Abstract. Detection of plumes produced by industrial accidents using NOAA/AVHRR thermal imagery may be substantially supported in urban areas by the presence of the heat island phenomenon. In this study, an attempt is made to classify the urban web on the basis of the heat island and its impact on the brightness temperatures. Application of the classi cation scheme on a night-time thermal infrared NOAA-14 image depicting the urban web of Athens demonstrates the potential of this classi cation for the detection of a plume caused by a re in a warehouse. Detection of the plume in this case is favoured by the urban heat island phenomenon due to which the urban surface has higher temperature compared to the adjacent environment and the plume above. As a result, distinction of the pixels corresponding to the plume is more eVective

C Cartalis

N Chrysoulakis

CiteSeerX

int. j. remote sensing, 2002, vol. 23, no. 14, 2909–2916
Thermal detection of plumes produced by industrial accidents in urban
areas based on the presence of the heat island
N. CHRYSOULAKIS*
Foundation for Research and Technology – Hellas, Institute of Applied
Mathematics, Regional Analysis Division, IACM–FORTH, Vassilika Vouton,
P.O. Box 1527, GR 71110, Heraklion, Crete, Greece;
e-mail: zedd2@iacm.forth.gr
and C. CARTALIS
University of Athens, Dept. of Applied Physics, Building PHYS-V, Athens,
GR 15784, Greece. e-mail: ckartali@cc.uoa.gr
(Received 19 March 2001; in  nal form 6 November 2001 )
Abstract. Detection of plumes produced by industrial accidents using
NOAA/AVHRR thermal imagery may be substantially supported in urban areas
by the presence of the heat island phenomenon. In this study, an attempt is made
to classify the urban web on the basis of the heat island and its impact on the
brightness temperatures. Application of the classi cation scheme on a night-time
thermal infrared NOAA-14 image depicting the urban web of Athens demonstrates
the potential of this classi cation for the detection of a plume caused by a  re in
a warehouse. Detection of the plume in this case is favoured by the urban heat
island phenomenon due to which the urban surface has higher temperature
compared to the adjacent environment and the plume above. As a result, distinc-
tion of the pixels corresponding to the plume is more eVective.
1. Introduction
In recent years, and due to a number of incidents involving  res in industrial
installations and warehouses, research has focused on the de nition of the properties
of produced plumes. The diVerence between the temperature of the top of a plume
and the temperature of the adjacent environment must be above a certain value for
a plume to be detectable (Chung and Le 1984, Scorer 1987). This temperature
diVerence can be estimated using thermal infrared images of the Advanced Very
High Resolution Radiometer (AVHRR) on board the National Oceanic and
Atmospheric Administration (NOAA) satellites.
Detection of a plume is favoured by the urban heat island phenomenon due to
the fact that the urban surface has higher temperature than the adjacent environment
and the plume above. As a result pixels that correspond to the land surface present
strong temperature diVerences to the pixels corresponding to the top of the plume.
* Author for correspondence
Internationa l Journal of Remote Sensing
ISSN 0143-1161 print/ISSN 1366-590 1 online © 2002 Taylor & Francis Ltd
http://www.tandf.co.uk/journals
DOI: 10.1080/01431160110111973
N. Chrysoulakis and C. Cartalis2910
This fact allows the plume to be more easily detected in the thermal infrared when
the plume is diVused over a city than when it is diVused over a suburban region.
In this study, an attempt was made to develop a classi cation scheme for urban
areas on the basis of the heat island and its impact on brightness temperatures. The
scheme was used to display a plume that was caused by a  re in the installations of
a Navy warehouse shop in Iera Odos, Votanikos in the city of Athens. This display
was based on the distinction of the pixels corresponding to the top of the plume
from those corresponding to the surface of the urban web below, using the AVHRR
Channel 4 (10.3–11.3 m) Brightness Temperature (hereinafter referred to as BT
4
)
diVerences. For this reason, the distribution of BT4 must be estimated for the broader
Athens area.
2. Data and methodology
For the purposes of this study, four high spatial resolution NOAA AVHRR
