1. CTCD Fire Activities P. Lewis, L. Rebelo, I. Woodward, P. Bowyer, B. Heung, M. Wooster, D. Roy

2. Fire Workpackage  Aim: – Provide improved estimates and model of global C-release from fires  Identification of existing Burn-Affected Area Datasets  Calibration and Testing of SDGVM Fire Module  End-to-end testing via Satellite C-emission estimates  Generation and Testing of Burn-Affected Area Datasets and Associated Products

5. Mapping of day of burn

6. Degree of burning (~= cc*f)

7. NameData TypeSpatial ExtentTime PeriodSpatial Resolution MODIS Thermal Anomalies productActive FireGlobalFrom 2000 to present1km x 1km WFWActive FireGlobalFrom 1996 to 20010.5 x 0.5 degree WFAActive FireGlobalNov. 1995 to June 2004 with process on going 1km x 1km Web fire mapperActive FireGlobal1km x 1km TRMM VIRS Monthly Fire ProductActive FireRegionalJan 1998 to Aug 20040.5 x 0.5 degree CIMSSActive FireRegionalMay to Oct for 1995 to 19974 km x 4 km AVHRR fire atlas (Australia)Active FireRegional19931km x 1km AVHRR fire atlas (South America)Active FireRegional19931km x 1km AVHRR fire atlas (Africa)Active FireRegionalJune 1992 to June 19941km x 1km GLOBSCARBurned AreaGlobal20001km x 1km GBA2000Burned AreaGlobal20001km x 1km MODIS Burned Area ProductBurned AreaGlobal2000+500 m x 500 m GLOBCARBONBurned AreaGlobal1998-200710km + GBA 82-991982 to 19998km x 8km Canadian Forest ServiceOtherRegional1959 to 1999All fire > 200 ha Mouillot’s DatabaseOtherGlobal1990 to 20001 x 1 degree

8. Issues – Many EO datasets single year only  Though increasing production of longer time series datasets – Active fire detection underestimates fire activity – Non-geo-located products double count fires at swath edges – Burn-affected area mapping needs to account for BRDF effects – General lack of ‘validation’

9. Calibration and Testing of SDGVM Fire Module  regression models based on the simulated SDGVM result – plant function types, temperature, surface soil content and precipitation – Currently using Global Burn Area (GBA) and World Fire Atlas (WFA) data  fitted to estimate the number of fire occurs in a 1 degree pixel.

10. Calibration and Testing of SDGVM Fire Module  Moved to 2-step model: – Logistic model of Fire Occurance – Model to estimate number of fires  Model testing – Canadian large fire data base – SDGVM run to simulate a fraction of the area burn in Canada between 1959 and1999. – data ½ degree resolution. – Initial analysis:  SDGVM fire estimated burnt area is a factor ~3 greater than the LFDB result.  Also shows less variation  does not pick up the extreme years  the time-series from 1958 to 2000 for the SDGVM and the LFDB show little correlation. Current efforts are to understand the possible reasons and hence how to improve the SDGVM prediction.  Demonstrates requirement for further work on model development and requirement for observations

11. End-to-end testing via Satellite C-emission estimates  Wooster producing C-emission estimate from Fire Radiative Energy  FRE from Meteosat Seviri (2004+) – And Boreal region MODIS (2000+)? – Diurnal activity from Seviri  Allows end-to-end testing of models – And estimation of other terms when combined with satellite burn affected area

12. Generation and Testing of Burn-Affected Area Datasets and Associated Products  Working with David Roy in development and testing MODIS burn-affected area product  Testing alternative methods  Examining derived products in S. Africa – Fire return frequency – Seasonality

13. (#fires in 5 years)

15. Monthly area burned as a proportion of the annual total

16. Seasonality of burning 2004

17. ‘Degree of burning’ 2004

18. Degree of burning

19. Fire Frequency  40% of the land surface burned, with 6% (area of approximately 131,420km ° ) burning during each of the five annual fire seasons.  Higher fire frequencies identified in savanna and grassland ecosystems, with shrublands and deciduous broadleaf forests burning less frequently.  Fire return intervals indicate that locations which burn every year do so at the same time each year.  These areas also have a distinct spatial pattern and are predominantly located in the northern section of Angola, southern Zaire and northern Zambia, as well as in a belt along the Namibia/Angola/Botswana borders.

