1 / 27

CTCD Fire Activities

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

leane
Download Presentation

CTCD Fire Activities

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

  3. Mapping of day of burn

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

  5. 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’

  6. 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.

  7. 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

  8. 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

  9. 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

  10. (#fires in 5 years)

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

  12. Seasonality of burning 2004

  13. ‘Degree of burning’ 2004

  14. Degree of burning

  15. 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.

  16. 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 690,000km2 . • 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.

  17. 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

  18. 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

  19. Spare slides

  20. 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) • 0.5o 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

  21. Active Fire Datasets: Regional • TRMM VIRS Monthly Fire Product • 0.5o resolution, 1998-2004+ • 38oS to 28oN • 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

  22. 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 • R2 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 R2 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

  23. 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 • 20th Century fire, 1o resolution • Reconstructed from various data sources (incomplete) uses ATSR for recent fires

More Related