cross-correlation between world fire atlas and environmental classifications
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Cross-Correlation between World Fire Atlas and Environmental Classifications
Diane Defrenne, SERCOOlivier Arino, ESA
Objective of the Cross Correlation with Environmental Classifications:
• Develop a set of Fire Behaviour Rules.• Develop a set of Emission prediction factor.• Increasing the WFA confidence.
CLASSIFICATIONS USED TO CROSS CORRELATE WITH THE WFA.
CROSS-CORRELATION WITH METEOROLOGICAL DATA.
CROSS-CORRELATION WITH ATHMOSPHERIC DATA.
FURTHER DEVELOPMENTS.
Classification available:• Meteorological data ECMWF 40 Years Re-Analysis, monthly fields (resolution
2.5°).• Vegetation Classification GLC2000 (30 sec°).• Atmospheric chemistry observation TEMIS, monthly fields (0.25°).
ENVIRONMENTAL CLASSIFICATIONS
Classification Criteria:• Temporal coverage about 5 years between November 1995 and May 2005.• Global Geographical coverage almost complete.
System used to generate the correlations:• Use of the World Fire Atlas Tool that permits the discrimination of the WFA
data in time and space.• Microsoft Visual Basic 6.0• Free GIS object library (www.inovagis.org).
Preliminary processing on the input files:• Generate from each classification file in various format (netcdf, grd, …) a raster file on
Plate Carré.• Manage the various resolution of each classification.
OBJECTIVE Fire Behaviour Rules.
Input: WFA
ECMWF Temperature from ECMWF ERA 40
ECMWF Precipitation from ECMWF ERA 40
Vegetation classification from GLC2000
Output: Hot spots detected from WFA.
Mean of monthly temperature over the region.
Mean of monthly cumulated precipitation over the region.
Classification of Vegetation index from GLC2000 (% of surface use by each vegetation).
Region: South America, Africa, Siberia.
WFA and METEOROLOGICAL CLASSIFICATION
Methodology
•Difference between local climate (Temperature and precipitation).
•Vegetation classification for each tile.
•Correlation between number of fire by month and meteorological parameters (the precipitation and the temperature).
•Extract some fire behaviour rules.
AMAZON
F(time): Time rule, F(T): Temperature rule , F(P): Precipitation rule
AFRICA
Fires depends of Vegetation and Precipitation.
Fires depends of temperature.
Cross-correlation between NO2 concentration and hot spots detected First Results:
Comparison Between NO2 Monthly mean Tropospheric column and the number of fires over Zambia
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100
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600
Apr-96
Jul-96
Oct-96
Jan-97
Apr-97
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Jul-02
Oct-02
Jan-03
Apr-03
Jul-03
Oct-03
Jan-04
Apr-04
Jul-04
Oct-04
Jan-05
Apr-05
number of fires
NO2 Tropospheric columnmean (10e15 molec/cm²)
Comparison Between NO2 Monthly mean Tropospheric column and the number of fires over MOZAMBIQUE
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Apr-96
Jul-96O
ct-96
Jan-97
Apr-97
Jul-97
Oct-97
Jan-98
Apr-98
Jul-98
Oct-98
Jan-99A
pr-99
Jul-99
Oct-99
Jan-00
Apr-00
Jul-00
Oct-00
Jan-01
Apr-01
Jul-01O
ct-01
Jan-02
Apr-02
Jul-02
Oct-02
Jan-03
Apr-03
Jul-03
Oct-03
Jan-04A
pr-04
Jul-04
Oct-04
Jan-05
Apr-05
number of fires
NO2 Tropospheric columnmean (10e15 molec/cm²)
Comparison Between NO2 Monthly mean Tropospheric column and the number of fires over ALGERIA
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Jul-96
