FIRE MONITORING: Towards Fire Damage Assessment

1. FIRE MONITORING: Towards Fire Damage Assessment Opha Pauline Dube, John Isaac Molefe and Sesafeleng Mosotho Department of Environmental Science, University of Botswana, African Monitoring of the Environment for Sustainable Development

2. Fire Detection Near real-time detection offer information on fire location, size, intensity - aid fire suppression • MODIS- special fire bands at 3.9 and 11 micrometer designed to saturate at ~ 500K and 400K, respectively with 4 observations a day offer the best result MSG though offer continuous coverage (15-min repeat cycle) but lower spatial resolution data based on brightness temperatures in channels Ch4 and Ch9

3. FIRMS website Yellow = Hot spots and wilderness areas Density of fires Low High Density of active fires detected from MODIS (Terra) within hotspot and wilderness areas: November 2001 –October 2004

5. Blackbody curves 300K – typical land surface 600K –smoldering fire 1000K –flaming fire

6. Thermal infrared energy emitted by earth features is in the range of 3 - 14um; Fire is detected within this range; Atmospheric effects restrict sensors to two wavelength windows; 3 to 5 um and 8 to 15 um

7. Fire temperature is proportional to thermal radiance emitted in these bands - • facilitating estimation of fire intensity

8. Fire intensity is influenced by Meteorological factors – these are subject to change under climate change Fire Intensity kJ/s/m Air Temperature – 0C Trollope, 3rd SAFNet workshop, Kruger National Park, 2003

9. Fire intensity: Satellite measured as fire Radiative Energy (FRE) release rate or power (FRP) • The Fire Radiative Energy (FRE) is the portion of emitted radiation liberated by the combustion process (Wooster et al. 2003) • Established through the aid of the blackbody concept • The FRP helps categorize fires in terms of intensity i.e. classify fires in terms of power to damage and difficulty to control: • Quantifies the strengths of different fires -. facilitate fire rating by strength as in e.g. earthquakes and hurricans

10. Fire radiative energy (FRE) release of the recognized hotspots Based MODIS and the BIRD satellite, Benin, West Africa (ZHUKOV et al., 2007)

11. Ichoku et al, 2008 in their study on: • “Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy” • Identified 5 RFP categories at global scale: • category 1 (< 100 MW), • category 2 (100 to < 500 MW), • category 3 (500 to < 1000 MW), • category 4 (1000 to < 1500 MW), • category 5 (≥ 1500 MW). • They noted that over 90% of fires globally fall within category 1 • Only less than 1% fall into categories 3 to 5 • - But these proportions may differ significantly from day to day and by season.

13. MODIS Fire Intensity classification for Malawi in 2008 by AFIS system • Each point is assigned a class based on the FRP value • On the right - variation in intensity within land covers is shown.

14. AFIS based: Fire intensity class per land cover - Malawi

15. Classifying fires into different intensities • helps depict areas where intense fires are common. • Together with other information e.g Land cover, fire danger, fuel condition, etc one can be able to know why fires in that area are of very high or low intensity.

16. Information for Fire Damage Assessment • Where did it burn and extent of burn -total area burned. • information on the starting point of the fire to help to investigate the cause • extent and type of fire damage - depending among others on time of burn, fuel load, weather and associated intensity. • An estimate of the cost of the damage: • on and off-site damage/disturbances AND short and long term damages – e.g. Local and offsite effect of smoke; immediate loss of pasture and soil exposure; long term loss of seed bank of perennials SAFNet, 2003 – Kruger National Park MODIS: Greece on 25 August 2007

17. Black carbon (soot) snow/ice albedo feedback- anthropogenic pollution transported to Arctic- increasing local pollution (ships, oil, gas, etc.) BEFORE Observed Arctic Sea-ice Extent AFTER Soot deposition darkens surface  more solar energy absorbed  increases surface temperature  snow melts  more solar energy absorbed  increases surface temperature (same effect with GHGs)

18. Fire can have different effects in different kinds of forests. E.G.: • Some species use the extreme heat of large fires to release their seeds. • Other species need frequent but more mild, low-level fires to thrive – these may not grow back after an intense blaze like this. • Land degradation and emergence of invasive species may eventually follow as a long term effect especially where there is high frequency of intense fires These “not so immediately obvious” effects but with long term far reaching consequences are usually not accounted for in fire damage assessment Idaho firehttp://environment.nationalgeographic.com/

19. In KwaZulu-Natal Province – South Africa • Themeda triandra declined after burning in autumn in comparison to burning in winter and spring, • whereas Tristachya leucothrix responded in the exact opposite manner in these burning timings (Bond & Van Wilgen, 1996).

20. Let’’s now Go try it on our data sets