michigan tech research institute, michigan technological university, ann arbor, michigan
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Assessment of Alaskan Fire Duration Using Modis Fire Products Lucas P. Spaete, Nancy H.F. French, Richard B. Powell
2005 Fire Season
4/18/2005
6/7/2005
7/27/2005
9/15/2005
11/4/2005
4/18/2005 6/7/2005 7/27/2005 9/15/2005 11/4/2005
MODIS End Date
AIC
C E
nd D
ate
2005
2005 Fire Season
4/18/2005
5/8/2005
5/28/2005
6/17/2005
7/7/2005
7/27/2005
8/16/2005
9/5/2005
4/18/05
5/8/05 5/28/05
6/17/05
7/7/05 7/27/05
8/16/05
9/5/05
MODIS Start Date
AIC
C S
tart
Dat
e
2005
2003 Fire Season
5/19/2003
5/29/2003
6/8/2003
6/18/2003
6/28/2003
7/8/2003
7/18/2003
7/28/2003
8/7/2003
8/17/2003
8/27/2003
5/19/03 6/8/03 6/28/03 7/18/03 8/7/03 8/27/03
MODIS Start Date
AIC
C S
tart
Dat
e
2003
Michigan Tech Research Institute, Michigan Technological University, Ann Arbor, Michigan
IntroductionEach year the Alaska Interagency Coordination Center (AICC) actively monitors wildland fires throughout Alaska. At the conclusion of each fire year the AICC compiles the yearly data into fire specific information. Historically this information has proven useful to scientists studying the historical effects of fire but has fallen short when it comes to studying seasonal aspects of fire occurrence i.e. start date, end date and duration of fires. Until recently the AICC was the only source where fire occurrence information could be obtained. Moderate Resolution Imaging Spectroradiometer (MODIS) satellites AQUA and Terra pass over the same location several times a day capturing information about the landscape with every pass. This increased temporal resolution can be used to look at seasonal aspects of fire occurrence, information that the AICC data fails to capture.
MODIS Rapid Response Fire Data•Detects fires using the fire detection algorithm based on algorithms developed for the AVHRR and TRMM VIRS (Giglio et al.,2003). Was developed for the need of the fire community for MODIS fire data shortly after acquisition to aid in fire management•1 km resolution•Fire Detection Algorithm 4 μm channel > 360K or 4 μm channel >330K and 4 μm channel - 11μm channel > 25K
AICC fire polygons•Vector based fire boundaries•Historical coverage: 1950 – present•Can be linked to Start/End date information for fires starting in 2001
Data Methods
Results
GIS Workflow
Example of a MODIS fire product with classification
MODIS Rapid Response Fire
Data Raster
Raster to Point Data
MODIS Rapid Response Fire
Data Vector
AICC Fire Polygons
Select all points that fall
within fire polygons
MODIS derived start & end date for
each fire
Example of the AICC fire polygons historical coverage. Each year is a different color
High Fire Year
Low Fire Year
MODIS & AICC Start Date Comparisons
MODIS Rapid Response Fire points selected by AICC fire polygons. Earliest fire pixel (highlighted) becomes start date
2003 Fire Season
5/19/2003
6/8/2003
6/28/2003
7/18/2003
8/7/2003
8/27/2003
9/16/2003
10/6/2003
5/19/03 6/8/03 6/28/03 7/18/03 8/7/03 8/27/03 9/16/03 10/6/03
MODIS End Date
AIC
C E
nd D
ate
2003
High Fire Year
Low Fire Year
MODIS & AICC End Date Comparisons
MODIS Duration/Acres burned
0
20
40
60
80
100
120
140
1124
1737
2489
3209
5403
7100
1138
8
1697
6
2119
4
3017
1
5007
9
8212
3
1311
09
1940
15
Acres burned
Du
rati
on
2005
AICC Duration/Acres burned
0
20
40
60
80
100
120
140
1124
1639
2350
3094
3653
6382
8959
1162
1
1697
6
1934
5
2681
0
3567
0
6256
3
1127
06
1544
32
2321
87
Acres burned
Du
rati
on
2005
F=-108 No functional relationship between variablesF=70 a functional relationship between variables
MODIS & AICC Fire Duration by Acres Burned Comparisons
Discussion
Results show that MODIS derived fire data and AICC fire data yield similar start dates but fail to yield similar end dates for all years studied. From these results we can conclude that the end date discrepancies are not determined by the intensity of the fire year i.e. monitoring resources spread to thin, but rather by regulatory and bureaucratic issues i.e. funding timelines, that influence AICC fire data end dates.
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