20. Spatial extent  Between 27% and 32% of the study area has burned during each of the five years of observation. This equates to an area of approximately 610,000 to 690,000km 2.  The distribution of burning within each of the main vegetation types is similar from year to year, with a much larger proportion of deciduous broadleaf forests, woody savannas and savannas burning each year in comparison to shrublands and grasslands.

21. Summary #1  Fire models (e.g. SDGVM) based on understanding of ecology and fire interactions – Very limited datasets previously available for testing – EO provides potential for much greater spatial sampling and analysis – FRE provides potential for end-to-end testing of model and C-release

22. Summary #2  Many EO datasets generated – Active fire detection underestimates activity and depends on time of observation – New generation of burn-affected area products under generation provide most high quality information  But need furter testing/validation – Rich source of information available for analysis – But over limited time period

23. Spare slides

24. Active Fire Datasets: Global  MODIS Thermal Anomolies (NASA) – 1 km resolution 2000+ – 2x daily (morning/afternoon) – High confidence of detection if fire observed – Also MODIS Rapid Response System  World Fire Web (GVM/JRC) – 0.5 o resolution AVHRR 1996-2001 – Errors of commision & omission – Different processing methods used at different receiving stations – Frame overlap issues – Discontinued  World Fire Atlas (ESA) – 1995-2004+ night time (A)ATSR – Frame overlap issues – Revisit period ~3 days

25. Active Fire Datasets: Regional  TRMM VIRS Monthly Fire Product – 0.5 o resolution, 1998-2004+ – 38 o S to 28 o N – 2+ observations/day – Moderate detection capability with higher probability of detection in non-forest land cover classes  GOES-8 ABBA Fire Product – 4km x 4km, 1994-1997 – 4x/day – Coverage S. America  AVHRR Fire Atlas (ESA ESRIN) – S. Hemisphere, day time AVHRR, 1993 (1992-1994 Africa) – High confidence detections only

26. Burn Affected Area (Global)  GLOBSCAR (ESA ESRIN) – 1 km, year 2000, monthly or annual – Daytime ATSR-2 data (3 day repeat) 10:30 am – 2 algorithms: combination gives low error of commission – Particular underdetection in United States (open shrubland and grasslands), Australia (open shrublands), Zimbabwe (croplands) and Brazil (broadleaf evergreen forest)  GBA-2000 (JRC/GVM) – 1 km, year 2000 SPOT VGT – Regional algorithms used – R 2 comparisons with TM data from 0.4 (Mozambique) to 0.99 (Botswana) – False detections in sub-Saharan Africa include false detections due to flooding of non- permanent water features as well as due to the presence of hot dark rocks. (but small proportion) – Only burned areas of at least 400ha in size output  MODIS Burned Area product (NASA) – David Roy will discuss – 500m resolution day of burn, monthly product 2000+ – Africa testing: 99.7% correct detections, and lowest in Mozambique (74.3%) (overall R 2 0.8)  GLOBCARBON – Steve Plummer will discuss – ERS-2 / ATSR-2, ENVISAT / AATSR, and SPOT /VEGETATION. ENVISAT / MERIS – global monthly maps of burnt areas for the period 1998-2007 in 10 km, 0.25° and – 0.5° resolution – based on the experience of both GLOBSCAR and GBA-2000. – CTCD testing dataset

27. Burn Affected Area (Regional)  Canadian Forest Service (Large fire database) – 1959-1999+, fires > 200ha – Small proportion of fires but 97% of total area burned – the date (year, month, day, start date, detect date), location (latitude, longitude, Province), cause, size and ecozone of each fire detection.  Mouillot’s Database – 20 th Century fire, 1 o resolution – Reconstructed from various data sources (incomplete) uses ATSR for recent fires