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Real Time AVHRR Detection of Forest Fires
and Smoke in Mexico Between January and
June 19981
Ignacio Galind02
Ramon 50lan0 3
Abstract-Using satellite imagery, the whole forest regions of
Mexico are extensively studied to monitor fires and smoke during
the 1998 biomass burning season. The spatial and temporal distribution of fires are examined. Although most of Mexico suffered
from forest fires, the largest number of correlated pixels are located
in the states ofChiapas (4,394, only during May), Durango (4,363,
March to June), Jalisco (3,414, January to March and May),
Guerrero (2760, March-May) and, Oaxaca (2093, April-May). The
largest number of fires occurred in May and haze and smoke covered
most of the country, the Gulf of Mexico and the southern part of the
United States.
We propose a multispectral detection method that operates in
real time. It works on the imagery received before sunrise and
after sunset. A flag is shown together with fire coordinates. At
present the method depicts all kind of biomass burning including
controlled straw and stubble burning for agricultural purposes.
Forest fires occur in Mexico every year between December
and August during the dry season. Usually forest fires peak
on April (Rodriguez-Trejo, 1996). Data for the period 19801997 indicate a yearly average of 6,837 forest fires with a
damaged surface of 223,114 ha, i.e., about 33 ha/fire. More
than 80% of forest fires correspond to shrubs and scrubs
(SEMARNAP, 1998). Although most offorest fires (97%) are
due to human negligence or. deliberate action, however
natural calamities such as hurricanes or the EI Nino/Southern Oscillation (ENSO) events contribute to accumulate
enormous amounts of dry organic matter. These conditions
are associated on the next year to a temporal drought now
called La Nina (SEMARNAP, 1998). In fact, Table 1 data
shows that the largest number offorest fires occur the year
after ENSO events. The previous maximum number of fires
for the period 1980-1997 happens to be 1988.
'
The necessary and sufficient conditions for the development of forest fires were provided by the ENSO event of
1997-98, considered as the most intense of this century,
namely: A very severe drought in most of the country
associated to out of records high temperatures and strong
winds. Maximum temperature for Mexico during the 1998
dry season was higher than the maximum temperature for
the period 1941-1997. The burning for agricultural purposes
Ipaper presented at the North American Science Symposium: Toward a
Unified Framework for Inventorying and Monitoring Forest Ecosystem
Resources, Guadalajara, Mexico, November 1-6,1998.
2 Ignacio Galindo is Professor and Principal Researcher at the Centro
Universitario de Investigaciones en Ciencias del Ambiente, Universidad de
Colima, Mexico.
3 Ramon Solano is Assistant Researcher at the same address.
68
produced also many uncontrolled fires. In spite of the different actions taken to reduce the forest fires risk, the final
balance from January to June, indicates 14,302 fires affecting 583,664 ha (0.4% of the total forest surface). 73% corresponded to grazing land, shrubs and scrubs. 27% corresponded to forest burning in different degrees (i.e., 0.3% of
the total forest surface). The average is 40.81 halfire, that is
about 20% higher than the average for the period 1980-1997.
Satellite data have been used increasingly during the past
few years to examine burning in remote places. One of the
primary sensors on board the NOAA series of polar orbiting
satellites is the Advanced Very High Resolution Radiometer
(AVHRR). This scanning instrument acquires data in five
spectral channels, one in the visual range CO.58 £ I £ 0.68
mm), one in the near infrared range (0.725 £ I £ 1.1 mm) and
three in the thermal range (3.53- 3.93, 10.3-11.3 and 11.512.5 mm). Data are sensed by all five channels simultaneously. The instrument has full resolution of 1.1 km at
nadir.
Although fire detection using satellite data comes back to
1977 when Croft (1977, 1978) presented views of agricultural burning in central Africa, the theory of fire monitoring
using channel 3 was developed by Dozier (1981) and Matson
et al., (1987). At present improvements on fire detection
Table 1.-Forest fires in Mexico, 1980-1997*
Year
1980
1981
1982**
1983**
1984
1985
1986**
1987**
1988
1989
1990
1991 **
1992**
1993
1994**
1995**
1996
1997**
Number of
fires
4,242
2,740
5,599
6,087
6,120
4,386
8,482
9,263
10,492
9,946
3,443
8,621
2,829
10,251
7,830
7,860
9,256
5,163
Area covered
(ha)
Area I Fire
(ha)
110,709
67,228
137,669
272,000
236,032
152,224
290,815
287,347
518,286
507,471
80,400
269,266
44,401
235,020
141,502
309,097
248,765
107,845
26
25
25
45
39
35
34
31
47
51
23
31
16
23
18
39
27
21
*Oirecci6n General Forestal, Subsecretarfa de Recursos Naturales.
SEMARNAP, 1998
**ENSO events
USDA Forest Service Proceedings RMRS-P-12. 1999
2. T3 ~ T4 + 10, where T4 is the AVHRR channel 4
temperature. It ensures that the hot bare soils are not
confused as fire pixels.
