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Article
Detection of inconsistencies in geospatial data with geostatistics
Boletim de Ciências Geodésicas
  • Adriana Maria Rocha Trancoso Santos, Universidade Federal de Viçosa
  • Gerson Rodrigues dos Santos, Universidade Federal de Viçosa
  • Paulo César Emiliano, Universidade Federal de Viçosa
  • Nilcilene das Graças Medeiros, Universidade Federal de Viçosa
  • Amy L. Kaleita, Iowa State University
  • Lígia de Oliveira Serrano Pruski, Universidade Federal de Viçosa
Document Type
Article
Publication Version
Published Version
Publication Date
4-1-2017
DOI
10.1590/s1982-21702017000200019
Abstract

Almost every researcher has come through observations that “drift” from the rest of the sample, suggesting some inconsistency. The aim of this paper is to propose a new inconsistent data detection method for continuous geospatial data based in Geostatistics, independently from the generative cause (measuring and execution errors and inherent variability data). The choice of Geostatistics is based in its ideal characteristics, as avoiding systematic errors, for example. The importance of a new inconsistent detection method proposal is in the fact that some existing methods used in geospatial data consider theoretical assumptions hardly attended. Equally, the choice of the data set is related to the importance of the LiDAR technology (Light Detection and Ranging) in the production of Digital Elevation Models (DEM). Thus, with the new methodology it was possible to detect and map discrepant data. Comparing it to a much utilized detections method, BoxPlot, the importance and functionality of the new method was verified, since the BoxPlot did not detect any data classified as discrepant. The proposed method pointed that, in average, 1,2% of the data of possible regionalized inferior outliers and, in average, 1,4% of possible regionalized superior outliers, in relation to the set of data used in the study.

Comments

This article is from Bol. Ciênc. Geod. vol.23 no.2 Curitiba Apr./June 2017, http://dx.doi.org/10.1590/s1982-21702017000200019.

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Open
Creative Commons License
Creative Commons Attribution 4.0
Copyright Owner
Adriana Maria Rocha Trancoso Santos, Gerson Rodrigues dos Santos, Paulo César Emiliano, Nilcilene das Graças Medeiros, Amy L. Kaleita, Lígia de Oliveira Serrano Pruski
Language
en
File Format
application/pdf
Citation Information
Adriana Maria Rocha Trancoso Santos, Gerson Rodrigues dos Santos, Paulo César Emiliano, Nilcilene das Graças Medeiros, et al.. "Detection of inconsistencies in geospatial data with geostatistics" Boletim de Ciências Geodésicas Vol. 23 Iss. 2 (2017) p. 296 - 308
Available at: http://works.bepress.com/amy_kaleita/62/