Assessing the Crown Closure of Nypa on UAV Images using Mean-Shift Segmentation Algorithm
Utilization of very high-resolution images becomes a new trend in forest management, particularly in the detection and identification of forest stand variables. This paper describes the use of mean-shift segmentation algorithm on unmanned aerial vehicles (UAV) images to measure crown closure of nypa...
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| Main Authors: | , , , |
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2018-03-01.
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| Online Access: | Get fulltext |
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| LEADER | 02328 am a22003253u 4500 | ||
|---|---|---|---|
| 001 | ijeecs8390_8049 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Silalahi, Robert Parulian |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Jaya, I Nengah Surati |e author |
| 700 | 1 | 0 | |a Tiryana, Tatang |e author |
| 700 | 1 | 0 | |a Mulia, Fairus |e author |
| 245 | 0 | 0 | |a Assessing the Crown Closure of Nypa on UAV Images using Mean-Shift Segmentation Algorithm |
| 260 | |b Institute of Advanced Engineering and Science, |c 2018-03-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/8390 | ||
| 520 | |a Utilization of very high-resolution images becomes a new trend in forest management, particularly in the detection and identification of forest stand variables. This paper describes the use of mean-shift segmentation algorithm on unmanned aerial vehicles (UAV) images to measure crown closure of nypa (Nypa fructicans) and gap. The 27 combinations of the parameter values such as spatial radius (hs), range radius (hr), and minimum region size (M). Gap detection and nypa crown closure measurements were performed using a hybrid between pixel-based (maximum likelihood classifier) and object-based approaches (segmentation). For evaluation of the approach performance, the accuracy assessment was done by comparing object-based classification results (segmentation) and visual interpretation (ground check). The study found that the best combination of segmentation parameter was the combination of hs 10, hr 10 and M 50, with the overall accuracy of 76,6% and kappa accuracy of 55.7%. | ||
| 540 | |a Copyright (c) 2017 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc-nd/4.0 | ||
| 546 | |a eng | ||
| 690 | |||
| 690 | |a nypa, unmanned aerial vehicles (UAV), mean-shift, segmentation | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 9, No 3: March 2018; 722-730 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v9.i3 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/8390/8049 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/8390/8049 |z Get fulltext |