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UAV-based approach to extract topographic and as-built information by utilising the OBIA technique

In this study, the capability of Unmanned Aerial Vehicle (UAV) optical data to provide reliable topographic and as-built information was tested using the eBee Sensefly UAV system. The Object-based Image Analysis (OBIA) technique was used to extract important geospatial information for mapping. The r...

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Main Authors: Sibaruddin, Hairie Ilkham, Mohd Shafri, Helmi Zulhaidi, Pradhan, Biswajeet, Haron, Nuzul Azam
Format: Article
Language:English
Published: Science and Education Publishing 2018
Online Access:http://psasir.upm.edu.my/id/eprint/74355/1/UAV-based%20approach%20to%20extract%20topographic%20and%20as-built%20information%20by%20utilising%20the%20OBIA%20technique.pdf
http://psasir.upm.edu.my/id/eprint/74355/
http://www.sciepub.com/journal/jgg
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spelling my.upm.eprints.743552020-03-26T06:21:29Z http://psasir.upm.edu.my/id/eprint/74355/ UAV-based approach to extract topographic and as-built information by utilising the OBIA technique Sibaruddin, Hairie Ilkham Mohd Shafri, Helmi Zulhaidi Pradhan, Biswajeet Haron, Nuzul Azam In this study, the capability of Unmanned Aerial Vehicle (UAV) optical data to provide reliable topographic and as-built information was tested using the eBee Sensefly UAV system. The Object-based Image Analysis (OBIA) technique was used to extract important geospatial information for mapping. The robust Taguchi method was adopted to optimise the segmentation process. Feature space optimisation method was used to obtain the best features for image classification utilising different supervised OBIA classifiers, such as K-nearest neighbour (KNN), normal Bayes (NB), decision tree (DT), random forest (RF) and support vector machine (SVM). Results showed that SVM obtained the highest percentage of overall accuracy, followed by RF, NB, DT and KNN at 97.20%, 95.80%, 93.14%, 86.01% and 77.62%, respectively. The McNemar test was implemented to analyse the significance of the classifier results. The as-built information showed that dimensional accuracy was less than 1 metre compared with ground survey measurement. We conclude that the combination of UAV and OBIA provides a rapid and efficient approach for map updating. This technique could replace the current procedure that utilises piloted aircraft and satellite images for data acquisition and reduce the time for digitising each feature that represents land cover for urban mapping. Science and Education Publishing 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/74355/1/UAV-based%20approach%20to%20extract%20topographic%20and%20as-built%20information%20by%20utilising%20the%20OBIA%20technique.pdf Sibaruddin, Hairie Ilkham and Mohd Shafri, Helmi Zulhaidi and Pradhan, Biswajeet and Haron, Nuzul Azam (2018) UAV-based approach to extract topographic and as-built information by utilising the OBIA technique. Journal of Geosciences and Geomatics, 6 (3). 103 - 123. ISSN 2373-6690; EISSN: 2373-6704 http://www.sciepub.com/journal/jgg 10.12691/jgg-6-3-2
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description In this study, the capability of Unmanned Aerial Vehicle (UAV) optical data to provide reliable topographic and as-built information was tested using the eBee Sensefly UAV system. The Object-based Image Analysis (OBIA) technique was used to extract important geospatial information for mapping. The robust Taguchi method was adopted to optimise the segmentation process. Feature space optimisation method was used to obtain the best features for image classification utilising different supervised OBIA classifiers, such as K-nearest neighbour (KNN), normal Bayes (NB), decision tree (DT), random forest (RF) and support vector machine (SVM). Results showed that SVM obtained the highest percentage of overall accuracy, followed by RF, NB, DT and KNN at 97.20%, 95.80%, 93.14%, 86.01% and 77.62%, respectively. The McNemar test was implemented to analyse the significance of the classifier results. The as-built information showed that dimensional accuracy was less than 1 metre compared with ground survey measurement. We conclude that the combination of UAV and OBIA provides a rapid and efficient approach for map updating. This technique could replace the current procedure that utilises piloted aircraft and satellite images for data acquisition and reduce the time for digitising each feature that represents land cover for urban mapping.
format Article
author Sibaruddin, Hairie Ilkham
Mohd Shafri, Helmi Zulhaidi
Pradhan, Biswajeet
Haron, Nuzul Azam
spellingShingle Sibaruddin, Hairie Ilkham
Mohd Shafri, Helmi Zulhaidi
Pradhan, Biswajeet
Haron, Nuzul Azam
UAV-based approach to extract topographic and as-built information by utilising the OBIA technique
author_facet Sibaruddin, Hairie Ilkham
Mohd Shafri, Helmi Zulhaidi
Pradhan, Biswajeet
Haron, Nuzul Azam
author_sort Sibaruddin, Hairie Ilkham
title UAV-based approach to extract topographic and as-built information by utilising the OBIA technique
title_short UAV-based approach to extract topographic and as-built information by utilising the OBIA technique
title_full UAV-based approach to extract topographic and as-built information by utilising the OBIA technique
title_fullStr UAV-based approach to extract topographic and as-built information by utilising the OBIA technique
title_full_unstemmed UAV-based approach to extract topographic and as-built information by utilising the OBIA technique
title_sort uav-based approach to extract topographic and as-built information by utilising the obia technique
publisher Science and Education Publishing
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/74355/1/UAV-based%20approach%20to%20extract%20topographic%20and%20as-built%20information%20by%20utilising%20the%20OBIA%20technique.pdf
http://psasir.upm.edu.my/id/eprint/74355/
http://www.sciepub.com/journal/jgg
_version_ 1665896018656362496
score 13.211869

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