

SN - 2169-9011

IS - 3

M1 - F03017

ER -