3. Albedo Al < Albedomax (2-4%), this is a masking
procedure to avoid pixels having a high albedo due to
clouds and ground features. This condition is applied to
NOAA 12 images received both near to sunset and
sunrise.
4. 268 <T4 < 303 K, this condi tion discriminates false "hot
points" such as water, water clouds over land, hot
rocks, active volcanoes, etc.
methods are made introducing temperature thresholds outlined for channel 3 temperatures with respect to channel 4
temperature (Christopher et al., 1998). Similarly, a technique to estimate satellite-derived burning areas is now in
use (Cahoon et al., 1992). In what follows we present a
multispectral method of forest fire detection. The method
aims a more complete description of burning and smoke
identification, geolocation, and area estimation. This method
is applied for detection of the 1998 Mexican forest fires. All
AVHRR channels are used in order to have a more complete
description of burning and the smoke plume
:.
Data and Methods _ _ _ _ _ __
B) Image Composition
Since April 1994 we have in operation a real-time NOAA
polar-orbiting satellite ground receiving station. The AVHRR
LAC images from NOAA-12 and NOAA-14 are used in this
analysis to map fires and smoke.
Forest fires points overlay on a visible image (channell +
channel 2). Channel 2 offers more ground features and it is
more transparent to aerosol. The combination of both channels produces a compensated image with a clear smoke
plume over ground features.
Since fires can be considerably smaller than the maximum
resolution (-1.1 km by 1.1 km) the data set needs to be
corrected in order to obtain subpixel size high-temperature
sources. Other necessary correction is the removal of water
bodies temperatures initially identified as "hot points" determined with channel 3 data.
The number of pixels with forest fires is distributed for
each month in a matrix array. Each row number corresponds
to the day of the month and the column number contains its
geographical coordinates distributed by states.
Finally, a multispectral data set is constructed containing
all forest fires and the smoke detected in Mexico from
January to June 1998.
,~
A) Fire Dectection
To locate forest fires it is necessary to determine the
geographical coordinates from any pixel in the image located
by its row, or scan line number S and within the scan line by
its column, or pixel number P. The geolocation process, i.e.,
the identification of the values of W (longitude) and N
(latitude) for each pixel (S,P) is electronically made through
a third order polynomial function.
Channels 1 and 2 data identify smoke loading and surface
characteristics. Channel 3 data provide information during
night on fires as ''hot spots" (Matson et al., 1987). Surface
temperature in the fire neighborhood is determined using
channels 4 and 5 data.
Several detection schemes are used, however, these methods are dependent on local conditions, a method applicable
over the Amazon was developed by Kaufman et al. (1990),
recently this method is improved by Christopher et al.
(1998). The method here used is adapted to local features. A
pixel is classified as fire if the following conditions are met:
Results _ _ _ _ _ _ _ _ _ __
The total number of pixels per month and state is shown
in Figures 1 to 6. It is noticeable that from January to April
the total pixel average per month was from 27 to 90, however
for May it went to 652 to decay in June to 100.
The first five places for the maximum number offires per
state is shown in Table 2. Whereas the temporal forest fire
distribution from January to June 1998 is shown in Table 3.
1. T3 ~ T3 min , where T3 is the AVHRR channel 3 temperature, T3 min @ 299 K. It ensures that false hot pixels are
counted as biomass burning.
160
149
143
140
en
120
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~./:''f'tf'.:?
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Figure 1.-Forest fires per state detected on real time using AVH RR channel 3 data. January 1998
USDA Forest Service Proceedings RMRS-P-12. 1999
69
~
3+4
350
304
300
I/)
270
Q)
,~
250
0
200
\...
266
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Figure 2.-Forest fires per state detected on real time using AVHRR channel 3 data. February 1998
.. 00
343
350
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300
~C. 250
0
L-
245
241
,,~
223
190
200
ID
..c
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74
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100
99
u
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a
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Figure 3.-Forest fires'per state detected on real time using AVH RR channel 3 data. March 1998
500
438
... 50
.. 00
367
361
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~~,
(j) 350
X
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300
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Figure 4.-Forest fires per state detected on real time using AVHRR channel 3 data. April 1998
/
70
USDA Forest Service Proceedings RMRS-P-12. 1999
5000
4394
4500
4000
1!2
3500
.~c..3000
~
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2676
2500
2188
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53
Table 2.-Maximum number of fires per state during the 1998 dry season.
January
February
March
-------------------------------Coahuila
149
Sinaloa
344
Jalisco
143
Puebla
304
Tamaulipas
80
Coahuila
270
Guanajuato
63
Jalisco
266
Veracruz
56
Tamaulipas 177
April
May
June
- - - - - - - - - - - - - - - No. of Pixels- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Michoacan
Coahuila
Guerrero
Durango
Jalisco
Table 3.-Temporal distribution of forest
fires during the 1998 dry season.
