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International Journal of Environment Science and Technology
Center for Environment and Energy Research and Studies (CEERS)
ISSN: 1735-1472 EISSN: 1735-1472
Vol. 10, No. 6, 2013, pp. 1245-1254
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Bioline Code: st13121
Full paper language: English
Document type: Research Article
Document available free of charge
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International Journal of Environment Science and Technology, Vol. 10, No. 6, 2013, pp. 1245-1254
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Development of the models to estimate particulate matter from thermal infrared band of Landsat Enhanced Thematic Mapper
Amanollahi, J.; Tzanis, C.; Abdullah, A. M.; Ramli, M. F. & Pirasteh, S.
Abstract
Particulate matter concentration and assess-
ment of its movement pattern is crucial in air pollution
studies. However, no study has been conducted to deter-
mine the PM
10concentration using atmospheric correction
of thermal band by temperature of nearest dark pixels
group (TNDPG) of this band. For that purpose, 16 Landsat
Enhanced Thematic Mapper plus ETM+
images for San-
andaj and Tehran in Iran were utilized to determine the
amount of PM
10
concentration in the air. Thermal infrared
(band 6) of all images was also used to determine the
ground station temperature (GST b6) and temperature of
nearest dark pixels group. Based on atmospheric correction
of images using temperature retrieval from Landsat
ETM+
, three empirical models were established. Non-
linear correlation coefficient with polynomial equation was
used to analyze the correlations between particulate matter
concentration and the ground station temperature for the
three models. Similar analyses were also undertaken for
three stations in Klang Valley, Malaysia, using 11 Landsat
ETM+
images to show the effectiveness of the model in
different region. The data analysis indicated a good cor-
relation coefficient
R
=
0.89 and
R
=
0.91 between the trend of the result of temperature of nearest dark pixels
group b6
-
(GST b6
-
GST) model and the trend of PM
10
concentration in Iran and Malaysia, respectively. This
study reveals the applicability of the thermal band of
Landsat TM and ETM+
to determine the PM
10
concentration over large areas.
Keywords
Digital number; Dark pixel; Land surface temperature; Atmospheric correction; Wind speed
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