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 Data DATE TIME LATITUDE LONGITUDE SAT ESR ESR ESR ESR ESR

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)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 spaceVoyager 4.Studied fire patterns in various regions 5.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

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