Mapping Heat Production from Wildland Fires using Time-Sequenced Airborne Imaging

1. Mapping Heat Production from Wildland Fires using Time-Sequenced Airborne Imaging Robert Kremens1, Anthony Bova2, Matthew Dickenson2, Jason Faulring1, S. McNamara1 1Rochester Institute of Technology 2USDA Forest Service Northeast Research Station

2. ABSTRACT Heat release maps of a prescribed burn in SE Ohio were created from images captured by a multi-band infrared camera constructed for the Wildfire Airborne Sensor Program (WASP). The entire event (~3 hrs) was captured in multiple frames with typical sampling interval of 5 -10 min. The infrared flux calculated from these frames was time-integrated, producing a map of total heat release, and calibrated using several ground-based infrared sensors that measure thermal flux emitted from the surface. As the sampling interval gives a discontinuous description of fire behavior and, thus, cannot provide exact heat output for all points within the burned area, we have developed an extrapolation method that obtains an upper limit and lower limit to the released thermal energy based on the available imagery and thermal decay rates. We compare the heat release map produced with this method to more than 40 ground-sample stations in an effort to predict fuel consumption and other fire effects parameters. This work has been performed under NASA contract NAG13-02051, and with support from the National Fire Plan, whose support is greatly appreciated.

3. Objectives • Describe the motivation for this work and outline previous efforts • Describe the experimental technique, including the airborne and ground based data collection systems • Describe the image analysis methods • Claim success for our method! • Explain what we missed and future improvements to the method

4. Motivation for this research • We need to know the heat energy released and fire patterns for wildland fires to answer: • Is prescribed fire capable of restoring a natural (pre-suppression) ecology/pattern? • What is the scale and pattern of unburned and heat-affected areas? (laborious using field techniques ) • What is the heat released from the fire? (and gaseous and particulate products) • Are the fire propagation codes accurate and at what spatial and temporal scale? • Does prescribed fire produce a different landscape pattern than ‘wild’ wildland fires?

5. We are attempting to refine and simplify previous (good!) work in this area • Overhead IR methods long used to detect and measure wildland fires • ‘Classic’ method (Riggans et al): • Infer fire temperature using dual band thermometry (MWIR + LWIR) • Estimate emissivity-area product from sensor reaching radiance using inferred temperature from 1 • Calculate the wavelength integrated flux density from 1 and 2 using the Boltzman equation

6. There are several problems with the ‘classic’ method • Requires two or more well-registered, absolutely calibrated cameras (MWIR + LWIR) • Many assumptions, most not proven physically: • The fire can be represented by two temperatures • The assumption of a temperature (implies local LTE) • The spectra is essentially black/grey body • The flux density does not change between exposures • Line emission / absorption from the fire is not significant (e.g. CO, CO2, H2O)

7. We combine overhead and ground based data collection to measure total fire energy output • An ‘in-situ’ method of removing atmospheric and spectral emission effects • Aircraft cameras sample ground at the same point as ground sensors • Clocks are synchronized on aircraft and ground (GPS clock) • Deploy several (2-5) of these ground sensors per fire

8. Collection method and processing chain • Capture a time series of airborne IR images (using WASP imager) • Simultaneously (spatially and temporally) capture ground calibration data and (optionally) burn plot samples (pre- and post- fire) • Geo- and ortho-rectify images, create mosaics • Mask areas not matching 0-heat boundary conditions • Calibrate image data using ground sensors (surface-leaving flux may be obtained from sensor-reaching radiance)

9. Collection method and processing chain (2) 6.Time integrate images to produce total flux map where L = total energy leaving the pixel, Dn = digital data from detector, Dt = time interval between frames, C = calibration derived from nearest ground sensors (W/Dn/pixel), f = frame number, n = total number of frames Advantages: For this work us only LWIR channel Do not need a calibrated instrument No assumptions about the atmosphere, fire spectra Still needs good frame-to-frame registration We still make some (slight) assumptions about the emitted spectral shape

10. The ground sensors were used to absolutely calibrate the airborne images. .

11. A little bit about the WASP camera COTS High Performance Position Measurement Measurement Accuracy Position 3 m Roll/Pitch 0.03 deg Heading 0.10 deg • COTS Camera for VNIR • Proven aerial mapping camera • 4k x 4k pixel format • 12 bit quantization • High quality Kodak CCD 1.5 km at nadir • COTS Cameras for SWIR, MWIR, LWIR • Rugged industrial/aerospace equipment • 640 x 512 pixel format • 14 bit quantization • < 0.05K NEDT 6 km swath from 3 km AGL

