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Impact of input data (in)accuracy on overestimation of visible area in digital viewshed models

Viewshed analysis is a GIS tool in standard use for more than two decades to perform numerous scientific and practical tasks. The reliability of the resulting viewshed model depends on the computational algorithm and the quality of the input digital surface model (DSM). Although many studies have de...

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Autores principales: Lagner, Ondřej, Klouček, Tomáš, Šímová, Petra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5967369/
https://www.ncbi.nlm.nih.gov/pubmed/29844982
http://dx.doi.org/10.7717/peerj.4835
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author Lagner, Ondřej
Klouček, Tomáš
Šímová, Petra
author_facet Lagner, Ondřej
Klouček, Tomáš
Šímová, Petra
author_sort Lagner, Ondřej
collection PubMed
description Viewshed analysis is a GIS tool in standard use for more than two decades to perform numerous scientific and practical tasks. The reliability of the resulting viewshed model depends on the computational algorithm and the quality of the input digital surface model (DSM). Although many studies have dealt with improving viewshed algorithms, only a few studies have focused on the effect of the spatial accuracy of input data. Here, we compare simple binary viewshed models based on DSMs having varying levels of detail with viewshed models created using LiDAR DSM. The compared DSMs were calculated as the sums of digital terrain models (DTMs) and layers of forests and buildings with expertly assigned heights. Both elevation data and the visibility obstacle layers were prepared using digital vector maps differing in scale (1:5,000, 1:25,000, and 1:500,000) as well as using a combination of a LiDAR DTM with objects vectorized on an orthophotomap. All analyses were performed for 104 sample locations of 5 km(2), covering areas from lowlands to mountains and including farmlands as well as afforested landscapes. We worked with two observer point heights, the first (1.8 m) simulating observation by a person standing on the ground and the second (80 m) as observation from high structures such as wind turbines, and with five estimates of forest heights (15, 20, 25, 30, and 35 m). At all height estimations, all of the vector-based DSMs used resulted in overestimations of visible areas considerably greater than those from the LiDAR DSM. In comparison to the effect from input data scale, the effect from object height estimation was shown to be secondary.
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spelling pubmed-59673692018-05-29 Impact of input data (in)accuracy on overestimation of visible area in digital viewshed models Lagner, Ondřej Klouček, Tomáš Šímová, Petra PeerJ Ecosystem Science Viewshed analysis is a GIS tool in standard use for more than two decades to perform numerous scientific and practical tasks. The reliability of the resulting viewshed model depends on the computational algorithm and the quality of the input digital surface model (DSM). Although many studies have dealt with improving viewshed algorithms, only a few studies have focused on the effect of the spatial accuracy of input data. Here, we compare simple binary viewshed models based on DSMs having varying levels of detail with viewshed models created using LiDAR DSM. The compared DSMs were calculated as the sums of digital terrain models (DTMs) and layers of forests and buildings with expertly assigned heights. Both elevation data and the visibility obstacle layers were prepared using digital vector maps differing in scale (1:5,000, 1:25,000, and 1:500,000) as well as using a combination of a LiDAR DTM with objects vectorized on an orthophotomap. All analyses were performed for 104 sample locations of 5 km(2), covering areas from lowlands to mountains and including farmlands as well as afforested landscapes. We worked with two observer point heights, the first (1.8 m) simulating observation by a person standing on the ground and the second (80 m) as observation from high structures such as wind turbines, and with five estimates of forest heights (15, 20, 25, 30, and 35 m). At all height estimations, all of the vector-based DSMs used resulted in overestimations of visible areas considerably greater than those from the LiDAR DSM. In comparison to the effect from input data scale, the effect from object height estimation was shown to be secondary. PeerJ Inc. 2018-05-21 /pmc/articles/PMC5967369/ /pubmed/29844982 http://dx.doi.org/10.7717/peerj.4835 Text en ©2018 Lagner et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Ecosystem Science
Lagner, Ondřej
Klouček, Tomáš
Šímová, Petra
Impact of input data (in)accuracy on overestimation of visible area in digital viewshed models
title Impact of input data (in)accuracy on overestimation of visible area in digital viewshed models
title_full Impact of input data (in)accuracy on overestimation of visible area in digital viewshed models
title_fullStr Impact of input data (in)accuracy on overestimation of visible area in digital viewshed models
title_full_unstemmed Impact of input data (in)accuracy on overestimation of visible area in digital viewshed models
title_short Impact of input data (in)accuracy on overestimation of visible area in digital viewshed models
title_sort impact of input data (in)accuracy on overestimation of visible area in digital viewshed models
topic Ecosystem Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5967369/
https://www.ncbi.nlm.nih.gov/pubmed/29844982
http://dx.doi.org/10.7717/peerj.4835
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