
Agricultural and Biosystems Engineering Publications
Campus Units
Agricultural and Biosystems Engineering
Document Type
Article
Publication Version
Published Version
Publication Date
4-2017
Journal or Book Title
Boletim de Ciências Geodésicas
Volume
23
Issue
2
First Page
296
Last Page
308
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.
Access
Open
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
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
Copyright Date
2017
Language
en
File Format
application/pdf
Recommended Citation
Trancoso Santos, Adriana Maria Rocha; dos Santos, Gerson Rodrigues; Emiliano, Paulo César; das Graças Medeiros, Nilcilene; Kaleita, Amy L.; and de Oliveira Serrano Pruski, Lígia, "Detection of inconsistencies in geospatial data with geostatistics" (2017). Agricultural and Biosystems Engineering Publications. 825.
https://lib.dr.iastate.edu/abe_eng_pubs/825
Comments
This article is from Bol. Ciênc. Geod. vol.23 no.2 Curitiba Apr./June 2017, http://dx.doi.org/10.1590/s1982-21702017000200019.