12. WASP has detected a 15 cm charcoal test fire at 3300m AGL LWIR MWIR SWIR

13. WASP II quick facts • Resolution at 1500m AGL – 2m IR, 0.3m VIS • Bands: visible (RGB or color IR) 0.9-1.8mm, 3-5mm, 8-11mm • Frame rate: 0.5 Hz Vis, 30 Hz IR • 14 bit dynamic range ~ 12 ½ bit effective • View Angle, 50o fixed, 110o scanning • Coverage @ 120kts @3100m AGL: 100,000 ac/hr • NEDT: measured less than 0.05 K in MWIR • Absolute geolocation accuracy~10m • Geolocation repeatability: ~1.5m

14. Typical WASP ortho- and geo- rectified data product (LWIR Tmax = 800C)

15. The ground based IR flux-weather stations used to calibrate the airborne sensor and obtain in-fire weather data for fire behavior calculations The WASP airborne sensor mounted in the aircraft

16. A little bit about the ground sensors… • In this experiment, the ground sensors allow us to calibrate absolutely and remove the effects of atmospheric absorption • Used for experiments on 6 fires • Measure in-fire weather and infrared flux, optionally several other variables • We have measured key factors for IR remote sensing: burn scar cool down rate, surface flux (outward), emissivity

17. The Vinton Furnace, OH experiment • 3 ½ hour fire duration, ~25 over flights by WASP sensor • 40 ground truth stations (manually sampled before and after) • 3 WX/fire intensity calibration stations • Two line ignition (upper and lower line), hilly terrain • Maple/oak/hickory forest, open with leaf duff and

18. Time Resolved Imaging Example • Five image sequence from prescribed fire in Vinton Furnace OH Images centered on a flux-weather station • Line ignition from top and bottom • Fire coalesces on sensor package near center of image • Time resolved flux measured from image and flux-WX station • Time integral shows fire effects Integrated Fire Intensity

19. Fire intensity/severity map from the time integral of a 10 exposure sequence

20. Discussion • Definite patterns generated by ignition torches/method • Highest heat areas tended to be nearest ignition line • Excellent qualitative agreement was obtained with fuel burn-up and other measures of fire intensity on ground truth • Longest ‘run’ had the most uniform and lowest intensity fires

21. Sanity check: airborne imaging achieved 100% agreement with ground sampling for unburned regions

22. Conclusions and Future Directions • We have developed an in-situ calibration method for overhead IR imaging of fires using fire resistant data loggers • Patterns generated by point ignition (lightning) may be different form line ignition, and heat release (effects) may be significantly different • We obtained proof of the utility of time-sequenced images for rapidly obtaining burned/unburned area maps and fire severity maps • Refinements; • We need to measure upwelled radiance from hot air column above the fire • We may need another channel in the ground-looking calibration measuring instrument • We need to exploit the measured and inferred burn scar cooling curves to give both a lower and upper on flux density

23. References: • Kremens, R.; Faulring, J.; Gallagher, A.; Seema, A.; Vodacek, A. 2003a. Autonomous field- deployable wildland fire sensors. Int. J. of Wildland Fire. (12): 237-244 • Kremens, R.; Faulring, J.; Hardy, C. 2003b. Measurement of the time-temperature and emissivity history of the burn scar for remote sensing applications. 2nd International Wildland Fire Ecology and Fire Management Congress, 16-20 November, Orlando FL. American Meteorological Society • National Wildfire Coordinating Group (NWCG), 1994: Fire Effects Guide. NFES 2394. • Riggans, P.J., Tissel, R.G., Lockwood, R. N., Brass, J.A., Perreira, J.A.R., Miranda, H.S., Miranda, A.C. 2004: Remote measurement of energy and carbon flux from wildfires in Brazil. Eco. Appl. 14(3) 855-872. • Schott, J.A. (1995) Remote Sensing, An Image Chain Approach. Springer Publishing. • Wilson, R.A., Hirsch, S.N., Madden F.H., Losensky, B.J., 1971: Airborne infrared forest fire detection system: final report. USDA Forest Research Paper, INT-93.