images (Local Area Coverage) were used as acquired from the Dundee University
and the University of the Aegean satellite stations. All images were night-time (01:44
UTC). Three of the images were taken from NOAA-14 during the period 15–17 July
1998. These dates were selected in order to estimate the intensity of the heat island
phenomenon over the city of Athens, at a time when a high-pressure system was
located over Greece. It should be mentioned that the heat island is favoured by
high-pressure systems and cloud free conditions, especially in summer. The fourth
image was taken from NOAA-14 on 7 March 1998. This date was selected because
at 20:30 Local Time a  re developed in the installations of a Navy warehouse shop
in Iera Odos, Votanikos in the city of Athens. The  re spread quickly destroying the
food and clothing departments and there also was a human casualty. In  gure 1 the
black spot delimits the area under investigation.
AVHRR has a spatial resolution of 1.1 km at nadir. The images used are in
NOAA Level 1-b format and they are structured in 10-bit (1024 grey level ) words.
Initially AVHRR images were geometrically corrected using the information (Ground
Control Points) embedded in Level 1-b format. Following the geometric correction,
a common projection system was used for all AVHRR images, as well as for the
map of the broader Athens area. At the next stage, AVHRR images were calibrated,
in order to transform grey level values (raw counts or digital numbers) to brightness
temperature values for each pixel of infrared channels.
For the purposes of this study, the spatial distribution of AVHRR channel 4
brightness temperature (BT4 ) for the broader Athens area was de ned. To this end
digital numbers were converted to at-sensor spectral radiances for channel 4, using
equation 1 (Kidwell 1997):
L
4=
A
4(j)
DN+B4(j)
(1)
where DN is the digital number for channel 4, for each pixel. DN varies from 0 to
1023 counts; A
4(j)
is the slope for channel 4 for satellite scan line ( j) (mW m Õ 2 sr Õ 1 cm);
B
4( j)
is the intercept value for channel 4 for satellite scan line ( j) (mW m Õ 2 sr Õ 1 cm);
and L
4
is the spectral radiance for channel 4, for each pixel (mW m Õ 2 sr Õ 1 cm).
A
4(j)
and B
4(j)
were derived from radiometric in- ight calibration following the
NOAA-NESDIS procedure which is based on regular measurements of deep space
and the AVHRR internal blackbody temperature. A
4( j)
and B
4(j)
were embedded in
Level 1-b format and allowed the linear calibration of AVHRR channel 4 using
equation 1. These coeYcients provide a linear radiance (L
4
); consequently a non-
linearity correction for channel 4 should be applied. The corrected radiance for
Remote Sensing L etters 2911
Figure 1. Map of the broader Athens area. The urban web is shown by the dark grey colour.
The black spot delimits the site of the industrial accident (Iera Odos, Votanikos).
channel 4 (RAD4 ) is calculated from L4 values using equation 2 (Kidwell 1997):
RAD
4=
0.92378 (L
4
)+0.0003822(L4
)2+3.72 (2)
RAD4 can be converted to brightness temperature (BT4 ) for each pixel using the
inverse of the Plank function with the appropriate central wave number. Therefore,
BT4 can be calculated using equation 3 (Kidwell 1997):
BT4=
C2v4
lnC1+A C1RAD4B v34D
(3)
where BT4 is the brightness temperature for channel 4, for each pixel (K); RAD4 is
the corrected spectral radiance for channel 4, for each pixel (mW m Õ 2 sr Õ 1 cm);
C1 is the constant 1.1910659×10 Õ 5 mW m Õ 2 sr Õ 1 cm4 ; C2 is the constant
1.438833×10 Õ 5 cm K; and v4
is the central wave number for channel 4 (cm Õ 1). In
N. Chrysoulakis and C. Cartalis2912
this study, we have considered that the surface temperature should be between 270 K
and 310 K. According to Kidwell (1997) v4 must have the value 929.3323 cm Õ 1 .
The aforementioned calibration method has been developed by NOAA-NESDIS
in order to provide prelaunch information to operational data users, that is both
concise and accurate. It corrects the linear radiance estimate instead of correcting
equivalent blackbody temperature values. The error in calculating brightness
temperature values was within 0.1–0.2 K for channel 4 (Sullivan 1999).
Subsequently, a supervised classi cation was performed in all AVHRR channel
4 images. BT
4
values of each pixel were distributed in six classes. In order to de ne
