Using hilltop curvature to derive the spatial distribution of erosion rates

Hurst, Martin D.; Mudd, Simon M.; Walcott, Rachel; Attal, Mikaël; Yoo, Kyungsoo

doi:10.1029/2011jf002057

Cited by 168 publications

(424 citation statements)

References 132 publications

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“…Predicted slope stability, modeled in part as a function of TWI, was assessed by Tarolli and Tarboton (2006), who demonstrated that, for large-scale landsliding, a lidar-derived DEM downsampled to 10 m resolution was more suitable to identify landslide hazard than the highest-resolution data available. This highlights the requirement to consider the scale of the process being studied when selecting the appropriate grid resolution for a study and corresponds to the challenges of selecting the correct size of smoothing window to capture processes on a suitable scale (e.g., Roering et al, 2010, Hurst et al, 2012, and Grieve et al, 2016b.…”

Section: Previous Workmentioning

confidence: 99%

“…However, all such work was performed on high-resolution topography and the impact of grid resolution on these metrics is unknown. Roering et al (2007) and Hurst et al (2012) demonstrated that the curvature of ridgelines measured from high-resolution topography can be used as a proxy for erosion rates in soil-mantled landscapes. This observation has been used in many studies in which cosmogenic radionuclide-derived erosion rates are unavailable (Pelletier et al, 2011;Hurst et al, 2013c, b;Grieve et al, 2016b).…”

Section: Introductionmentioning

confidence: 99%

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How does grid-resolution modulate the topographic expression of geomorphic processes?

et al. 2016

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Abstract. In many locations, our ability to study the processes which shape the Earth are greatly enhanced through the use of high-resolution digital topographic data. However, although the availability of such datasets has markedly increased in recent years, many locations of significant geomorphic interest still do not have highresolution topographic data available. Here, we aim to constrain how well we can understand surface processes through topographic analysis performed on lower-resolution data. We generate digital elevation models from point clouds at a range of grid resolutions from 1 to 30 m, which covers the range of widely used data resolutions available globally, at three locations in the United States. Using these data, the relationship between curvature and grid resolution is explored, alongside the estimation of the hillslope sediment transport coefficient (D, in m 2 yr −1 ) for each landscape. Curvature, and consequently D, values are shown to be generally insensitive to grid resolution, particularly in landscapes with broad hilltops and valleys. Curvature distributions, however, become increasingly condensed around the mean, and theoretical considerations suggest caution should be used when extracting curvature from landscapes with sharp ridges. The sensitivity of curvature and topographic gradient to grid resolution are also explored through analysis of one-dimensional approximations of curvature and gradient, providing a theoretical basis for the results generated using two-dimensional topographic data. Two methods of extracting channels from topographic data are tested. A geometric method of channel extraction that finds channels by detecting threshold values of planform curvature is shown to perform well at resolutions up to 30 m in all three landscapes. The landscape parameters of hillslope length and relief are both successfully extracted at the same range of resolutions. These parameters can be used to detect landscape transience and our results suggest that such work need not be confined to high-resolution topographic data. A synthesis of the results presented in this work indicates that although high-resolution (e.g., 1 m) topographic data do yield exciting possibilities for geomorphic research, many key parameters can be understood in lower-resolution data, given careful consideration of how analyses are performed.

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Section: Previous Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

How does grid-resolution modulate the topographic expression of geomorphic processes?

et al. 2016

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“…1 and includes the possibility of filtering (step 1) and degrading (step 2) the DEM; the effects of both treatments are examined in the discussion. A slope raster is then generated by fitting a polynomial surface to topographic data and taking the derivative of this surface (Hurst et al, 2012;Grieve et al, 2016) (step 3). Steps 4 and 5 are novel algorithms developed in this study to isolate scarps and platforms.…”

Section: Methodsmentioning

confidence: 99%

“…Topographic input data are therefore clipped to the landward limit of the platform, at the discretion of the user. In the preparation stage, local slope is calculated from the DEM by fitting a second-order polynomial surface (Hurst et al, 2012) with a window radius of 3 times the horizontal resolution of the DEM, selected because it is the minimum radius needed to calculate slope with this method. The DEM may be passed through a Wiener filter (Wiener, 1949;Robinson and Treitel, 1967) to reduce noise from lidar datasets and/or degraded by averaged subsampling before the determination of slope to match complementary datasets.…”

