Departamento de Ingeniería Cartográfica, Geodésica y Fotogrametría
URI permanente para esta comunidadhttps://hdl.handle.net/10953/36
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Examinando Departamento de Ingeniería Cartográfica, Geodésica y Fotogrametría por Materia "Accuracy"
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Ítem Accuracy Assessment of Digital Elevation Models (DEMs): A Critical Review of Practices of the Past Three Decades(MDPI, 2020) Mesa-Mingorance, José Luis; Ariza-López, Francisco JavierAn analysis of almost 200 references has been carried out in order to obtain knowledge about the DEM (Digital Elevation Model) accuracy assessment methods applied in the last three decades. With regard to grid DEMs, 14 aspects related to the accuracy assessment processes have been analysed (DEM data source, data model, reference source for the evaluation, extension of the evaluation, applied models, etc.). In the references analysed, except in rare cases where an accuracy assessment standard has been followed, accuracy criteria and methods are usually established according to the premises established by the authors. Visual analyses and 3D analyses are few in number. The great majority of cases assess accuracy by means of point-type control elements, with the use of linear and surface elements very rare. Most cases still consider the normal model for errors (discrepancies), but analysis based on the data itself is making headway. Sample size and clear criteria for segmentation are still open issues. Almost 21% of cases analyse the accuracy in some derived parameter(s) or output, but no standardization exists for this purpose. Thus, there has been an improvement in accuracy assessment methods, but there are still many aspects that require the attention of researchers and professional associations or standardization bodies such as a common vocabulary, standardized assessment methods, methods for meta-quality assessment, and indices with an applied quality perspective, among others.Ítem Influence of Sample Size on Automatic Positional Accuracy Assessment Methods for Urban Areas(MDPI, 2018) Ariza-López, Francisco Javier; Ruiz-Lendínez, Juan José; Ureña, Manuel AntonioIn recent years, new approaches aimed to increase the automation level of positional accuracy assessment processes for spatial data have been developed. However, in such cases, an aspect as significant as sample size has not yet been addressed. In this paper, we study the influence of sample size when estimating the planimetric positional accuracy of urban databases by means of an automatic assessment using polygon-based methodology. Our study is based on a simulation process, which extracts pairs of homologous polygons from the assessed and reference data sources and applies two buffer-based methods. The parameter used for determining the different sizes (which range from 5 km up to 100 km) has been the length of the polygons’ perimeter, and for each sample size 1000 simulations were run. After completing the simulation process, the comparisons between the estimated distribution functions for each sample and population distribution function were carried out by means of the Kolmogorov–Smirnov test. Results show a significant reduction in the variability of estimations when sample size increased from 5 km to 100 km.