A Technique for Assessing Land Surface Ruggedness

Beasom, Samuel L.; Wiggers, Ernie P.; Giardino, John R.

doi:10.2307/3808184

Cited by 58 publications

(39 citation statements)

References 3 publications

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“…Whilst surface roughness remains the most common generic term, a variety of terminology have been applied to its study, including ruggedness Beasom et al (1983); Washtell et al (2009) (2004); Wilson et al (2007), microrelief Stone and Dugundji (1965) or microtopography Herzfeld et al (2000). Throughout this article, we use the term surface roughness as an expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest, either local or regional.…”

Section: Introductionmentioning

confidence: 99%

Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland

Grohmann

Smith

Riccomini

2011

IEEE Trans. Geosci. Remote Sensing

252

196

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Surface roughness is an important geomorphological variable which has been used in the earth and planetary sciences to infer material properties, current/past processes and the time elapsed since formation. No single definition exists, however within the context of geomorphometry we use surface roughness as a expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest. Six techniques for the calculation of surface roughness were selected for an assessment of the parameter's behaviour at different spatial scales and dataset resolutions. Area ratio operated independently of scale, providing consistent results across spatial resolutions. Vector dispersion produced results with increasing roughness and homogenisation of terrain at coarser resolutions and larger window sizes. Standard deviation of residual topography tends to highlight local features and doesn't detect regional relief. Standard deviation of elevation correctly identified breaks-of-slope and was good at detecting regional relief. Standard deviation of slope (SDslope) also correctly identified smooth sloping areas and breaks-of-slope, providing the best results for geomorphological analysis. Standard deviation of profile curvature identified the breaks-of-slope, although not as strongly as SDslope and it is very sensitive to noise and spurious data. In general, SDslope offered good performance at a variety of scales, whilst the simplicity of calculation is perhaps its single greatest benefit.

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Section: Introductionmentioning

confidence: 99%

Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland

Grohmann

Smith

Riccomini

2011

IEEE Trans. Geosci. Remote Sensing

252

196

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“…Topography is an important ecological component affecting the distribution of wildlife and vegetation (Beasom et al, 1983). This is particularly true for alpine and arctic environments, where vegetation and snow patterns respond to even minor changes in relief (Shaver et al, 1990;Hall et al, 1991).…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Terrain Ruggedness in Reindeer Winter Grounds

Nellemann¹,

Fry²

1995

ARCTIC

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ABSTRACT. We report a distinct terrain structure in high-use portions of reindeer (Rangifer tarandus tarandus) winter grounds for two regions within Norway. A new index of terrain ruggedness based on topographic maps was used for analyzing terrain structure within historic high-and low-use portions of wintering areas. Terrain ruggedness was found to be significantly higher in high-use areas. Indices of terrain ruggedness reflecting fine-scale features (10 -20 m) corresponded well with the availability of potential feeding sites (< 40 cm snow depth), while contour densities alone did not. Terrain structure should be considered an important habitat attribute for management planning on reindeer winter habitats. The index provides a simple method for quantifying differences in fine-scale ruggedness between habitats.

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“…Hobson described some early computational methods for estimating surface area and discussed the concept of surface area ratios [23]. Beasom et al described a method for estimating land surface ruggedness based on the intersections of sample points and contour lines [24], and Jenness described a similar method based on measuring the density of contour lines [3]. Mandelbrot et al described the concept of "fractal dimension" in which the dimension of an irregular surface lies between 2 and 3 [25], and a series of publications discussed a variety of methods for estimating the fractal dimension for a landscape [26,27].…”

Section: Overlay-based Surface Area Estimationmentioning

confidence: 99%

A Stream Tilling Approach to Surface Area Estimation for Large Scale Spatial Data in a Shared Memory System

et al. 2017

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Surface area estimation is a widely used tool for resource evaluation in the physical world. When processing large scale spatial data, the input/output (I/O) can easily become the bottleneck in parallelizing the algorithm due to the limited physical memory resources and the very slow disk transfer rate. In this paper, we proposed a stream tilling approach to surface area estimation that first decomposed a spatial data set into tiles with topological expansions. With these tiles, the one-to-one mapping relationship between the input and the computing process was broken. Then, we realized a streaming framework towards the scheduling of the I/O processes and computing units. Herein, each computing unit encapsulated a same copy of the estimation algorithm, and multiple asynchronous computing units could work individually in parallel. Finally, the performed experiment demonstrated that our stream tilling estimation can efficiently alleviate the heavy pressures from the I/O-bound work, and the measured speedup after being optimized have greatly outperformed the directly parallel versions in shared memory systems with multi-core processors.

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A Technique for Assessing Land Surface Ruggedness

Cited by 58 publications

References 3 publications

Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland

Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland

Quantitative Analysis of Terrain Ruggedness in Reindeer Winter Grounds

A Stream Tilling Approach to Surface Area Estimation for Large Scale Spatial Data in a Shared Memory System

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