1

Remote Measurements of

Alistair Smith (and many many others …)Alistair Smith (and many many others …)

Remote Measurements of

Active Fire Behavior and Post-Fire Effects

Remote Sensing: A very Brief OverviewRemote Sensing: A very Brief Overview

~ 5 million years B.C. : Humans Begin to Understand their Environment

Wildlife Management

Hazard Assessment

The Remote Sensing ProcessThe Remote Sensing Process

We aim to: Physically relate surface process to remotely derived measures

2

What’s Happening?What’s Happening?

Fire-Remote Sensing Essentials: ReflectanceFire-Remote Sensing Essentials: Reflectance

100%

5%

5%

8%

40% 10%

More than just redMore than just red

What does the Reflectance Look Like?

3

Fire-Remote Sensing Essentials: EmittanceFire-Remote Sensing Essentials: Emittance

Energy emitted (q λ) at a given wavelength and temperature is given by the Stefan-Boltzmann law:

q λ = εσ T4 [σ = 5.67 x 10-8 watts/m2/K4]

ε = emissivity, 0 <= ε <= 1, and is the efficiency that surface emits energywhen compared to a black body

Fires follow the curveFires follow the curve

Wooster et al 2005

Fire-Remote Sensing Fire Remote Sensing Terminology

4

Fire Intensity, Fire Severity, and Burn Severity…

From Jain T, Pilliod D, Graham R (2004) Tongue-tied. Wildfire. 4, 22-26. [After: DeBano LF, Neary DG,Ffolliott PF (1998) ‘Fire’s effects on ecosystems.’ (John Wiley and Sons: New York) 333 pp.

Source of Confusion: The Terms Fire Severity and Burn Severityare used inconsistently in the Remote Sensing literature

Value Laden Term

• Negative Connotations: severity = bad

• Public & Policy Miscommunication

• Multiple Definitions in the Literature

The Severity Concern

p

* Fire duration and heat transfer

* Vegetation consumption

* White ash production

* Change in surface reflectance

* Alteration in soil properties

* Changes in the litter and duff layers

* Long-term vegetation mortality and recovery

5

The Need for ClarificationThe Need for Clarification

Simplifying the Fire Disturbance Continuum:

• Limit use of the Terms Fire Severity & Burn Severity

• Describe and Quantify the Actual Processes Being Assessed

• Make sure that satellites CAN also measure these processes

Active Fire Characteristics

Post Fire EffectsPre-Fire Condition

During Combustion

Following Combustion

What Can Remote Sensing do for What Can Remote Sensing do for Fire Science?

Vegetation Mortality & Ecosystem Recovery

6

Need immediate Active or Post-fire measures that:

• Relate to active fire characteristics (i.e. intensity) &

• Predict post-fire effects (i.e. severity)

How about the Post-Fire Measures?

From Unburned to Burned Surfaces

DECREASE in Visible-NIR

(in General)

From Unburned to Burned Surfaces

INCREASE in SWIR reflectance

Trigg and Flasse (2000)

7

From Unburned to Burned Surfaces

INCREASE in surface temp

Trigg and Flasse (2000); Smith and Wooster (2005)

Several Remote Methods Use These ChangesSeveral Remote Methods Use These Changes

NIR SWIR

NIR – REDNIR + REDNDVI =

NIR – SWIRNIR + SWIRNBR =

dNBR = NBRprefire - NBRpostfire

Produce Maps of Area Burned and Maps of Vegetation Mortality and Recovery

The Severity ConcernThe Severity Concern

Subjective & Value Laden Term

∆NBR: non-linear asymptotic relationship with CBI that varies with sensor spatial resolution and environment

Van Wagtendonk et al (2004); Epting et al (2005) Lentile et al (2006)

Highlights need to evaluate alternative methods

∆NBR

8

Multiple Agency’s use the dNBR method

dNBR is a good Measure of Current Canopy Condition

The Burn Severity Map Concern

dNBR BAER

Remember our Aim:Remember our Aim:

To physically relate surface process to remotely derived measures

The rapid-response measurement of active fire behavior and immediate post-fire effects is very difficult and immediate post-fire effects is very difficult

Need easy measure that can be related to the fire behavior.

From fire behavior we can predict or model the longer-term ecosystem condition.

Use Cover Fractions Within a PixelUse Cover Fractions Within a Pixel

• Direct Measure via Remote Sensing

• Comparable Measure via Field Methods

• Similar to traditional %Green, %Brown, % Black

Source: Hudak, Morgan, Hardy et al

9

Use Cover Fractions Within a PixelUse Cover Fractions Within a Pixel

• Inherently Scalable

• Use Existing 30m Immediate Post-fire Landsat Data

• Physically Related to Carbon and Water Processes

Source: Smith et al in prep

Measuring Cover Fractions in a PixelMeasuring Cover Fractions in a Pixel

Standard and Simple Method: Linear Spectral Unmixing

Pixel: Green (Leaf) + Brown (dry grass) + Black (char)

We can break a pixel down into component fractions

Mapping Burned Areas: Woodland SavannahMapping Burned Areas: Woodland Savannah

10

Setting a Char Fraction ThresholdSetting a Char Fraction ThresholdSmith et al. RSE (2005)

Smith et al. IJRS (in press)

Landsat ETM (4:3:2)>50% Charcoal

Mapping Burned Area: ComparisonMapping Burned Area: Comparison

Landsat (30m) IKONOS (4m)

Char Fraction >50% Supervised Classification

Smith et al. IJRS (in press)

Using Char Fractions to Predict Post-Fire Effects?Using Char Fractions to Predict Post-Fire Effects?

