Smoke detection using remote sensing technique

Particulate matter sizing less than 10 micrometers widely known as PM10 is one of the major constituents of the thick smoke haze phenomenon, which occured in Malaysia during September 1997. In this study, seven scenes of NOAA-14 AVHRR satellite data were acquired in order to determine and map PM10 o...

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Main Authors: Asmala, A., Ayof, M. N., Agus, S.B., Sakidin, H., Sharifah Sakinah, S.A.
Format: Article
Language:English
Published: Universiti Teknikal Malaysia Melaka 2006
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Online Access:http://eprints.utem.edu.my/id/eprint/342/1/reach2006_1.pdf
http://eprints.utem.edu.my/id/eprint/342/
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spelling my.utem.eprints.3422021-09-29T15:58:08Z http://eprints.utem.edu.my/id/eprint/342/ Smoke detection using remote sensing technique Asmala, A. Ayof, M. N. Agus, S.B. Sakidin, H. Sharifah Sakinah, S.A. QC Physics Particulate matter sizing less than 10 micrometers widely known as PM10 is one of the major constituents of the thick smoke haze phenomenon, which occured in Malaysia during September 1997. In this study, seven scenes of NOAA-14 AVHRR satellite data were acquired in order to determine and map PM10 over Malaysia. Five locations of air pollution station were chosen where PM10 was measured. Initially, preprocessing tasks namely: atmospheric and geometric correction were implemented befor further image processing job. Next, band 1 of AVHRR data with wavelength ranging from 0.58 to 0.68 micrometers were calibrated to compensate for post-launch sensor deradation. Cloud separation was then carried out using visual and thresholding technique. Relationship between the satellite and the corresponding PM10 AQI (air quality index) at the selected stations was established using linear regression model. The model was then used to map the concentration of PM10 over Malaysia. The result indicates that remote sensing technique usin band 1 of NOAA-14 AVHRR data was capable to determine PM10 concentration quantitatviely and spatially in continous manner. Finally, accuracy was assessed using Root-mean-square error technique. Universiti Teknikal Malaysia Melaka 2006 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/342/1/reach2006_1.pdf Asmala, A. and Ayof, M. N. and Agus, S.B. and Sakidin, H. and Sharifah Sakinah, S.A. (2006) Smoke detection using remote sensing technique. Prosiding Seminar Pencapaian Penyelidikan KUTKM 2006 (REACH 06). pp. 284-293. ISSN 983-40684-4-1
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic QC Physics
spellingShingle QC Physics
Asmala, A.
Ayof, M. N.
Agus, S.B.
Sakidin, H.
Sharifah Sakinah, S.A.
Smoke detection using remote sensing technique
description Particulate matter sizing less than 10 micrometers widely known as PM10 is one of the major constituents of the thick smoke haze phenomenon, which occured in Malaysia during September 1997. In this study, seven scenes of NOAA-14 AVHRR satellite data were acquired in order to determine and map PM10 over Malaysia. Five locations of air pollution station were chosen where PM10 was measured. Initially, preprocessing tasks namely: atmospheric and geometric correction were implemented befor further image processing job. Next, band 1 of AVHRR data with wavelength ranging from 0.58 to 0.68 micrometers were calibrated to compensate for post-launch sensor deradation. Cloud separation was then carried out using visual and thresholding technique. Relationship between the satellite and the corresponding PM10 AQI (air quality index) at the selected stations was established using linear regression model. The model was then used to map the concentration of PM10 over Malaysia. The result indicates that remote sensing technique usin band 1 of NOAA-14 AVHRR data was capable to determine PM10 concentration quantitatviely and spatially in continous manner. Finally, accuracy was assessed using Root-mean-square error technique.
format Article
author Asmala, A.
Ayof, M. N.
Agus, S.B.
Sakidin, H.
Sharifah Sakinah, S.A.
author_facet Asmala, A.
Ayof, M. N.
Agus, S.B.
Sakidin, H.
Sharifah Sakinah, S.A.
author_sort Asmala, A.
title Smoke detection using remote sensing technique
title_short Smoke detection using remote sensing technique
title_full Smoke detection using remote sensing technique
title_fullStr Smoke detection using remote sensing technique
title_full_unstemmed Smoke detection using remote sensing technique
title_sort smoke detection using remote sensing technique
publisher Universiti Teknikal Malaysia Melaka
publishDate 2006
url http://eprints.utem.edu.my/id/eprint/342/1/reach2006_1.pdf
http://eprints.utem.edu.my/id/eprint/342/
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score 13.15806