TY - JOUR

T1 - Mitigating systematic error in topographic models for geomorphic change detection

T2 - Accuracy, precision and considerations beyond off‐nadir imagery

AU - James, Mike R.

AU - Antoniazza, Gilles

AU - Robson, Stuart

AU - N. Lane, Stuart

PY - 2020/8/1

Y1 - 2020/8/1

N2 - Unmanned aerial vehicles (UAVs) and structure-from-motion photogrammetry enable detailed quantification of geomorphic change. However, rigorous precision-based change detection can be compromised by survey accuracy problems producing systematic topographic error (e.g. 'doming'), with error magnitudes greatly exceeding precision estimates. Here, we assess survey sensitivity to systematic error, directly correcting topographic data so that error magnitudes align more closely with precision estimates. By simulating conventional grid-style photogrammetric aerial surveys, we quantify the underlying relationships between survey accuracy, camera model parameters, camera inclination, tie point matching precision and topographic relief, and demonstrate a relative insensitivity to image overlap. We show that a current doming-mitigation strategy of using a gently inclined ( 0 center dot 3 m, representing accuracy issues an order of magnitude greater than precision-based error estimates. For higher-relief topography, and for nadir-imaging surveys of the lower-relief topography, systematic error was <0 center dot 09 m. Modelling and subtracting the systematic error directly from the topographic data successfully reduced error magnitudes to values consistent with twice the estimated precision. Thus, topographic correction can provide a more robust approach to uncertainty-based detection of event-scale geomorphic change than designing surveys with small off-nadir camera inclinations and, furthermore, can substantially reduce ground control requirements. (c) 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd

AB - Unmanned aerial vehicles (UAVs) and structure-from-motion photogrammetry enable detailed quantification of geomorphic change. However, rigorous precision-based change detection can be compromised by survey accuracy problems producing systematic topographic error (e.g. 'doming'), with error magnitudes greatly exceeding precision estimates. Here, we assess survey sensitivity to systematic error, directly correcting topographic data so that error magnitudes align more closely with precision estimates. By simulating conventional grid-style photogrammetric aerial surveys, we quantify the underlying relationships between survey accuracy, camera model parameters, camera inclination, tie point matching precision and topographic relief, and demonstrate a relative insensitivity to image overlap. We show that a current doming-mitigation strategy of using a gently inclined ( 0 center dot 3 m, representing accuracy issues an order of magnitude greater than precision-based error estimates. For higher-relief topography, and for nadir-imaging surveys of the lower-relief topography, systematic error was <0 center dot 09 m. Modelling and subtracting the systematic error directly from the topographic data successfully reduced error magnitudes to values consistent with twice the estimated precision. Thus, topographic correction can provide a more robust approach to uncertainty-based detection of event-scale geomorphic change than designing surveys with small off-nadir camera inclinations and, furthermore, can substantially reduce ground control requirements. (c) 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd

KW - UAV

KW - DEM

KW - structure from motion

KW - systematic doming error

KW - decentring lens distortion

KW - topographic correction

U2 - 10.1002/esp.4878

DO - 10.1002/esp.4878

M3 - Journal article

VL - 45

SP - 2251

EP - 2271

JO - Earth Surface Processes and Landforms

JF - Earth Surface Processes and Landforms

SN - 0197-9337

IS - 10

ER -