The use of multi-sensor for illegal human settlement detection / Arnis Asmat, S. Z. Zamzami and S. Mansor
The paper presents preliminary results of legal and illegal settlement extraction in Pulau Gaya, Sabah using high resolution Quickbird and SPOT- 5 multi-spectral imageries using automated house detection technique. The technique developed is spatial-based using tree counting approach. From the resul...
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| Format: | Article |
| Language: | English |
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Faculty of Architecture, Planning and Surveying
2012
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| Online Access: | http://ir.uitm.edu.my/id/eprint/8757/ http://ir.uitm.edu.my/id/eprint/8757/1/AJ_ARNIS%20ASMAT%20AJEBS%2012.pdf |
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uitm-8757 |
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eprints |
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uitm-87572019-03-25T04:25:19Z http://ir.uitm.edu.my/id/eprint/8757/ The use of multi-sensor for illegal human settlement detection / Arnis Asmat, S. Z. Zamzami and S. Mansor Zamzami, S. Z Mansor, S. Computer software The paper presents preliminary results of legal and illegal settlement extraction in Pulau Gaya, Sabah using high resolution Quickbird and SPOT- 5 multi-spectral imageries using automated house detection technique. The technique developed is spatial-based using tree counting approach. From the results, edge to edge of the house features was found precisely separated and can be delineated between houses that less than 2m distance. Results show that the technique able to delineate legal houses from Quickbird image more than SPOT-5. Differs results would be due to different spatial and spectral resolution of images. Faculty of Architecture, Planning and Surveying 2012 Article NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/8757/1/AJ_ARNIS%20ASMAT%20AJEBS%2012.pdf Zamzami, S. Z and Mansor, S. (2012) The use of multi-sensor for illegal human settlement detection / Arnis Asmat, S. Z. Zamzami and S. Mansor. Asian Journal Of Environment-Behaviour Studies, 3 (10). pp. 71-80. ISSN 1394-0384 |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Teknologi MARA |
| building |
UiTM Institutional Repository |
| collection |
Online Access |
| language |
English |
| topic |
Computer software |
| spellingShingle |
Computer software Zamzami, S. Z Mansor, S. The use of multi-sensor for illegal human settlement detection / Arnis Asmat, S. Z. Zamzami and S. Mansor |
| description |
The paper presents preliminary results of legal and illegal settlement extraction in Pulau Gaya, Sabah using high resolution Quickbird and SPOT- 5 multi-spectral imageries using automated house detection technique. The technique developed is spatial-based using tree counting approach. From the results, edge to edge of the house features was found precisely separated and can be delineated between houses that less than 2m distance. Results show that the technique able to delineate legal houses from Quickbird
image more than SPOT-5. Differs results would be due to different spatial and spectral resolution of images. |
| format |
Article |
| author |
Zamzami, S. Z Mansor, S. |
| author_facet |
Zamzami, S. Z Mansor, S. |
| author_sort |
Zamzami, S. Z |
| title |
The use of multi-sensor for illegal human settlement detection / Arnis Asmat, S. Z. Zamzami and S. Mansor |
| title_short |
The use of multi-sensor for illegal human settlement detection / Arnis Asmat, S. Z. Zamzami and S. Mansor |
| title_full |
The use of multi-sensor for illegal human settlement detection / Arnis Asmat, S. Z. Zamzami and S. Mansor |
| title_fullStr |
The use of multi-sensor for illegal human settlement detection / Arnis Asmat, S. Z. Zamzami and S. Mansor |
| title_full_unstemmed |
The use of multi-sensor for illegal human settlement detection / Arnis Asmat, S. Z. Zamzami and S. Mansor |
| title_sort |
use of multi-sensor for illegal human settlement detection / arnis asmat, s. z. zamzami and s. mansor |
| publisher |
Faculty of Architecture, Planning and Surveying |
| publishDate |
2012 |
| url |
http://ir.uitm.edu.my/id/eprint/8757/ http://ir.uitm.edu.my/id/eprint/8757/1/AJ_ARNIS%20ASMAT%20AJEBS%2012.pdf |
| first_indexed |
2023-09-18T22:47:28Z |
| last_indexed |
2023-09-18T22:47:28Z |
| _version_ |
1777417321032187904 |