Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1080/01431161.2020.1800122 http://hdl.handle.net/11449/201068 |
Resumo: | The development of unmanned aerial vehicles (UAVs) along with that of positioning and imaging sensors has promoted the use of photogrammetric techniques for applications other than the conventional acquisition of the Earth’s surface information. Moreover, the accuracy of photogrammetric products depends on several parameters, such as sensor quality and stability, image scale, strip overlap, and the number and distribution of ground control points (GCPs). Although technological developments have improved the automation and accuracy of the photogrammetric process, the acquisition of GCPs remains a highly time-consuming task. To address this problem, this study investigated the positional error of digital surface models (DSMs) generated via the post-processing of data acquired with a SenseFly eBee Classic, with respect to the number and distribution of GCPs. A single flight was conducted over a test field located at an urban expansion region of Presidente Prudente, State of São Paulo, Brazil. Nine DSMs were generated using different configurations of the number and distribution of GCPs. An accuracy assessment was performed based on 20 horizontal check points and 270 vertical check points determined by global navigation satellite system (GNSS) positioning. The vertical error surfaces were generated by Kriging. The Student’s t-test, Chi-square test, and root mean square error (RMSE) were used for the positional accuracy assessment. The results show that the qualities of the products generated by GNSS-supported Aerial Triangulation (GNSS-AT) without GCPs were in accordance with those indicated by the UAV manufacturer. In contrast, the results obtained by considering the GNSS-AT with different GCPs were not in accordance with the manufacturer’s claims. Finally, RMSE values of approximately 3 ground sample distance (GSD) for the horizontal component and 5 GSD for the vertical component are achievable with at least three well-distributed GCPs; however, the use of additional points is encouraged. |
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Repositório Institucional da UNESP |
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Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control pointsThe development of unmanned aerial vehicles (UAVs) along with that of positioning and imaging sensors has promoted the use of photogrammetric techniques for applications other than the conventional acquisition of the Earth’s surface information. Moreover, the accuracy of photogrammetric products depends on several parameters, such as sensor quality and stability, image scale, strip overlap, and the number and distribution of ground control points (GCPs). Although technological developments have improved the automation and accuracy of the photogrammetric process, the acquisition of GCPs remains a highly time-consuming task. To address this problem, this study investigated the positional error of digital surface models (DSMs) generated via the post-processing of data acquired with a SenseFly eBee Classic, with respect to the number and distribution of GCPs. A single flight was conducted over a test field located at an urban expansion region of Presidente Prudente, State of São Paulo, Brazil. Nine DSMs were generated using different configurations of the number and distribution of GCPs. An accuracy assessment was performed based on 20 horizontal check points and 270 vertical check points determined by global navigation satellite system (GNSS) positioning. The vertical error surfaces were generated by Kriging. The Student’s t-test, Chi-square test, and root mean square error (RMSE) were used for the positional accuracy assessment. The results show that the qualities of the products generated by GNSS-supported Aerial Triangulation (GNSS-AT) without GCPs were in accordance with those indicated by the UAV manufacturer. In contrast, the results obtained by considering the GNSS-AT with different GCPs were not in accordance with the manufacturer’s claims. Finally, RMSE values of approximately 3 ground sample distance (GSD) for the horizontal component and 5 GSD for the vertical component are achievable with at least three well-distributed GCPs; however, the use of additional points is encouraged.Graduate Program in Cartographic Sciences São Paulo State University (UNESP)Department of Cartography São Paulo State University (UNESP)Graduate Program in Cartographic Sciences São Paulo State University (UNESP)Department of Cartography São Paulo State University (UNESP)Universidade Estadual Paulista (Unesp)Gomes Pessoa, Guilherme [UNESP]Caceres Carrilho, André [UNESP]Takahashi Miyoshi, Gabriela [UNESP]Amorim, Amilton [UNESP]Galo, Mauricio [UNESP]2020-12-12T02:23:15Z2020-12-12T02:23:15Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1080/01431161.2020.1800122International Journal of Remote Sensing.1366-59010143-1161http://hdl.handle.net/11449/20106810.1080/01431161.2020.18001222-s2.0-85090945247Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Journal of Remote Sensinginfo:eu-repo/semantics/openAccess2024-06-18T15:01:28Zoai:repositorio.unesp.br:11449/201068Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T18:07:04.506827Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points |
title |
Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points |
spellingShingle |
Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points Gomes Pessoa, Guilherme [UNESP] |
title_short |
Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points |
title_full |
Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points |
title_fullStr |
Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points |
title_full_unstemmed |
Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points |
title_sort |
Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points |
author |
Gomes Pessoa, Guilherme [UNESP] |
author_facet |
Gomes Pessoa, Guilherme [UNESP] Caceres Carrilho, André [UNESP] Takahashi Miyoshi, Gabriela [UNESP] Amorim, Amilton [UNESP] Galo, Mauricio [UNESP] |
author_role |
author |
author2 |
Caceres Carrilho, André [UNESP] Takahashi Miyoshi, Gabriela [UNESP] Amorim, Amilton [UNESP] Galo, Mauricio [UNESP] |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Gomes Pessoa, Guilherme [UNESP] Caceres Carrilho, André [UNESP] Takahashi Miyoshi, Gabriela [UNESP] Amorim, Amilton [UNESP] Galo, Mauricio [UNESP] |
description |
The development of unmanned aerial vehicles (UAVs) along with that of positioning and imaging sensors has promoted the use of photogrammetric techniques for applications other than the conventional acquisition of the Earth’s surface information. Moreover, the accuracy of photogrammetric products depends on several parameters, such as sensor quality and stability, image scale, strip overlap, and the number and distribution of ground control points (GCPs). Although technological developments have improved the automation and accuracy of the photogrammetric process, the acquisition of GCPs remains a highly time-consuming task. To address this problem, this study investigated the positional error of digital surface models (DSMs) generated via the post-processing of data acquired with a SenseFly eBee Classic, with respect to the number and distribution of GCPs. A single flight was conducted over a test field located at an urban expansion region of Presidente Prudente, State of São Paulo, Brazil. Nine DSMs were generated using different configurations of the number and distribution of GCPs. An accuracy assessment was performed based on 20 horizontal check points and 270 vertical check points determined by global navigation satellite system (GNSS) positioning. The vertical error surfaces were generated by Kriging. The Student’s t-test, Chi-square test, and root mean square error (RMSE) were used for the positional accuracy assessment. The results show that the qualities of the products generated by GNSS-supported Aerial Triangulation (GNSS-AT) without GCPs were in accordance with those indicated by the UAV manufacturer. In contrast, the results obtained by considering the GNSS-AT with different GCPs were not in accordance with the manufacturer’s claims. Finally, RMSE values of approximately 3 ground sample distance (GSD) for the horizontal component and 5 GSD for the vertical component are achievable with at least three well-distributed GCPs; however, the use of additional points is encouraged. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-12T02:23:15Z 2020-12-12T02:23:15Z 2020-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1080/01431161.2020.1800122 International Journal of Remote Sensing. 1366-5901 0143-1161 http://hdl.handle.net/11449/201068 10.1080/01431161.2020.1800122 2-s2.0-85090945247 |
url |
http://dx.doi.org/10.1080/01431161.2020.1800122 http://hdl.handle.net/11449/201068 |
identifier_str_mv |
International Journal of Remote Sensing. 1366-5901 0143-1161 10.1080/01431161.2020.1800122 2-s2.0-85090945247 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
International Journal of Remote Sensing |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128897390215168 |