Section: Preprocessing Topographic Datamentioning

confidence: 99%

Unsupervised detection of salt marsh platforms: a topographic method

2018

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Abstract. Salt marshes filter pollutants, protect coastlines against storm surges, and sequester carbon, yet are under threat from sea level rise and anthropogenic modification. The sustained existence of the salt marsh ecosystem depends on the topographic evolution of marsh platforms. Quantifying marsh platform topography is vital for improving the management of these valuable landscapes. The determination of platform boundaries currently relies on supervised classification methods requiring near-infrared data to detect vegetation, or demands labourintensive field surveys and digitisation. We propose a novel, unsupervised method to reproducibly isolate salt marsh scarps and platforms from a digital elevation model (DEM), referred to as Topographic Identification of Platforms (TIP). Field observations and numerical models show that salt marshes mature into subhorizontal platforms delineated by subvertical scarps. Based on this premise, we identify scarps as lines of local maxima on a slope raster, then fill landmasses from the scarps upward, thus isolating mature marsh platforms. We test the TIP method using lidar-derived DEMs from six salt marshes in England with varying tidal ranges and geometries, for which topographic platforms were manually isolated from tidal flats. Agreement between manual and unsupervised classification exceeds 94 % for DEM resolutions of 1 m, with all but one site maintaining an accuracy superior to 90 % for resolutions up to 3 m. For resolutions of 1 m, platforms detected with the TIP method are comparable in surface area to digitised platforms and have similar elevation distributions. We also find that our method allows for the accurate detection of local block failures as small as 3 times the DEM resolution. Detailed inspection reveals that although tidal creeks were digitised as part of the marsh platform, unsupervised classification categorises them as part of the tidal flat, causing an increase in false negatives and overall platform perimeter. This suggests our method may benefit from combination with existing creek detection algorithms. Fallen blocks and high tidal flat portions, associated with potential pioneer zones, can also lead to differences between our method and supervised mapping. Although pioneer zones prove difficult to classify using a topographic method, we suggest that these transition areas should be considered when analysing erosion and accretion processes, particularly in the case of incipient marsh platforms. Ultimately, we have shown that unsupervised classification of marsh platforms from high-resolution topography is possible and sufficient to monitor and analyse topographic evolution.

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“…In the preparation stage, local slope is calculated from the DEM by fitting a second order polynomial surface (Hurst et al, 2012) with a circular window radius equal to three times the horizontal resolution of the DEM. The DEM may be passed through a Wiener filter (Wiener, 1949;Robinson and Treitel, 1967) to reduce noise from lidar datasets and/or degraded by averaged subsampling 20 before the determination of slope to match complementary datasets.…”

Section: Preprocessing Topographic Datamentioning

confidence: 99%

Unsupervised detection of salt marsh platforms: a topographic method

Goodwin¹,

Mudd²,

Clubb³

2017

Preprint

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Abstract.Salt marshes filter pollutants, protect coastlines against storm surges, and sequester carbon, yet are under threat from sea level rise and anthropogenic modification. The productivity and even survival of salt marsh vegetation depends on the topographic evolution of marsh platforms. Quantifying marsh platform topography is vital for improving the management of these valuable landscapes. Determining platform boundaries currently relies on supervised classification methods requiring near-infrared data 5 to detect vegetation, or demands labor-intensive field surveys and digitization. We propose a novel, unsupervised method to reproducibly isolate saltmarsh scarps and platforms from a DEM, referred to as Topographic Identification of Platforms (TIP).Field observations and numerical models show that saltmarshes mature into sub-horizontal platforms delineated by sub-vertical scarps: based on this premise, we identify scarps as lines of local maxima on a slope raster, then fill landmasses from the scarps upward, thus isolating mature marsh platforms. We test the TIP method using lidar-derived DEMs from six saltmarshes in 10England with varying tidal ranges and geometries, for which topographic platforms were manually distinguished from tidal flats. Agreement between manual and unsupervised classification exceeds 94% for DEM resolutions of 1 m, with all but one sites maintaining an accuracy superior to 90% for resolutions up to 3 m. For resolutions of 1 m, platforms detected with the TIP method are comparable in surface area to digitized platforms, and have similar elevation distributions. We also find that our method allows the accurate detection of local bloc failures as small as 3 times the DEM resolution. Detailed inspection 15 reveals that although tidal creeks were digitized as part of the marsh platform, unsupervised classification categorizes them as part of the tidal flat, causing an increase in false negatives and overall platform perimeter. This suggests our method would have increased accuracy if used in combination with existing creek detection algorithms. Fallen blocs and high tidal flat portions, associated with potential pioneer zones, may also be areas of discordance between our method and supervised mapping.Although pioneer zones prove difficult to classify using a topographic method, it also suggests that these transition areas 20 should be considered when analysing erosion and accretion processes, particularly in the case of incipient marsh platforms.Ultimately, we have shown that unsupervised classification of marsh platforms from high-resolution topography is possibleand sufficient to monitor and analyze topographic evolution.

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Using hilltop curvature to derive the spatial distribution of erosion rates

Cited by 168 publications

References 132 publications

How does grid-resolution modulate the topographic expression of geomorphic processes?

How does grid-resolution modulate the topographic expression of geomorphic processes?

Unsupervised detection of salt marsh platforms: a topographic method

Unsupervised detection of salt marsh platforms: a topographic method

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