Stochastic simulation models to internally validate analytical error models of a point and a line segment in GIS

Sungchul Hong, Joon Heo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An error model in GIS is used to characterize positional errors in spatial data and to propagate the errors through spatial processes. Generally, there are two distinctive approaches for modeling positional errors in the spatial data: analytical and simulation. Analytical and simulation error models have the ability to describe (or realize) error-corrupted versions of spatial data. But the different approaches for modeling positional errors require internal validation that ascertains whether the analytical and simulation error models predict correct positional errors in a defined set of conditions. This paper presents stochastic simulation models of a point and a line segment to validate analytical error models, which are an error ellipse and an advanced error band model, respectively. The simulation error models populate positional errors by the Monte Carlo simulation, according to an assumed error distribution prescribed by given parameters of a variance-covariance matrix. In the validation process, a set of positional errors by the simulation models is compared to a theoretical description by the analytical error models. Results show that the proposed simulation models realize positional uncertainties of the same spatial data according to a defined level of positional quality.

Original languageEnglish
Title of host publication32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Pages786-790
Number of pages5
Publication statusPublished - 2011 Dec 1
Event32nd Asian Conference on Remote Sensing 2011, ACRS 2011 - Tapei, Taiwan, Province of China
Duration: 2011 Oct 32011 Oct 7

Publication series

Name32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Volume2

Other

Other32nd Asian Conference on Remote Sensing 2011, ACRS 2011
CountryTaiwan, Province of China
CityTapei
Period11/10/311/10/7

Fingerprint

Geographic information systems
Covariance matrix

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Hong, S., & Heo, J. (2011). Stochastic simulation models to internally validate analytical error models of a point and a line segment in GIS. In 32nd Asian Conference on Remote Sensing 2011, ACRS 2011 (pp. 786-790). (32nd Asian Conference on Remote Sensing 2011, ACRS 2011; Vol. 2).
Hong, Sungchul ; Heo, Joon. / Stochastic simulation models to internally validate analytical error models of a point and a line segment in GIS. 32nd Asian Conference on Remote Sensing 2011, ACRS 2011. 2011. pp. 786-790 (32nd Asian Conference on Remote Sensing 2011, ACRS 2011).
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Hong, S & Heo, J 2011, Stochastic simulation models to internally validate analytical error models of a point and a line segment in GIS. in 32nd Asian Conference on Remote Sensing 2011, ACRS 2011. 32nd Asian Conference on Remote Sensing 2011, ACRS 2011, vol. 2, pp. 786-790, 32nd Asian Conference on Remote Sensing 2011, ACRS 2011, Tapei, Taiwan, Province of China, 11/10/3.

Stochastic simulation models to internally validate analytical error models of a point and a line segment in GIS. / Hong, Sungchul; Heo, Joon.

32nd Asian Conference on Remote Sensing 2011, ACRS 2011. 2011. p. 786-790 (32nd Asian Conference on Remote Sensing 2011, ACRS 2011; Vol. 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Hong S, Heo J. Stochastic simulation models to internally validate analytical error models of a point and a line segment in GIS. In 32nd Asian Conference on Remote Sensing 2011, ACRS 2011. 2011. p. 786-790. (32nd Asian Conference on Remote Sensing 2011, ACRS 2011).