Remote sensing technique for retrieval of biomass burning haze in Malaysia
Biomass burning is a major problem in the Southeast Asian region. This anthropogenic haze occures very frequetly in this region due to drier weather conditions leading to an escalation in forest fire activities mainly over central Sumatra, Indonesia, and affected human health and other economic acti...
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| Format: | Conference or Workshop Item |
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2015
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| _version_ | 1796861196793544704 |
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| author | Adli Zakaria, Muhamad Faridzul Sarker, Md. Latifur Rahman Wahab, Ahmad Mubin |
| author_facet | Adli Zakaria, Muhamad Faridzul Sarker, Md. Latifur Rahman Wahab, Ahmad Mubin |
| author_sort | Adli Zakaria, Muhamad Faridzul |
| collection | ePrints |
| description | Biomass burning is a major problem in the Southeast Asian region. This anthropogenic haze occures very frequetly in this region due to drier weather conditions leading to an escalation in forest fire activities mainly over central Sumatra, Indonesia, and affected human health and other economic activities severely. This study has proposed an algorithm to estimate haze aerosol optical thickness (HAOT) in Peninsular Malaysia during the severe haze event in 2013 using MODIS 500m spatial resolution data in order to get a better understanding of the spatial distribution of the haze compared. The methodological consideration includes several steps of data processing i.e. i) haze identification, ii) haze LUT building using 6SV radiative transfer code, iii) AOT retrieval, and validation. Preliminary results indicate that haze aerosol optical thickness can be estimated from the MODIS 500 m data successfully with an accuracy more than 85% despite the problem of cloud cover. Further investigation is needed in order to understand the total potential of this algorithm by i) performing validation comparing with several data such as AERONET, Air Pollution Index (API) , and Pollutant Standards Index (PSI) ii) investigating the effect of land surface reflectance on the HAOT estimation, and iii) applying robust cloud screening technique. However, from this initial outcome, it can be concluded that the limitations of point based estimation of air quality can be reduced using this algorithm and spatial distribution of HAOT can be investigated with a greater confidence level. |
| first_indexed | 2024-03-05T19:52:42Z |
| format | Conference or Workshop Item |
| id | utm.eprints-62063 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:52:42Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | utm.eprints-620632017-08-22T03:15:57Z http://eprints.utm.my/62063/ Remote sensing technique for retrieval of biomass burning haze in Malaysia Adli Zakaria, Muhamad Faridzul Sarker, Md. Latifur Rahman Wahab, Ahmad Mubin G70.39-70.6 Remote sensing Biomass burning is a major problem in the Southeast Asian region. This anthropogenic haze occures very frequetly in this region due to drier weather conditions leading to an escalation in forest fire activities mainly over central Sumatra, Indonesia, and affected human health and other economic activities severely. This study has proposed an algorithm to estimate haze aerosol optical thickness (HAOT) in Peninsular Malaysia during the severe haze event in 2013 using MODIS 500m spatial resolution data in order to get a better understanding of the spatial distribution of the haze compared. The methodological consideration includes several steps of data processing i.e. i) haze identification, ii) haze LUT building using 6SV radiative transfer code, iii) AOT retrieval, and validation. Preliminary results indicate that haze aerosol optical thickness can be estimated from the MODIS 500 m data successfully with an accuracy more than 85% despite the problem of cloud cover. Further investigation is needed in order to understand the total potential of this algorithm by i) performing validation comparing with several data such as AERONET, Air Pollution Index (API) , and Pollutant Standards Index (PSI) ii) investigating the effect of land surface reflectance on the HAOT estimation, and iii) applying robust cloud screening technique. However, from this initial outcome, it can be concluded that the limitations of point based estimation of air quality can be reduced using this algorithm and spatial distribution of HAOT can be investigated with a greater confidence level. 2015 Conference or Workshop Item PeerReviewed Adli Zakaria, Muhamad Faridzul and Sarker, Md. Latifur Rahman and Wahab, Ahmad Mubin (2015) Remote sensing technique for retrieval of biomass burning haze in Malaysia. In: Proceedings of the 36th Asian Conference on Remote Sensing 2015, 24-28 Oct, 2015, Phillipines. http://www.acrs2015.org/ |
| spellingShingle | G70.39-70.6 Remote sensing Adli Zakaria, Muhamad Faridzul Sarker, Md. Latifur Rahman Wahab, Ahmad Mubin Remote sensing technique for retrieval of biomass burning haze in Malaysia |
| title | Remote sensing technique for retrieval of biomass burning haze in Malaysia |
| title_full | Remote sensing technique for retrieval of biomass burning haze in Malaysia |
| title_fullStr | Remote sensing technique for retrieval of biomass burning haze in Malaysia |
| title_full_unstemmed | Remote sensing technique for retrieval of biomass burning haze in Malaysia |
| title_short | Remote sensing technique for retrieval of biomass burning haze in Malaysia |
| title_sort | remote sensing technique for retrieval of biomass burning haze in malaysia |
| topic | G70.39-70.6 Remote sensing |
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