Application of Digital Photogrammetry to Complex Topography for Geomorphological Research

Abstract

This paper is concerned with the application of automated digital photogrammetry, using 1:3000 scale photography, to complex, natural landform surfaces, of typical interest to geomorphologists. It assesses the quality of the results obtained using a relatively cheap and readily available area based stereomatching package, in terms of precision, accuracy and external reliability. Precision is investigated with reference to the confidence that can be placed in individual matches. Accuracy is evaluated using specially collected, independent datasets obtained from an area of complex topography in Glen Affric, Scotland. Data collection was stratified to areas of different surface roughness. External reliability is judged with respect to estimates of slope, a key parameter in geomorphological investigations. The results show that, whilst the effects of grid density and vegetation correction are the most important controls upon the accuracy and the external reliability of the photogrammetric results, collection parameters associated with the stereomatching process can also exert some control, particularly in areas of complex topography. It is impossible to generalize rules for choice of optimal collection parameters without careful consideration of the surface under investigation. Given that maximum grid densities are defined by the object space pixel resolution, the paper concludes that surface quality is largely governed by traditional controls upon photogrammetric data quality (camera calibration, base:distance ratio, ground control), combined with either scanning density or digital image resolution. However, over some surfaces, careful consideration has to be given to the effect of matching parameters.

High spatial resolution data acquisition for the geosciences: kite aerial photography

“…The mean error (ME) indicates the presence of bias or systematic errors; whereas the standard deviation of error (SDE) provides a measure of surface variability or precision. Past research (Li, 1988;Lane et al, 2000;Chandler et al, 2005) has demonstrated that these two statistics are more informative for surface comparison than the RMSE more traditionally used in surveying. Primary data output for the esker study yielded aerial photography, derivative DEMs and orthophotographs from stereo-pairs.…”

“…However, a lower coefficient increases the chance of 'false matches' and potential inclusion of erroneous data points. This effect is well known (Gooch et al, 1999;Lane et al, 2000) and some judgment is required in selecting the optimum correlation coefficient. It is comforting that a range of coefficients (0·7-0·8) appear to have produced a surface which is of an acceptable accuracy, despite some variation in point density.…”

Detection of Gully-Affected Areas by Applying Object-Based Image Analysis (OBIA) in the Region of Taroudannt, Morocco

“…The identification and classification of landforms from remote sensing data is increasingly popular among scientists [5,[9][10][11]. Tasks are carried out at various levels of scale, from global-scale landform classification [12] to a local-scale delineation of landforms [13,14].…”

Effect of Digital Elevation Model Mesh Size on Geomorphic Indices: A Case Study of the Ivaí River Watershed - State of Paraná, Brazil

“…In the floodplain areas, the movement of water is hardly detected using a DEM as it is controlled by very small topographic features, specifically if the mesh size is not fine enough to represent these small features such as narrow channels connecting main rivers and floodplains (Yamazaki et al 2012, Saksena andMerwade 2015). Moreover, the presence of noise and canopy in the DEM highly affect the drainage network in these regions, specifically with small mesh sizes (Lane, James andCrowell 2000, Polidori andSimonetto 2014).…”