Terrain complexity and uncertainties in grid‐based digital terrain analysis

Zhou, Qiming; Liu, Xuejun; Sun, Yizhong

doi:10.1080/13658810600816573

Cited by 39 publications

(27 citation statements)

References 16 publications

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“…It is noted that the terrain of Scotland is more complex and higher than the terrain of England and Wales, because the terrain complexity index of Scotland is larger (Zhou, Liu et al 2006, Lu, Liu et al 2007). …”

Section: Analysis and Discussionmentioning

confidence: 99%

Icesat Validation of Tandem-X I-Dems Over the Uk

Feng¹,

Müller²

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:From the latest TanDEM-X mission (bistatic X-Band interferometric SAR), globally consistent Digital Elevation Model (DEM) will be available from 2017, but their accuracy has not yet been fully characterised. This paper presents the methods and implementation of statistical procedures for the validation of the vertical accuracy of TanDEM-X iDEMs at grid-spacing of approximately 12.5m, 30m and 90m based on processed ICESat data over the UK in order to assess their potential extrapolation across the globe. The accuracy of the TanDEM-X iDEM in UK was obtained as follows: against ICESat GLA14 elevation data, TanDEM-X iDEM has -0.028±3.654m over England and Wales and 0.316±5.286m over Scotland for 12m, -0.073±6.575m for 30m, and 0.0225±9.251m at 90m. Moreover, 90% of all results at the three resolutions of TanDEM-X iDEM data (with a linear error at 90% confidence level) are below 16.2m. These validation results also indicate that derivative topographic parameters (slope, aspect and relief) have a strong effect on the vertical accuracy of the TanDEM-X iDEMs. In high-relief and large slope terrain, large errors and data voids are frequent, and their location is strongly influenced by topography, whilst in the low-to medium-relief and low slope sites, errors are smaller. ICESat derived elevations are heavily influenced by surface slope within the 70m footprint as well as there being slope dependent errors in the TanDEM-X iDEMs.

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Section: Analysis and Discussionmentioning

confidence: 99%

Icesat Validation of Tandem-X I-Dems Over the Uk

Feng¹,

Müller²

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…The positive correlation of error and slope has been shown in numerous studies, e.g. Hunter and Goodchild (1997), Veregin (1997) and Fisher (1998); yet on mathematical surfaces (synthetic DEMs) smoother, flatter areas generate a greater amount of uncertainty in their derived parameters (Zhou, Liu, & Sun, 2006). However, a more recent study by Holmes et al (2000) found only a weak correlation between calculated DEM error and various terrain attributes.…”

Section: Spatial Dependency and Variabilitymentioning

confidence: 91%

Improving user assessment of error implications in digital elevation models

Darnell

Tate

Brunsdon

2008

Computers, Environment and Urban Systems

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a b s t r a c tA digital representation of a terrain surface is an approximation of reality and is inherently prone to some degree of error and uncertainty. Research in uncertainty analysis has produced a vast range of methods for investigating error and its propagation. However, the complex and varied methods proposed by researchers and academics create ambiguity for the dataset user. In this study, existing methods are combined and simplified to present a prototype tool to enable any digital elevation model (DEM) user to access and apply uncertainty analysis. The effect of correlated gridded DEM error is investigated, using stochastic conditional simulation to generate multiple equally likely representations of an actual terrain surface. Propagation of data uncertainty to the slope derivative, and the impact on a landslide susceptibility model are assessed. Two frameworks are developed to examine the probable and possible uncertainties in classifying the landslide hazard: probabilistic and fuzzy. The entire procedure is automated using publicly available software and user requirements are minimised. A case study example shows the resultant code can be used to quantify, visualise and demonstrate the propagation of error in a DEM. As a tool for uncertainty analysis the method can improve user assessment of error and its implications.

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“…They found a systematic increase in soil loss estimations with increasing cell size at hillslope scale, while differences at catchment scale were less pronounced. Also terrain complexity is likely to affect the quality of DEM derivatives, as Zhou et al (2006) found that the Root Mean Square Error (RMSE) of derived aspect and slope is negatively correlated with slope steepness in complex terrain. Both the stream power induced bedrock incision concept (e.g.…”

Section: Introductionmentioning

confidence: 97%