Comparison of Gridded DEMs by Buffering

Comparing two digital elevation models (DEMs), S1 (reference) and S2 (product), in order to get the S2 quality, has usually been performed on sampled points. However, it seems more natural, as we propose, comparing both DEMs using 2.5D surfaces: applying a buffer to S1 (single buffer method, SBM) or...

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Main Authors: Francisco Javier Ariza-López, Juan Francisco Reinoso-Gordo
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/15/3002
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spelling doaj-a3fdd418e02a437eb121db8ea2425fc32021-08-06T15:30:46ZengMDPI AGRemote Sensing2072-42922021-07-01133002300210.3390/rs13153002Comparison of Gridded DEMs by BufferingFrancisco Javier Ariza-López0Juan Francisco Reinoso-Gordo1Departamento de Ingeniería Cartográfica, Geodésica y Fotogrametría, Universidad de Jaén, 23071 Jaén, SpainDepartamento de Expresión Gráfica, Arquitectónica y en la Ingeniería; Universidad de Granada, 18071 Granda, SpainComparing two digital elevation models (DEMs), S1 (reference) and S2 (product), in order to get the S2 quality, has usually been performed on sampled points. However, it seems more natural, as we propose, comparing both DEMs using 2.5D surfaces: applying a buffer to S1 (single buffer method, SBM) or to both S1 and S2 (double buffer method, DBM). The SBM and DBM approaches have been used in lines accuracy assessment and, in this paper, we generalize them to a DEM surface, so that more area of the S2 surface (in the case of the SBM), or the area and volume (in the case of the DBM) that are involved, more similarly are S1 and S2. The results obtained show that across both methods, SBM recognizes the presence of outliers and vertical bias while DBM allows a richer and more complex analysis based on voxel intersection. Both methods facilitate creating observed distribution functions that eliminate the need for the hypothesis of normality on discrepancies and allow the application of quality control techniques based on proportions. We consider that the SBM is more suitable when the S1 accuracy is much greater than that of S2 and DBM is preferred when the accuracy of S1 and S2 are approximately equal.https://www.mdpi.com/2072-4292/13/15/3002grid DEMbuffering surfacequality assessmentaccuracydistribution function
collection DOAJ
language English
format Article
sources DOAJ
author Francisco Javier Ariza-López
Juan Francisco Reinoso-Gordo
spellingShingle Francisco Javier Ariza-López
Juan Francisco Reinoso-Gordo
Comparison of Gridded DEMs by Buffering
Remote Sensing
grid DEM
buffering surface
quality assessment
accuracy
distribution function
author_facet Francisco Javier Ariza-López
Juan Francisco Reinoso-Gordo
author_sort Francisco Javier Ariza-López
title Comparison of Gridded DEMs by Buffering
title_short Comparison of Gridded DEMs by Buffering
title_full Comparison of Gridded DEMs by Buffering
title_fullStr Comparison of Gridded DEMs by Buffering
title_full_unstemmed Comparison of Gridded DEMs by Buffering
title_sort comparison of gridded dems by buffering
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-07-01
description Comparing two digital elevation models (DEMs), S1 (reference) and S2 (product), in order to get the S2 quality, has usually been performed on sampled points. However, it seems more natural, as we propose, comparing both DEMs using 2.5D surfaces: applying a buffer to S1 (single buffer method, SBM) or to both S1 and S2 (double buffer method, DBM). The SBM and DBM approaches have been used in lines accuracy assessment and, in this paper, we generalize them to a DEM surface, so that more area of the S2 surface (in the case of the SBM), or the area and volume (in the case of the DBM) that are involved, more similarly are S1 and S2. The results obtained show that across both methods, SBM recognizes the presence of outliers and vertical bias while DBM allows a richer and more complex analysis based on voxel intersection. Both methods facilitate creating observed distribution functions that eliminate the need for the hypothesis of normality on discrepancies and allow the application of quality control techniques based on proportions. We consider that the SBM is more suitable when the S1 accuracy is much greater than that of S2 and DBM is preferred when the accuracy of S1 and S2 are approximately equal.
topic grid DEM
buffering surface
quality assessment
accuracy
distribution function
url https://www.mdpi.com/2072-4292/13/15/3002
work_keys_str_mv AT franciscojavierarizalopez comparisonofgriddeddemsbybuffering
AT juanfranciscoreinosogordo comparisonofgriddeddemsbybuffering
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