these classes, the mean BT
4
value was calculated for the pixels representing the urban
web. The relative positions of these pixels on the channel 4 image were related to
the map of the broader Athens area ( gure 1). The name and the de nition of each
class are presented in table 1.
The above classi cation scheme, which is in practice a simple thresholding
procedure, was selected to classify the pixels according to their temperature diVerence
from T0 . The width of each class (with the exception of the  rst class and the last
one) is 1 K. Given that the brightness temperature diVerences between pixels corres-
ponding to the top of the plume and pixels corresponding to the urban web are
greater than 1 K (and are enhanced at the presence of the heat island), a distinction
of the pixels is allowed since they are included in diVerent classes. Applying the
thresholding procedure in every AVHRR channel 4 image, a new thematic image is
produced. DiVerent colours are used to display each class on the thematic images.
3. Results
Figures 2(a) and 2(b) present the spatial distribution of BT4 (for T0=296 K and
295 K respectively) resulting from the classi cation of the AVHRR channel 4 bright-
ness temperature images of 15 July 1998 and 16 July 1998. The heat island phenom-
enon is evident in both cases. The pixels corresponding to areas that have been
aVected by the heat island phenomenon are included in the second class (displayed
with red colour). According to the map of  gure 1, these pixels represent the centre
of the city and the area around it. In the same area, some pixels are displayed in
blue (third class). This implies that these pixels have BT
4
which is 1 K less than T
0
and are representative of the industrial area of Athens, which is located near the
centre of the city.
Figure 2(c) presents the spatial distribution of BT4 (for T0=293 K) resulting from
the classi cation of the AVHRR channel 4 brightness temperature image of 17 July
1998. The heat island phenomenon is more evident in this case. The pixels
Table 1. De nition of the six classes that were used in the supervised classi cation scheme.
BT4 value of each pixel de nes the respective class. T0 is the mean BT4 value for the
pixels representing the urban web.
Class name Class de nition
>T0 BT4 " T0+0.5 K
T0 T0 ­ 0.5 K å BT4<T0+0.5 K
T0 ­ 1 (T0 ­ 1)­ 0.5 K å BT4<(T0 ­ 1)+0.5 K
T0 ­ 2 (T0 ­ 2) ­ 0.5 K å BT4<(T0 ­ 2)+0.5 K
T0 ­ 3 (T0 ­ 3) ­ 0.5 K å BT4<(T0 ­ 3)+0.5 K<T0 ­ 3 BT4<(T0 ­ 3)­ 0.5 K
Remote Sensing L etters 2913
Figure 2. Thematic images of the broader Athens area resulting from the classi cation of
the AVHRR channel 4 brightness temperature images of (a) 15, (b) 16 and (c) 17 July
1998 (01.44 UTC). The spatial distribution of BT4 is shown using six distinct classes.
corresponding to areas that have been aVected by the heat island phenomenon are
included in the second class (displayed with red colour). According to the map of
 gure 1(a), these pixels represent the greater part of the city around its centre.
In the above cases, the diVerence in BT
4
between the centre of the city and the
N. Chrysoulakis and C. Cartalis2914
suburban areas (magnitude of the heat island) is about 2–3 K and it is in accordance
to Katsoulis and Theoharatos (1985).
Figure 3(a) presents the spatial distribution of BT
4
(for T
0=
280 K) resulting from
the classi cation of the AVHRR channel 4 brightness temperature image of 7 March
1998. For better display, pixels which have T0 of 0.5 K å BT4<T0+0.5 K are dis-
played with blue colour; these pixels correspond to areas which have been aVected
by the heat island phenomenon. The second class, in this case, includes pixels
representing the coastal area of Athens. At this time of year, the coastal line has
greater temperatures than the centre of the city (see Katsoulis and Theoharatos 1985).
An area in brown appears in the urban web, where only blue or green colours
are expected due to the heat island phenomenon; the corresponding pixels of this
area belong to the  fth class. This implies that lower brightness temperatures (by
approximately 2 K) are observed in this area, which lies over the accident site. This
may be veri ed by creating a digital mask for this (T-shaped) area and by applying
the mask to the map of the broader Athens area. As shown in  gure 3(b), the relative
position of the mask on the map is over Iera Odos, Votanikos, which is the accident
