Deriving Optimum Visibility Range and Aerosol Loading from Urban Atmospheric Model in Malaysia

Abstract:

Visibility, aerosol optical thickness and water vapor are important atmospheric parameters that vary in space and time. Using radiative transfer algorithm to derive surface reflectance from imaging these values would be critical to be assigned. This study will investigate the optimum range of visibility and aerosol loading in Malaysia deriving from atmospheric model. Urban atmospheric model was performed into two major cities in Malaysia to represent for ideal tropical climate. The study found that the farthest visibility range at 50km,the aerosol loading was low and the shortest range at 10 km was contain high aerosol loading. Relatively, aerosol loading estimation is higher at close-shore city (Penang) than inland city (Kuala Lumpur).

• Periodical: Advanced Materials Research (Volumes 518-523)
• Pages: 5784-5787
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.518-523.5784
• Online since: May 2012
• Authors: Wan Noni Afida Ab Manan, Arnis Asmat, Noordin Ahmad
• Keywords: Aerosol, Atmospheric Model, Imaging Data, Reflectance, Visibility

References

[1] G. Asrar, in: Theory and Applications of optical remote sensing. John Wiley & Sons, New York, (1989).

[2] R. Richter, in: ATCOR-2/3 User Guide, version 8.0, (2011).

[3] D. T. Janzen, A. L. Fredeen, and R. D. Wheate, in: Radiometric correction techniques and accuracy assessment for Landsat TM data in remote forested regions, Journal of Remote Sensing, 32, 5, 330-340, (2006).

DOI: 10.5589/m06-028

[4] R. Richter, in: Atmospheric/Topographic correction for Airborne Imagery, ATCOR-4 User Guide version 5.1, (2010)

[5] R. Richter, in: Geomatica II Course Guide version 10.1, 51-61, (2007).

[6] W. N. A. A. Manan, and A. Asmat, in: The relationship of atmospheric aerosol and visibility in Penang Island using landsat data for year 1993 and 2005, 10th International Symposium and Exhibition on Geoinformation Conference, (2011).

[7] V. P. R. Silva, P. V. Azevedo, R. S. Brito and J. H. B. C. Campos, in: Evaluating the urban climate of a typically tropical city of northeastern Brazil, Journal of Environmental Monitoring Assessment, 161, 45-59, (2010).

DOI: 10.1007/s10661-008-0726-3

[8] Q. Weng, D. Lu and J. Schubring, in: Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies, Journal of Remote Sensing of Environment, 89, 467-483, (2004).

DOI: 10.1016/j.rse.2003.11.005

[9] W. Takeuchi, N. Hashim and K.M. Thet, in: Application of Remote sensing and GIS for monitoring urban heat island in Kuala Lumpur Metropolitan area, submitted to Map Asia and ISG 2010 conference, (2010).

[10] M. Sirat, C. Tan and T. Subramaniam, in: Penang, Malaysia Self-evaluation report, Review of Higher Education Institutions in Regional and city development, (2010).

[11] Information on http://www.met.gov.my, Malaysian Meteorological Department. (2012). Observation of temperature and humidity. Retrieved January 2, 2012.

[12] Y. J. Kaufman, D. Tanré, H. R. Gordon, T. Nakajima, J. Lenoble, R. Frouin, H. Grassal, B. M. Herman, M. D. King, and P. M. Teillet, in: Passive remote sensing of tropospheric aerosol and atmospheric correction for the aerosol effect, Journal of Geograpical Research, 102, 815-830, (1997).

DOI: 10.1029/97jd01496

[13] Information on http://earthobservatory.nasa.gov, Haze over Sumatra on February 2005.Retrieved March 9, 2012.

[14] A. Asmat, P.M. Atkinson, G. M. Foody, in: Geostatically estimated image noise is a function of variance in the underlying signal, International Journal of Remote Sensing, 31: 4, 1009-1025.(2010).

DOI: 10.1080/01431160902922888