Oct-96
Jan-97
Apr-97
Jul-97
Oct-97
Jan-98
Apr-98
Jul-98
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Apr-99
Jul-99
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Jan-00
Apr-00
Jul-00
Oct-00
Jan-01
Apr-01
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Oct-01
Jan-02
Apr-02
Jul-02
Oct-02
Jan-03
Apr-03
Jul-03
Oct-03
Jan-04
Apr-04
Jul-04
Oct-04
Jan-05
Apr-05
number of fires
NO2 Troposphericcolumn mean(10e15 molec/cm²)
Comparison Between NO2 Monthly mean Tropospheric column and the number of fires over PORTUGAL
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Ap
r-96
Jul-9
6
Oct-9
6
Jan
-97
Ap
r-97
Jul-9
7
Oct-9
7
Jan
-98
Ap
r-98
Jul-9
8
Oct-9
8
Jan
-99
Ap
r-99
Jul-9
9
Oct-9
9
Jan
-00
Ap
r-00
Jul-0
0
Oct-0
0
Jan
-01
Ap
r-01
Jul-0
1
Oct-0
1
Jan
-02
Ap
r-02
Jul-0
2
Oct-0
2
Jan
-03
Ap
r-03
Jul-0
3
Oct-0
3
Jan
-04
Ap
r-04
Jul-0
4
Oct-0
4
Jan
-05
Ap
r-05
number of fires
NO2 Tropospheric columnmean (10e15 molec/cm²)
Predicting the No2 Concentration from the hot spots detected by the satellite:
METHODOLOGY:• Divide the region of interest in small tile (5°x5°).• Group the tiles having a similar vegetation following the GLC2000
index.• Select inside each zone a central region of study with enough fires.• Perform a cross-correlation between the number of fires by month
and the No2 mean concentration in a month from march 1996 to may 2005 (without Jan 1998 and November 2003 because data from TEMIS are not available or complete) for each region selected.
• Perform a linear regression over each region.• Try to generate an emission prediction factor for each region and to
find the natural NO2 emission cycle.
ASSUMPTION:• GLC2000 is a fixed vegetation classification the vegetation has
globally changed between 1996 and 2005.• TEMIS NO2 tropospheric concentration data available from April
1996 to date and WFA data available from July 1996 to date.• The emission predictor factor is considering linear and doesn’t take
in consideration the natural NO2 emission cycle.
Using satellite data to better understand Ozone budget. N.Savage
REPARTITION OVER AFRICA:
RegionType of vegetationGLC2000 index
% of the surface covered by this vegetation
Dimension of each area
Total number of fires
Region_1 1 67.66 % 8 x (5°x5°) 9389
Region_22 37.37 %
6 x (5°x5°) 25579 3 33.99 %
Region_33 33.51 %
7 x (5°x5°) 34793 12 29.26 %
Region_412 45.86 %
5 x (5°x5°) 7303 13 35.08 %
GLC2000 Index Vegetation:12 Shrub Cover, closed-open, deciduous (with or without sparse tree layer)13 Herbaceous Cover, closed-open16 Cultivated and managed areas
1 Tree Cover, broadleaved, evergreen2 Tree Cover, broadleaved, deciduous, closed3 Tree Cover, broadleaved, deciduous, open
Discriminate region by GLC2000 Classification
Emission prediction factor
1 C=152,09+31.49(HS)
2 C=88.07+26.46(HS)
NOT ENOUGH HOT SPOTS !!
3 C=?
4 C=163.36+24.90(HS)
5 C=159.84+65.046(HS)
FURTHER DEVELOPMENTS
Behaviour Model:• Fully define F(time), F(precipitation) and F(temperature) from
Cross-correlation over some significant regions• Use ERA 40 4 time daily data set to refine in time the Behaviour
model.
Emission prediction factor:• Results are very encouraging.• Complete the study to define the NO2 emission prediction
factor and seasonal cycle.
Vegetation Classification:• Cross-correlate the WFA data with the classification from
GLOBCOVER for 2005 (available by the end of 2007).
Thank You!
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