fire climatology the pattern of fire frequency and the applied qc algorithms
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Fire Climatology
The pattern of fire frequency and the applied QC Algorithms
Presentation Overview
• Introduction• Objectives• Methodology• Creation of the fire database• Discussion of fire patterns• Conclusions
Introduction
• Fire location data are collected by the ERS-2 satellite and mapped monthly
• These data are tabulated into monthly databases– Location resolution is high
(0.001 radians)– The data is available for a
three year span, beginning in 1996
Raw DataDATE TIME LATITUDE LONGITUDE SAT
--------------------------------------------
960801 025841.833 -34.088 -58.982 -.-- ESR
960801 025841.833 -34.075 -58.954 -.-- ESR
960801 025841.982 -34.077 -58.994 -.-- ESR
960801 025841.982 -34.079 -58.985 -.-- ESR
960801 025841.982 -34.075 -58.966 -.-- ESR
•http://shark1.esrin.esa.it/ionia/FIRE/
Objective• Study the data provided by the ERS-2 satellite to:
– Create a database easily browsed by date and location– Determine the spatial and temporal patterns of fires– Recognize and remove data not caused by fires
Motivation• Understand the nature of large-scale fire occurrence
• Create a database of fire locations that can be compared to other data sets
– Smoke data (TOMS satellite)
– Forest Service data
Methodology
1. Collected monthly satellite data (available here)2. Used Access to create a database of fire
frequency with resolutions of one degree latitude and longitude and one day
3. Exported the database to Voyager for browsing in time and space
4. Studied fire patterns in various regions5. Created Voyager scripts to remove non-fire
signals
Database Creation• Turned raw data into an Access database• Database counts the number of fires at a given location and
date– Each twelve digit ID is a unique location and time– This chart shows that there were 285 fires detected on Feb. 8, 1999
between 53° and 54° latitude and 107° and 108° longitude
raw text data LATLONYYMMDD Count960801 025841.833 -34.088 -58.982 -.-- ESR 053107981219 6960801 025841.833 -34.075 -58.954 -.-- ESR 053107990101 2960801 025841.982 -34.077 -58.994 -.-- ESR 053107990202 1960801 025841.982 -34.079 -58.985 -.-- ESR 053107990208 285960801 025841.982 -34.075 -58.966 -.-- ESR 053107990218 12960801 025842.131 -34.070 -58.988 -.-- ESR 053107990416 7
053107990429 3053107990603 4053108970807 1
Viewing the Database in Voyager• Global fire locations from
August 1996 to July 1999– Fires occur in most areas– Absent in large deserts and polar
regions
• Three-year fire count in North America– Log scale– Frequent fires in Mexico,
Central America, and the boreal forests of Canada
– Less common in the contiguous US
Fire Patterns
• Several recognizable patterns of fire frequency can be seen in the database
• Good data (actual fires)– Periodic (seasonal) fires– Sporadic fires– Catastrophic regional events
• Bad data (noise)– Constant– Cyclical
Periodic Fires
• Heavy seasonal burning• Highly regional• Burning season lasts a
few months
Sporadic Fires• Occur during regional dry
periods• Do not cover a large region• Not annual in a given
location
Catastrophic Regional Events
• Non-annual fire events– High fire
counts– Cover a large
region
Constant Noise / Cyclical Noise• Not all signals are from fires• Certain urban areas may
produce counts– Non-periodic noise– Low signal counts
• Cyclical noise is found in oil producing regions
Conclusions
• Fire location data collected by the ERS-2 satellite can be used to understand the patterns of fire frequency
• These patterns (periodic, sporadic, catastrophic) can be used to distinguish real fire data from noise
• A filter system must be created to remove the non-fire signals– Remove non-periodic, low-level noise
• Once the noise is removed, this database can be compared to other data sets
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