Month
Total number of pixels
January
February
March
April
May
June
893
2,603
2,533
2,864
20,870
3,227
Total
32,990
USDA Forest Service Proceedings RMRS-P-12. 1999
343
245
241
230
223
Durango
Oaxaca
Michoacan
Guerrero
Edo. de Mexico
438
367
361
331
252
Chiapas
Jalisco
Durango
Guerrero
Oaxaca
4,394
2,782
2,676
2,188
1,726
Durango
1,019
Sonora
380
Guanajuato
371
Tamaulipas
269
Edo. de Mexico
210
The geographical distribution of all the detected forest
fires in Mexico determined from AVHRR data from January
to June 1998 is shown in Figure 7.
Figure 8 shows a composite image depicting fire points
and the haze and smoke layer originating in the Southeast
from Mexico and Central America spreading over the Gulf of
Mexico. Smoke trajectories are conformed according with
the wind pattern. Figure 9 shows the alignment of smoke
plumes from fires detected on February 28, 1998 where wind
blows northeast.
71
~
~
?
(J>
"I'
\t~
~~~"
Ii:(
~
•
~
~
{)
Figure 7.-Geographical distribution of forest fires in Mexico detected from AVHRR data. January to June 1998
72
USDA Forest Service Proceedings RMRS-P-12. 1999
Figure S.-Composite image (AVHRR channels 1 + 2,3 and 4) showing forest fires (dot points) and the smoke layer spreading over
the Gulf of Mexico. May 8, 1998.
USDA Forest Service Proceedings RMRS-P-12. 1999
73
Figure g.-Composite image (AVHRR channels 1 + 2,3 and 4) showing forest fires (circles) and the alignment of the smoke plumes
in NE direction. February 26, 1998.
74
USDA Forest Service Proceedings RMRS-P-12. 1999
Conclusions ------------------------------
References ____________________
1. From January to June 1998 were recorded in Mexico
14,302 fires affecting 583,664 ha (0.4% of the total forest
surface). 73% corresponded to grazing land, shrubs and
scrubs. 27% to forest burning in different degrees (i.e., 0.3%
ofthe total forest surface). The average is 40.81 halfire, that
is about 20% higher than the average for the period 19801997.
2. A unique AVHRR data set containing the geographical
and temporal distribution of burning for Mexico (JanuaryJune, 1998) is now ready for analysis and assessment of the
impacts on the biodiversity and the effects of smoke on the
regional radiation balance.
3. The largest number of fires occurred in the states of
Chiapas, Durango, Jalisco, Guerrero, and Oaxaca.
4. Burning reach~d a maximum in May covering most of
the country. The smoke reached the Gulf of Mexico and the
southern part of the United States.
5. The forest fire detection method is now operational, it
works on real time basis.
Cahoon, D.R. Jr., Stocks, B., J., Levine, J.S., Cofer III, W.R., and
Chung, C.C., (1992): Evaluation of a Technique for Satellitederived Area Estimation of Forest Fires. J. of Geophys. Res., 97
D4, 3805-3814.
Christopher, S.A, Wang, M.,· Berendes, T.A, Welch, R.A., and
Yang, S.K., (1998): The 1985 Biomass Burning Season in South
America: Satellite Remote Sensing of Fires, Smoke, and Regional
Radiative Energy Budgets. J. Appl. Meteorology, 37, 661-678.
Croft, T.A, (1977): Nocturnal images of the earth from space (Order
Number 68197) (Reston, Virginia: U.S. Geological survey). Cited
in Cracknell, AP., The Advanced Very High Resolution Radiometer (AVHRR). Taylor and Francis, London, pp. 534
Croft, T.A, (1978): Night-time images of the Earth from Space.
Scientific American, 239, No.1, 68-79. Cited in Cracknell, A.P.,
The Advanced Very High Resolution Radiometer (AVHRR). Taylor and Francis, London, pp. 534
Dozier, J., (1981): A method for satellite identification of surface
temperature fields of subpixel resolution. Remote Sensing of
Environment, 11,221-229.
Kaufman, Y.J., Tucker, C.J., and Fung, 1. (1990): Remote sensing of
biomass burning in the tropics. J. Geophys. Res., 95, 9927-9939.
Matson, M., Stephens, G., and Robinson, J. (1987): Fire detection
using data from the NOAA-N satellites. Int. J. ofRemote Sensing,
8,961-970.
Rodriguez-Trejo, D. (1996): Incendios Forestales. Universidad
Aut6noma de Chapingo y Mundi-Prensa, Mexico. pp 167-170.
Secretaria de Medio Ambiente, Recursos Naturales y Pesca
(SEMARNAP) (1998): Los incendios forestales en Mexico, 1998.
36pp.
Acknowledgments
The authors are indebted to Mrs. Myriam Cruz for her
assistance in preparing the manuscript. This research was
partially sponsored by CONACYT (26001-T; 095PN-1297),
Comisi6n Forestal del Estado de Michoacan and,
Subsecretaria de Recursos Naturales (SEMARNAP).
USDA Forest Service Proceedings RMRS-P-12. 1999
75