Thematic quality assessment of land surface geospatial data based on confusion matrices: A matrix set for research on measures and procedures

Abstract The confusion matrix has long been adopted as the ‘de facto’ and ‘de jure’ standard method of reporting on the thematic accuracy assessment of any land surface geospatial dataset. This type of data supports decision‐making in many different fields, so suitable quality is therefore essential...

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Main Authors: Francisco J. Ariza‐López, José L. García‐Balboa, María V. Alba‐Fernández, José Rodríguez‐Avi
Format: Article
Language:English
Published: Wiley 2022-06-01
Series:Geoscience Data Journal
Subjects:
Online Access:https://doi.org/10.1002/gdj3.116
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author Francisco J. Ariza‐López
José L. García‐Balboa
María V. Alba‐Fernández
José Rodríguez‐Avi
author_facet Francisco J. Ariza‐López
José L. García‐Balboa
María V. Alba‐Fernández
José Rodríguez‐Avi
author_sort Francisco J. Ariza‐López
collection DOAJ
description Abstract The confusion matrix has long been adopted as the ‘de facto’ and ‘de jure’ standard method of reporting on the thematic accuracy assessment of any land surface geospatial dataset. This type of data supports decision‐making in many different fields, so suitable quality is therefore essential in order to take the best decisions. Nevertheless, the creation and exploitation of the confusion matrix remains as an open topic with issues related to sampling design, quantitative indices derived from the matrix, statistical hypotheses that could be applied, etc. In connection with the latter, a confusion matrix dataset would be useful for a researcher in this matter. We have developed such a dataset retrieving confusion matrices from the literature, mainly research articles published in scientific journals included in WoS. We have collected almost 200 matrices in a database. This allows us to access the complete matrices and query different interesting properties of them and of the project where they were developed such as matrix size, sample size, location, year of data capture, labels of the classes, quality indices used, and extension and location of the project (where available).
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spelling doaj.art-ad8cd25ed031409abbd51eeda0b8c3b52022-12-22T00:20:01ZengWileyGeoscience Data Journal2049-60602022-06-0191374510.1002/gdj3.116Thematic quality assessment of land surface geospatial data based on confusion matrices: A matrix set for research on measures and proceduresFrancisco J. Ariza‐López0José L. García‐Balboa1María V. Alba‐Fernández2José Rodríguez‐Avi3Departamento de Ingeniería Cartográfica Geodésica y Fotogrametría Universidad de Jaén Jaén SpainDepartamento de Ingeniería Cartográfica Geodésica y Fotogrametría Universidad de Jaén Jaén SpainDepartamento de Estadística e Investigación Operativa Universidad de Jaén Jaén SpainDepartamento de Estadística e Investigación Operativa Universidad de Jaén Jaén SpainAbstract The confusion matrix has long been adopted as the ‘de facto’ and ‘de jure’ standard method of reporting on the thematic accuracy assessment of any land surface geospatial dataset. This type of data supports decision‐making in many different fields, so suitable quality is therefore essential in order to take the best decisions. Nevertheless, the creation and exploitation of the confusion matrix remains as an open topic with issues related to sampling design, quantitative indices derived from the matrix, statistical hypotheses that could be applied, etc. In connection with the latter, a confusion matrix dataset would be useful for a researcher in this matter. We have developed such a dataset retrieving confusion matrices from the literature, mainly research articles published in scientific journals included in WoS. We have collected almost 200 matrices in a database. This allows us to access the complete matrices and query different interesting properties of them and of the project where they were developed such as matrix size, sample size, location, year of data capture, labels of the classes, quality indices used, and extension and location of the project (where available).https://doi.org/10.1002/gdj3.116confusion matrixgeospatial dataland surfacequality assessmentthematic accuracy
spellingShingle Francisco J. Ariza‐López
José L. García‐Balboa
María V. Alba‐Fernández
José Rodríguez‐Avi
Thematic quality assessment of land surface geospatial data based on confusion matrices: A matrix set for research on measures and procedures
Geoscience Data Journal
confusion matrix
geospatial data
land surface
quality assessment
thematic accuracy
title Thematic quality assessment of land surface geospatial data based on confusion matrices: A matrix set for research on measures and procedures
title_full Thematic quality assessment of land surface geospatial data based on confusion matrices: A matrix set for research on measures and procedures
title_fullStr Thematic quality assessment of land surface geospatial data based on confusion matrices: A matrix set for research on measures and procedures
title_full_unstemmed Thematic quality assessment of land surface geospatial data based on confusion matrices: A matrix set for research on measures and procedures
title_short Thematic quality assessment of land surface geospatial data based on confusion matrices: A matrix set for research on measures and procedures
title_sort thematic quality assessment of land surface geospatial data based on confusion matrices a matrix set for research on measures and procedures
topic confusion matrix
geospatial data
land surface
quality assessment
thematic accuracy
url https://doi.org/10.1002/gdj3.116
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AT mariavalbafernandez thematicqualityassessmentoflandsurfacegeospatialdatabasedonconfusionmatricesamatrixsetforresearchonmeasuresandprocedures
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