Towards a general theory of control point distribution effects in trend-surface models

Unwin, David; Wrigley, Neil

doi:10.1016/0098-3004(87)90007-0

Cited by 33 publications

(3 citation statements)

References 9 publications

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“…The influence of the distribution of the GCPs on the results has been analyzed in different studies [20][21][22], which indicate that the points at the edges of the image are particularly important in obtaining a better fitting. A sufficiently regular grid of points distributed over the entire image achieved good results, although the outside points are more influential in the overall goodness of the adjustment than the inner points [20].…”

Section: Variables That Affect the Generation Of A Demmentioning

confidence: 99%

Optimal Parameters for DEM Extraction from IKONOS data: A case Study of a Coastal Area

Docampo¹,

Arza-García²

2017

Geoinfor Geostat: An Overview

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The gap between aerial and satellite photogrammetry is getting smaller as both systems have benefited from great technology improvements in the last years. However, the major advantage of earth observation satellites continues to be the possibility to acquire data virtually anywhere on the planet without considering border and logistical restrictions and over huge extensions. A pair of stereo images corresponding to a coastal area in the NW of Spain is the basis for this paper, which analyzes certain influential variables in the process of generating a Digital Elevation Model (DEM) from stereoscopic pairs of IKONOS images. The mathematical model, the number of Ground Control Points (GCPs) and their accuracies are analyzed through a sequence of experimental trials. Two main methods are applied for math modeling: a CCRS model (rigorous model) and a Rational Functions model. The influence of the GCPs' positional quality is compared using two different information sources: points measured in 1:5,000 cartography and points surveyed via GPS. The number of GCPs tested varies between 0 and 20. Using different configurations of these variables, 17 models are generated. The best results are achieved with the rigorous model and 16 GCPs measured with GPS with an RMSE of 1.01 m (or an LE95 -Linear Error in Z at 95% confidence level-of 2 m), which is approximately the pixel size of the initial pair. The mathematical model was determined to be the variable with the most influence on accuracy. Moreover, the results suggest that the use of 10-16 GCPs is sufficient. Additional points do not improve the DEM accuracy or may even worsen it in certain cases. Although the study is carried out in a coastal zone, which restricts the GCPs' distribution possibilities, the results are comparable with similar results from inland areas.

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Section: Variables That Affect the Generation Of A Demmentioning

confidence: 99%

Optimal Parameters for DEM Extraction from IKONOS data: A case Study of a Coastal Area

Docampo¹,

Arza-García²

2017

Geoinfor Geostat: An Overview

View full text Add to dashboard Cite

show abstract

“…332-333). For example, the fit of a trend surface model can be influenced by the configuration of the sample data points on the surface where, as a result of the particular distribution, certain values have high leverage (Unwin and Wrigley, 1987); the particular shape of the study region may also influence the trend surface model fit (Haining, 1990, p. 372). These and other issues are reviewed in Haining (1990, pp.…”

Section: Andmentioning

confidence: 99%

The Special Nature of Spatial Data

Haining¹

2009

The SAGE Handbook of Spatial Analysis

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“…"Dahlberg has shown that, where there are many data points providing good control for the interpolation process, ..." (p. 183) in some ways ignores the important point here; Unwin and Wrigley [8] explore this question applying leverage analysis to trend surface models, while Anselin and Griffith [1 ] examine this issue within the context of interpreting standard statistical and econometric diagnostics. Since many location-allocation solutions are based upon heuristics, mostly because of problem size coupled with hardware and software constraints (presumably these will become increasingly less restrictive with the passing of time), the optimality sought remains unknown.…”

Section: The Relationship Between This Formulation and Equation (29)mentioning

confidence: 99%

Geographical Systems and Systems of Geography

Griffith¹,

Coffey²

1988

Economic Geography

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Towards a general theory of control point distribution effects in trend-surface models

Cited by 33 publications

References 9 publications

Optimal Parameters for DEM Extraction from IKONOS data: A case Study of a Coastal Area

Optimal Parameters for DEM Extraction from IKONOS data: A case Study of a Coastal Area

The Special Nature of Spatial Data

Geographical Systems and Systems of Geography

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