PM10 distribution using remotely sensed data and GIS techniques; Klang Valley, Malaysia
Remote sensing and GIS have been increasingly used for air pollution monitoring in past decade. In this study the distribution of PM10 were measured at eight air quality monitoring stations in Klang Valley. The attempt was carried out in GIS environment. The data are belonging to the beginning of th...
| Main Authors: | , , , , |
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| Format: | Article |
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Thai Society of Higher Education Institutes on Environment
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/44377/ |
| _version_ | 1848850436628414464 |
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| author | Amanollahi, Jamil Abdullah, Ahmad Makmom Farzanmanesh, Raheleh Ramli, Mohammad Firuz Pirasteh, Saeid |
| author_facet | Amanollahi, Jamil Abdullah, Ahmad Makmom Farzanmanesh, Raheleh Ramli, Mohammad Firuz Pirasteh, Saeid |
| author_sort | Amanollahi, Jamil |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Remote sensing and GIS have been increasingly used for air pollution monitoring in past decade. In this study the distribution of PM10 were measured at eight air quality monitoring stations in Klang Valley. The attempt was carried out in GIS environment. The data are belonging to the beginning of the week –Monday- and weekend –Saturday-. Aerosol optical thickness (AOT) values retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) were interpolated in GIS for comparison with ground station PM10 data. The validation between AOT and amount of PM10 in the atmosphere were analyzed using non-linear correlation coefficient (NLCC) for 2004. Results showed that the amount of PM10 at the beginning of the week is higher than the weekend. Remote sensing data showed better distribution of PM10 than ground station data. The NLCC results had a range from (0.10) at Petaling Jaya to (0.61) at Shah Alam. This study shows that GIS is useful tool to generate distribution map of PM10. This study shows that MODIS AOT data are able to present the amount of PM10 over large spatial scales that there is no ground stations air quality monitoring. |
| first_indexed | 2025-11-15T10:06:16Z |
| format | Article |
| id | upm-44377 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T10:06:16Z |
| publishDate | 2011 |
| publisher | Thai Society of Higher Education Institutes on Environment |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-443772023-12-24T17:18:59Z http://psasir.upm.edu.my/id/eprint/44377/ PM10 distribution using remotely sensed data and GIS techniques; Klang Valley, Malaysia Amanollahi, Jamil Abdullah, Ahmad Makmom Farzanmanesh, Raheleh Ramli, Mohammad Firuz Pirasteh, Saeid Remote sensing and GIS have been increasingly used for air pollution monitoring in past decade. In this study the distribution of PM10 were measured at eight air quality monitoring stations in Klang Valley. The attempt was carried out in GIS environment. The data are belonging to the beginning of the week –Monday- and weekend –Saturday-. Aerosol optical thickness (AOT) values retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) were interpolated in GIS for comparison with ground station PM10 data. The validation between AOT and amount of PM10 in the atmosphere were analyzed using non-linear correlation coefficient (NLCC) for 2004. Results showed that the amount of PM10 at the beginning of the week is higher than the weekend. Remote sensing data showed better distribution of PM10 than ground station data. The NLCC results had a range from (0.10) at Petaling Jaya to (0.61) at Shah Alam. This study shows that GIS is useful tool to generate distribution map of PM10. This study shows that MODIS AOT data are able to present the amount of PM10 over large spatial scales that there is no ground stations air quality monitoring. Thai Society of Higher Education Institutes on Environment 2011 Article PeerReviewed Amanollahi, Jamil and Abdullah, Ahmad Makmom and Farzanmanesh, Raheleh and Ramli, Mohammad Firuz and Pirasteh, Saeid (2011) PM10 distribution using remotely sensed data and GIS techniques; Klang Valley, Malaysia. EnvironmentAsia, 4 (1). pp. 47-52. ISSN 1906-1714 https://tshe.org/ea/ea_jan2011.html 10.14456/ea.2011.7 |
| spellingShingle | Amanollahi, Jamil Abdullah, Ahmad Makmom Farzanmanesh, Raheleh Ramli, Mohammad Firuz Pirasteh, Saeid PM10 distribution using remotely sensed data and GIS techniques; Klang Valley, Malaysia |
| title | PM10 distribution using remotely sensed data and GIS techniques; Klang Valley, Malaysia |
| title_full | PM10 distribution using remotely sensed data and GIS techniques; Klang Valley, Malaysia |
| title_fullStr | PM10 distribution using remotely sensed data and GIS techniques; Klang Valley, Malaysia |
| title_full_unstemmed | PM10 distribution using remotely sensed data and GIS techniques; Klang Valley, Malaysia |
| title_short | PM10 distribution using remotely sensed data and GIS techniques; Klang Valley, Malaysia |
| title_sort | pm10 distribution using remotely sensed data and gis techniques; klang valley, malaysia |
| url | http://psasir.upm.edu.my/id/eprint/44377/ http://psasir.upm.edu.my/id/eprint/44377/ http://psasir.upm.edu.my/id/eprint/44377/ |