The potential of digital filtering of generic topographic data for geomorphological research

Abstract

High resolution terrain models generated from widely available Interferometric Synthetic Aperture Radar (IfSAR) and digital photogrammetry are an exciting resource for geomorphological research. However, these data contain error, necessitating pre-processing to improve their quality. We evaluate the ability of digital filters to improve topographic representation, using: (1) a Gaussian noise removal filter; (2) the proprietary filters commonly applied to these datasets; and (3) a terrain sensitive filter, similar to those applied to laser altimetry data. Topographic representation is assessed in terms of both absolute accuracy measured with reference to independent check data and derived geomorphological variables (slope, upslope contributing area, topographic index and landslide failure probability) from a steepland catchment in northern England. Results suggest that proprietary filters often degrade or fail to improve precision. A combination of terrain sensitive and Gaussian filters performs best for both IfSAR and digital photogrammetry datasets, improving the precision of photogrammetry digital elevation models (DEMs) by more than 50 per cent relative to the unfiltered data. High-frequency noise and high-magnitude gross errors corrupt geomorphological variables derived from unfiltered photogrammetry DEMs. However, a terrain sensitive filter effectively removes gross errors and noise is minimized using a Gaussian filter. These improvements propagate through derived variables in a landslide prediction model, to reduce the area of predicted instability by up to 29 per cent of the study area. Interferometric Synthetic Aperture Radar is susceptible to removal of topographic detail by oversmoothing and its errors are less sensitive to filtering (maximum improvement in precision of 5 per cent relative to the raw data).

Perspective – synthetic DEMs: A vital underpinning for the quantitative future of landform analysis?

“…Thus, there are a number of valid types and specific uses of synthetic DEMs, but in combination we believe that they form a vital underpinning for the quantitative future of landform analysis (e.g. see McCoy, 2015).…”

“…Rigour added to geomorphological observations through testing with synthetic DEMs will, we believe, ultimately link physics-driven models of processes to morphological observations, allowing quantitative hypotheses to be formulated and tested (e.g. see McCoy, 2015). This is illustrated in Fig.…”

“…They can also be used to estimate the probability of landsliding during rainstorms or for (semi-)automated geomorphological mapping (e.g. Tarolli and Tarboton, 2006;Milledge et al, 2009;Eisank et al, 2014). Thus, such quantifications also have value for geomorphic understanding.…”

Mobile laser scanning in fluvial geomorphology: mapping and change detection of point bars

“…They demonstrated that a vertical accuracy of ± 0.02 m could be obtained for a dry bar surface. In another study, the point density of the static TLS varied between 100 and 10 000 points/m 2 mainly due to changes in the range to the target and an RMS error ranging from ± 2 to ± 25 mm (Milledge et al, 2009). Milan et al (2007) concluded that TLS makes it possible to identify faint changes in fluvial geomorphology, including change detection of the bar edges, banks, chute channels and lobe deposition.…”

Towards a protocol for laser scanning of rock surfaces

“…English Heritage have proposed a series of standard scanning resolutions for representing specifi c scales of change on stonework (English Heritage, 2007). Use of high resolution remotely sensed data for representing terrain has become increasingly common across a range of scales (Lane and Chandler, 2003), in particular the use of digital photogrammetry (Lane et al, 2000;Bailey et al, 2003), detailed GPS survey (Brasington et al, 2000), LiDAR (Glenn et al, 2006;Notebaert et al, 2009;Mitasova et al, 2009) as well as combinations of these techniques and consideration of the associated potential errors (Lim et al, 2005;Dewitte et al, 2008;Milledge et al, 2009).…”