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Journal ArticleDOI

A general framework for error analysis in measurement-based GIS Part 1: The basic measurement-error model and related concepts

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TLDR
A simple but general model for ME in MBGIS is introduced and an approximate law of error propagation is formulated, and a simple, unified, and effective treatment of error bands for a line segment is made under the name of “covariance-based error band”.
Abstract
This is the first of a four-part series of papers which proposes a general framework for error analysis in measurement-based geographical information systems (MBGIS). The purpose of the series is to investigate the fundamental issues involved in measurement error (ME) analysis in MBGIS, and to provide a unified and effective treatment of errors and their propagation in various interrelated GIS and spatial operations. Part 1 deals with the formulation of the basic ME model together with the law of error propagation. Part 2 investigates the classic point-in-polygon problem under ME. Continuing to Part 3 is the analysis of ME in intersections and polygon overlays. In Part 4, error analyses in length and area measurements are made. In this present part, a simple but general model for ME in MBGIS is introduced. An approximate law of error propagation is then formulated. A simple, unified, and effective treatment of error bands for a line segment is made under the name of “covariance-based error band”. A new concept, called “maximal allowable limit”, which guarantees invariance in topology or geometric-property of a polygon under ME is also advanced. To handle errors in indirect measurements, a geodetic model for MBGIS is proposed and its error propagation problem is studied on the basis of the basic ME model as well as the approximate law of error propagation. Simulation experiments all substantiate the effectiveness of the proposed theoretical construct.

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Citations
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Journal ArticleDOI

Imaged-based verification of as-built documentation of operational buildings

TL;DR: In this article, the advantages and limitations of using photogrammetric image processing to document and verify actual as-built conditions are investigated, and the potential of the image-based spatial data is assessed for accurately generating 3D models.
Journal ArticleDOI

Sample surveying to estimate the mean of a heterogeneous surface: reducing the error variance through zoning

TL;DR: The study shows that zoning improves estimator efficiency when sampling a heterogeneous surface and provides rules of thumb for choice of sample design, sample statistics and uncertainty estimation, based on considering different spatial heterogeneities on real surfaces.
Book ChapterDOI

A Functional Ontology of Observation and Measurement

TL;DR: An ontology of observation and measurement is proposed, which models the relevant information processes independently of sensor technology, and establishes the ontological basis for these as well as other extensions.
Journal ArticleDOI

Error in target-based georeferencing and registration in terrestrial laser scanning

TL;DR: This paper demonstrates that statistics used routinely to describe the registration accuracy are incompetent measures of the actual registration and georeferencing errors in TLS data and, thus, should no longer be used in practice and are of use for subsequent analysis of the uncertainty in TLS datasets.
References
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Book

Statistics for spatial data

TL;DR: In this paper, the authors present a survey of statistics for spatial data in the field of geostatistics, including spatial point patterns and point patterns modeling objects, using Lattice Data and spatial models on lattices.
Journal ArticleDOI

Statistics for Spatial Data, Revised Edition.

Noel A Cressie
- 01 Mar 1994 - 
TL;DR: This chapter discusses how to make practical use of spatial statistics in day-to-day analytical work, and some examples from the scientific literature suggest a straightforward and efficient way to do this.
Book

Error Propagation in Environmental Modelling with GIS

TL;DR: An error model for quantitative spatial attributes identification of the error model - a case study error propagation with local GIS operations - the use of multidimensional simulation implementation of error propagation techniques in GIS.
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