site. It should be mentioned that all images and the map are in the same
projection system.
The assignment of the pixels to the  fth class can be explained from the presence
of the plume over the accident area. Practically, this implies that the pixels for which
the brightness temperature is estimated corresponds to the top of the plume. As a
result, the thermal detection of the pixels corresponding to the plume is favoured by
the heat island phenomenon, due to which a brightness temperature diVerence greater
than 1 K appears, between the pixels corresponding to the top of the plume and the
pixels corresponding to the urban background. If the site of the accident was in the
suburban area, the thermal detection of the plume should be unattainable, because
the pixels corresponding to the top of the plume, as well as the pixels corresponding
to the suburban background, should be included in the same class ( fth) and should
be displayed in the same colour (brown).
4. Conclusions
The temperature diVerence of a plume to its surroundings is typical over the
urban web of a large city at night. Due to the urban heat island phenomenon, pixels
corresponding to the land surface obtain traceable temperature diVerences to pixels
corresponding to the top of the plume. This makes the plume more distinct in the
thermal infrared when diVused over a city, than when diVused over a rural or
suburban area.
The methodology used to assess this temperature diVerence between the plume
and the surface was based on an analysis of the distribution of the brightness
temperature diVerence in AVHRR channel 4. Brightness temperatures (BT4 ) were
calculated by transforming grey level values in brightness temperature values for
each pixel of the geometrically corrected AVHRR channel 4 image. A supervised
classi cation was performed and the BT
4
values were distributed in six classes. These
classes were de ned using the mean BT
4
value for the pixels representing the
urban web.
Using this method, the plume resulting from a  re in the installation of the Navy
warehouse shop in the city of Athens in the Votanikos area was detected. The
thermal detection of the plume was achieved because the pixels corresponding to
the top of the plume and the pixels corresponding to the urban background re ected
Remote Sensing L etters 2915
Figure 3. (a) Thematic image of the broader Athens area as a result of the classi cation of
the AVHRR channel 4 brightness temperature image of 7 March 1998 (01.44 UTC).
The spatial distribution of BT4 is shown using six distinct classes. An area in brown
appears in the urban web, where only blue or green colours should be expected due
to the heat island phenomenon. This area practically refers to the area covered by the
plume produced by an industrial accident. (b) Map of the broader Athens area,
following the application of the digital mask (T-shape black area). This digital mask
has been developed using the pixels which correspond to the plume area detected in
(a). The relative position of the mask on the map, is over Iera Odos, Votanikos, which
is the accident site.
Remote Sensing L etters2916
diVerent classes and could thus be easily separated. In particular, lower brightness
temperatures (by as much as 2 K) correspond to pixels representing the top of
the plume.
References
Chung, Y. S., and Le, H. V., 1984, Detection of forest- re smoke plumes by satellite imagery.
Atmospheric Environment, 18, 2143–2151.
Katsoulis, B. D., and Theoharatos, G. A., 1985, Indications of the urban heat island in
Athens. Journal of Climate and Applied Meteorology, 24, 1296–1302.
Kidwell, K. B. (editor), 1997, NOAA polar orbiter data users guide. (Washington, DC: US
Department of Commerce, National Oceanic and Atmospheric Administration).
Scorer, R. S., 1987, Hot Spots and Plumes: Observation By Meteorologiacal Satellites.
Atmospheric Environment, 21, 1427–1435.
Sullivan, J., 1999, New radiance-based method for AVHRR thermal channel nonlinearity
corrections. International Journal of Remote Sensing, 20, 3493–3501.


Thermal detection of plumes produced by industrial accidents in urban areas based on the presence of the heat

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Thermal detection of plumes produced by industrial accidents in urban areas based on the presence of the heat

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