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Propagation of vertical and horizontal source data errors into a TIN with linear interpolation

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Propagation of vertical and horizontal source data errors into a TIN with linear interpolation. / Fan, Lei; Smethurst, Joel A.; Atkinson, Peter M. et al.
In: International Journal of Geographical Information Science, Vol. 28, No. 7, 07.2014, p. 1378-1400.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Fan, L, Smethurst, JA, Atkinson, PM & Powrie, W 2014, 'Propagation of vertical and horizontal source data errors into a TIN with linear interpolation', International Journal of Geographical Information Science, vol. 28, no. 7, pp. 1378-1400. https://doi.org/10.1080/13658816.2014.889299

APA

Fan, L., Smethurst, J. A., Atkinson, P. M., & Powrie, W. (2014). Propagation of vertical and horizontal source data errors into a TIN with linear interpolation. International Journal of Geographical Information Science, 28(7), 1378-1400. https://doi.org/10.1080/13658816.2014.889299

Vancouver

Fan L, Smethurst JA, Atkinson PM, Powrie W. Propagation of vertical and horizontal source data errors into a TIN with linear interpolation. International Journal of Geographical Information Science. 2014 Jul;28(7):1378-1400. Epub 2014 Mar 24. doi: 10.1080/13658816.2014.889299

Author

Fan, Lei ; Smethurst, Joel A. ; Atkinson, Peter M. et al. / Propagation of vertical and horizontal source data errors into a TIN with linear interpolation. In: International Journal of Geographical Information Science. 2014 ; Vol. 28, No. 7. pp. 1378-1400.

Bibtex

@article{119fbe03a45440ca872409fe37c60c7c,
title = "Propagation of vertical and horizontal source data errors into a TIN with linear interpolation",
abstract = "Digital elevation models (DEMs) have been widely used for a range of applications and form the basis of many GIS-related tasks. An essential aspect of a DEM is its accuracy, which depends on a variety of factors, such as source data quality, interpolation methods, data sampling density and the surface topographical characteristics. In recent years, point measurements acquired directly from land surveying such as differential global positioning system and light detection and ranging have become increasingly popular. These topographical data points can be used as the source data for the creation of DEMs at a local or regional scale. The errors in point measurements can be estimated in some cases. The focus of this article is on how the errors in the source data propagate into DEMs. The interpolation method considered is a triangulated irregular network (TIN) with linear interpolation. Both horizontal and vertical errors in source data points are considered in this study. An analytical method is derived for the error propagation into any particular point of interest within a TIN model. The solution is validated using Monte Carlo simulations and survey data obtained from a terrestrial laser scanner.",
keywords = "error propagation, DEM accuracy, triangulated irregular network, spatial interpolation, topographical survey",
author = "Lei Fan and Smethurst, {Joel A.} and Atkinson, {Peter M.} and William Powrie",
note = "M1 - 7",
year = "2014",
month = jul,
doi = "10.1080/13658816.2014.889299",
language = "English",
volume = "28",
pages = "1378--1400",
journal = "International Journal of Geographical Information Science",
issn = "1365-8816",
publisher = "Taylor and Francis Ltd.",
number = "7",

}

RIS

TY - JOUR

T1 - Propagation of vertical and horizontal source data errors into a TIN with linear interpolation

AU - Fan, Lei

AU - Smethurst, Joel A.

AU - Atkinson, Peter M.

AU - Powrie, William

N1 - M1 - 7

PY - 2014/7

Y1 - 2014/7

N2 - Digital elevation models (DEMs) have been widely used for a range of applications and form the basis of many GIS-related tasks. An essential aspect of a DEM is its accuracy, which depends on a variety of factors, such as source data quality, interpolation methods, data sampling density and the surface topographical characteristics. In recent years, point measurements acquired directly from land surveying such as differential global positioning system and light detection and ranging have become increasingly popular. These topographical data points can be used as the source data for the creation of DEMs at a local or regional scale. The errors in point measurements can be estimated in some cases. The focus of this article is on how the errors in the source data propagate into DEMs. The interpolation method considered is a triangulated irregular network (TIN) with linear interpolation. Both horizontal and vertical errors in source data points are considered in this study. An analytical method is derived for the error propagation into any particular point of interest within a TIN model. The solution is validated using Monte Carlo simulations and survey data obtained from a terrestrial laser scanner.

AB - Digital elevation models (DEMs) have been widely used for a range of applications and form the basis of many GIS-related tasks. An essential aspect of a DEM is its accuracy, which depends on a variety of factors, such as source data quality, interpolation methods, data sampling density and the surface topographical characteristics. In recent years, point measurements acquired directly from land surveying such as differential global positioning system and light detection and ranging have become increasingly popular. These topographical data points can be used as the source data for the creation of DEMs at a local or regional scale. The errors in point measurements can be estimated in some cases. The focus of this article is on how the errors in the source data propagate into DEMs. The interpolation method considered is a triangulated irregular network (TIN) with linear interpolation. Both horizontal and vertical errors in source data points are considered in this study. An analytical method is derived for the error propagation into any particular point of interest within a TIN model. The solution is validated using Monte Carlo simulations and survey data obtained from a terrestrial laser scanner.

KW - error propagation

KW - DEM accuracy

KW - triangulated irregular network

KW - spatial interpolation

KW - topographical survey

U2 - 10.1080/13658816.2014.889299

DO - 10.1080/13658816.2014.889299

M3 - Journal article

VL - 28

SP - 1378

EP - 1400

JO - International Journal of Geographical Information Science

JF - International Journal of Geographical Information Science

SN - 1365-8816

IS - 7

ER -