Characterizing arid region alluvial fan surface roughness with airborne laser swath mapping digital topographic data

Frankel, Kurt L.; Dolan, James F.

doi:10.1029/2006jf000644

Cited by 185 publications

(190 citation statements)

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“…Several authors define surface roughness in terms of the variability of elevation values, generally expressed as the absolute standard deviation of all values within a window, or as the deviation from a best-fit plane. It has been applied to data such as raw elevation points Hobson (1972), DEMs Evans (1984); Haneberg et al (2005); Glenn et al (2006);Frankel and Dolan (2007); Arrell and Carver (2009), satellite imagery Beyer et al (2003); Cord et al (2007), bathymetric data Dartnell and Gardner (2004); Valentine et al (2004); Lundblad et al (2006); Wilson et al (2007) or elevation profiles Van Der Veen et al (1998); Kreslavsky and Head (2000); Shepard et al (2001). Standard deviation of residual topography was used as a measure of roughness by Haneberg et al (2005); Haneberg (2007); Cavalli et al (2008), where the residual topography is the difference between the original and a smoothed DEM (an approach similar to the deviation of values from a best-fit plane).…”

Section: Measures Of Surface Roughnessmentioning

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: Measures Of Surface Roughnessmentioning

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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“…Nos ambientes áridos a ocorrência de eventos pluviométricos em períodos curtos e geralmente intensos, pode potencializar as características de erosão. Assim, os sedimentos erodidos são depositados em locais com topografia favorável a cada evento chuvoso, que é um fenômeno comumente chamado gerações múltiplas de superfícies aluvionais (Frankel & Dolan, 2007). Em razão da importância desses sedimentos observa-se a necessidade de se estabelecer uma metodologia para seu mapeamento por meio de técnicas espaciais utilizando-se dados de imagens de satélite, fotografias aéreas, radar e GPS.…”

Section: Introductionunclassified

“…Gellispie et al (1984) propuseram interpretação baseada em bandas termais, dados de campo, estudos espectroscópicos e mapas geológicos. Frankel & Dolan (2007) mapearam leques aluvionares por meio de laser utilizando a técnica de rugosidade da superfície extraída de dados de topografia digital.…”

Section: Introductionunclassified

“…Técnicas de campo com inspeção e levantamento topográfico consomem tempo e são laboriosas e possuem limitação espacial; logo, são mais aplicadas para pequeno segmento de determinada unidade de aluvião (Frankel & Dolan, 2007). Uma alternativa são as imagens de alta resolução e o mapeamento a Laser (conhecido como LiDAR -Light Detection and Ranging).…”

Section: Introductionunclassified

“…Uma alternativa são as imagens de alta resolução e o mapeamento a Laser (conhecido como LiDAR -Light Detection and Ranging). Essas tecnologias têm renovado o interesse para caracterização quantitativa de tipos de terreno aluvial e coluvial (Glenn et al, 2006;Staley et al, 2006;Gaber et al, 2010;Frankel & Dolan, 2007) porém apresentam custos elevados em relação às imagens de satélite de média resolução. Amit et al (1996) observaram, em aluviões, diferenças no grau de desenvolvimento do solo principalmente onde há maior gradiente.…”

Section: Introductionunclassified

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Mapeamento de áreas aluvionares no semiárido brasileiro por meio de dados colaterais e imagens orbitais

Lopes

Cabral²,

Filho

et al. 2013

Rev. bras. eng. agríc. ambient.

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RESUMOA região semiárida do Brasil possui grande potencial para armazenamento de água em áreas aluvionares, podendo potencializar a pequena agricultura. Verifica-se a necessidade de uma metodologia para mapeamento dessas áreas, com o objetivo de futuros estudos in loco para implantação de barragens subterrâneas e manejo correto dos solos aluvionares. Neste sentido, objetivou-se a aplicação de imagens Landsat-Mapeador Temático 5 em conjunto com dados colaterais, como a rede de drenagem, mapa de classes de solo e mapa de relevo para auxiliar na classificação de terraços aluviais. Teve-se, como área de estudo, a bacia do Rio Pajeú, no sertão do estado de Pernambuco. Buscou-se também, por meio de dados SRTM (Shuttle Radar Topography Mission), a avaliação topográfica das áreas classificadas. Verifica-se que a utilização única de dados orbitais traz classificação incongruente mas com a inserção de dados colaterais é possível obter melhores resultados na classificação. A rede de drenagem é fundamental no mascaramento de classificações espúrias. Quando procede à análise topográfica por meio de dados do SRTM das áreas classificadas como terraços aluvionares, observa-se a inconsistência desses dados. Palavras-chave: solos aluviais, classificação supervisionada, sensoriamento remoto, relevoMapping alluvial areas in semi-arid region of Brazil through collateral data and satellite images ABSTRACT The semi-arid region of Brazil has great potential for storing water in alluvial areas, and may give support to small-scale family farming. There is a need to establish a methodology for mapping these areas with the objective of future studies to implement underground dams and suitable management of the soils that occur on alluvial terraces. In this way, the aim of this study was to apply Landsat-Thematic Mapper images together with collateral data such as the drainage network, map of soil classes and elevation data to assist in the classification of alluvial terraces. The study area was Pajeú River basin located in the 'Caatinga' ecosystem of the Pernambuco state. Topographic assessment of the alluvial areas was done by using SRTM (Shuttle Radar Topography Mission) data. It was found that the single use of orbital data brings incongruous classification, but with the inclusion of collateral data it was possible to obtain better results in classification. The drainage network was also important in masking the spurious classification. The analysis of the topography of the classified areas was inadequate using SRTM data.

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Mapping Quaternary alluvial fans in the southwestern United States based on multiparameter surface roughness of lidar topographic data

2014

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[1] Quaternary alluvial fans have diverse surface morphologies related to both depositional and weathering processes. Numerous studies have demonstrated that the surface expression and morphometry of alluvial fans can be used as an indicator of their relative age of deposition, but only recently has there been an effort to utilize high-resolution topographic data to differentiate alluvial fans by surface age with automated and quantifiable routines. We developed a quantitative model for mapping the relative age of alluvial fan surfaces based on multiparameter surface roughness values computed from 1 m resolution lidar topographic data. Roughness is defined as a function of observational scale and integration of slope, curvature, and aspect topographic parameters. Alluvial fan roughness values were computed across multiple observation scales (3 × 3 m to 150 × 150 m) based on the standard deviation (SD) of slope, curvature (tangential), and aspect topographic parameters. Plots of roughness value versus size of observation scale suggest that the SD of each parameter over a 7 × 7 m observation window best identified the signature of surface roughness elements. Roughness maps derived from slope, curvature, and aspect at this scale were integrated using fuzzy logic. The integrated roughness map was then classified into five relative morphostratigraphic surface age categories (active wash to~400 ka) and statistically compared with a similar fivefold surface age map of alluvial fans developed using traditional field surveys and aerial photographic interpretation. The model correctly predicted the distribution and relative surface age of~61% of alluvial fan landforms based on traditional mapping techniques.

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Characterizing arid region alluvial fan surface roughness with airborne laser swath mapping digital topographic data

Cited by 185 publications

References 51 publications

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

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

Mapeamento de áreas aluvionares no semiárido brasileiro por meio de dados colaterais e imagens orbitais

Mapping Quaternary alluvial fans in the southwestern United States based on multiparameter surface roughness of lidar topographic data

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