Demystifying the Differences between Structure-from-MotionSoftware Packages for Pre-Processing Drone Data
- Pell, Taleatha
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Li, Joan Y. Q.
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Joyce, Karen E.
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González Aguilera, Diego
1
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Rodríguez Gonzálvez, Pablo
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1
Universidad de Salamanca
info
ISSN: 2504-446X
Año de publicación: 2022
Volumen: 6
Número: 1
Páginas: 24
Tipo: Artículo
Otras publicaciones en: Drones
Objetivos de desarrollo sostenible
Resumen
With the increased availability of low-cost, off-the-shelf drone platforms, drone data become easy to capture and are now a key component of environmental assessments and monitoring. Once the data are collected, there are many structure-from-motion (SfM) photogrammetry software options available to pre-process the data into digital elevation models (DEMs) and orthomosaics for further environmental analysis. However, not all software packages are created equal, nor are their outputs. Here, we evaluated the workflows and output products of four desktop SfM packages (AgiSoft Metashape, Correlator3D, Pix4Dmapper, WebODM), across five input datasets representing various ecosystems. We considered the processing times, output file characteristics, colour representation of orthomosaics, geographic shift, visual artefacts, and digital surface model (DSM) elevation values. No single software package was determined the “winner” across all metrics, but we hope our results help others demystify the differences between the options, allowing users to make an informed decision about which software and parameters to select for their specific application. Our comparisons highlight some of the challenges that may arise when comparing datasets that have been processed using different parameters and different software packages, thus demonstrating a need to provide metadata associated with processing workflows.
Referencias bibliográficas
- 10.1177/0309133319837454
- 10.1071/MF17380
- 10.1890/120150
- 10.1016/j.jag.2019.101909
- 10.3390/rs13183655
- 10.3390/rs12182970
- 10.3390/drones5030097
- 10.1080/22797254.2020.1793687
- 10.3390/rs12233986
- 10.1016/j.geomorph.2021.107968
- 10.3390/rs13142688
- 10.3390/rs11202394
- 10.3390/rs12132093
- 10.1007/s00338-021-02088-9
- 10.3390/jmse7030063
- 10.3390/rs13101987
- 10.3390/jmse8090647
- 10.3390/rs13040830
- 10.1002/rra.3832
- 10.3390/land10010029
- 10.1139/juvs-2015-0019
- 10.1007/s00300-019-02616-y
- 10.5194/isprs-annals-IV-2-W5-141-2019
- 10.3390/rs13142705
- 10.1145/3437120.3437333
- 10.3390/rs12244144
- 10.5194/nhess-19-2039-2019
- 10.1080/19475705.2020.1760360
- 10.5194/isprs-archives-XLII-3-W12-2020-267-2020
- 10.1007/978-3-540-72108-6_5
- 10.3390/rs4051392
- 10.1016/j.geomorph.2016.11.021
- 10.3390/rs12061001
- 10.1177/0309133315615805
- 10.3832/ifor2986-012
- 10.14358/PERS.82.6.419
- 10.3390/ijgi9030164
- 10.1016/j.isprsjprs.2020.04.016
- 10.3724/SP.J.1006.2020.91066
- (2017)
- (2021)
- (2021)
- Web Open Drone Map (ODM) https://www.opendronemap.org/
- Geonadir https://data.geonadir.com/
- (2019)
- (2019)
- (2017)
- (2020)
- Vineyard in Luxembourg https://data.geonadir.com/project-details/341
- SE Pelorus March 2021 Part 1 https://data.geonadir.com/project-details/139
- Trinity Park January 2021 https://data.geonadir.com/project-details/98
- Tucson Arizona https://data.geonadir.com/project-details/353
- Lung Island Annan River Yuku Baja https://data.geonadir.com/project-details/523
- (2019)
- Van Rossum, (2009)
- Bradski, (2000), Dr. Dobb’s J. Softw. Tools, 25, pp. 120
- World Imagery—Overview https://www.arcgis.com/home/item.html?id=10df2279f9684e4a9f6a7f08febac2a9
- 10.5194/hess-11-1481-2007
- 10.1515/geo-2019-0066
- 10.3390/rs10101606
- 10.3390/rs8090786
- 10.1061/(ASCE)SU.1943-5428.0000206
- 10.5194/isprs-archives-XLIII-B1-2020-451-2020
- 10.5623/cig2016-102
- 10.1109/TGRS.2013.2265295
- 10.3390/rs12060986
- 10.3390/rs13071359
- 10.1515/geo-2020-0257
- 10.3390/rs12172806
- 10.1080/10095020.2019.1710437