Jasper Fire, South Dakota started 24th Aug 2000

~33,800 ha Burned in 9 days

Ponderosa Pine Forest

Lentile et al (2005,2006b):Lentile et al (2005,2006b):

1-Yr post-fire Measures in 80 sites

Landsat Image: 14th Sept 2000

11

Compare both ∆NBR and Char Fraction Cover to

1-yr Post-Fire Field Canopy and Sub-Canopy Measures

Also Measure Immediate Post-Fire ∆NBR

Landsat 7:5:4 ∆NBR Char Fraction

R2=0 55

Immediate ∆NBR

R2=0 56

Char Fraction

Canopy Variables: 1-Yr Post FireCanopy Variables: 1-Yr Post Fire Smith, Lentile et al. IJRS (in review)

R 0.55R 0.56

Percentage Live Tree

Immediate ∆NBRChar Fraction

Canopy Variables: 1-Yr Post FireCanopy Variables: 1-Yr Post Fire Lentile, Smith et al. (in review)

R2=0.49R2=0.52

Total Crown Effects (Crown Scorch + Crown Consumption)

12

Retrospective Measurement of the Fire IntensityRetrospective Measurement of the Fire Intensity

R2=0.69

Char Fraction

Bole Scorch (surrogate of flame length Intensity)

What’s Potentially Happening with Bole Scorch?What’s Potentially Happening with Bole Scorch?

Char Fraction = 50%Char Fraction = 75%Char Fraction = 100%

Prediction of Sub-Canopy Ecosystem ConditionPrediction of Sub-Canopy Ecosystem Condition

R2=0.55

Char Fraction

Litter Organic Weight (g/m2)

13

R2=0.29

Immediate ∆NBR

R2=0.47

Char Fraction

Sub-Canopy VariablesSub-Canopy Variables Lentile, Smith et al. (in prep)

Average Bark Thickness

What Can Remote Sensing do for What Can Remote Sensing do for Fire Science?

Fire Behavior and Active Fire Effects

Fire Line Intensity: I = HWR

How Much Fuel (Carbon) is Combusted?

H is known

Need Measurement of:

W – Fuel Combusted

R – Rate of Spread

In Crown Fires W can be ‘very Difficult’

14

Also Many Large Fires Occur in Remote AreasAlso Many Large Fires Occur in Remote Areas

NASA 2000

Andrews and Rothermel 1982 – Heat Per Unit Area:Andrews and Rothermel 1982 – Heat Per Unit Area:

Energy= εσT4

HPA= Energy from Combusting Fuel

- Energy Absorbed by Background

HPA = εσ(T4fire - T4

background)

This Equation can be Applied to Satellite DataThis Equation can be Applied to Satellite Data

Wooster, M.J., et al. (2005) Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release, JGR, 110, D24311, doi:10.1029/2005JD006318,

15

Accurate MeasuresAccurate Measures

Wooster, M.J., et al. (2005) Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release, JGR, 110, D24311, doi:10.1029/2005JD006318,

MODIS BIRD3.9 μm channel images

MODIS andBIRD FRP data in

Boreal Forest

FRP dataMODIS BIRD‘false alarms’

Zhukov, B., et al. (2005) Spaceborne detection and characterization of fires during the Bi-spectral Infrared Detection (BIRD) experimental small satellite mission (2001-2004) Remote Sensing of Environment, 100, 29-51

Regional W Estimates

MIR channel TIR channelMSG SEVIRI

MIR-TIR Fire Map

15 mins imaging frequency

16

0 3 6 9 11Day of Burn

A Week of W: Southern AfricaA Week of W: Southern Africa

Roberts, G., et al. (2005) Retrieval of biomass combustion rates and totals from fire radiative power observations: Application to southern Africa using geostationary SEVIRI Imagery, JGR, 110, D21111, doi: 10.1029/2005JD006018

A Week of W: Southern AfricaA Week of W: Southern Africa

BiomassCombusted

= 3.2 million tonnes (1.5 Mtonnes C)(4.3-5.1 million tonnes adj. for cloud)

ect

Roberts, G., et al. (2005) Retrieval of biomass combustion rates and totals from fire radiative power observations: Application to southern Africa using geostationary SEVIRI Imagery, JGR, 110, D21111, doi: 10.1029/2005JD006018

Clo

ud e

ffe

17

From Energy to Fire BehaviorFrom Energy to Fire Behavior

Head and Backing Grassland Fires

Smith AMS, Wooster MJ (2005) Remote classification of head and backfire types from MODIS fire radiative power observations. International Journal of Wildland Fire 14, 249-254.

From Energy to Fire BehaviorFrom Energy to Fire Behavior

Field

Image

From Energy to Fire Behavior

Crown and Surface Boreal Forest Fires

Wooster M.J, Zhang YH (2004) Boreal forest fires burn less intensely in Russia than in North America. Geophysical Research Letters 31, L20505. doi:10.1029/2004GL020805

18

Fire Behavior Model Emissions (CONSUME/EPM)Fire Behavior Model Emissions (CONSUME/EPM)

Directly Relate Energy to PM Emissions

Linking Energy to Emissions and Air QualityLinking Energy to Emissions and Air Quality

Future: Linking Active Fire Measures to Post-fire EffectsFuture: Linking Active Fire Measures to Post-fire Effects

19

“As a young man, my fondest dream was to become a geographer. However, while working in the Patents Office, I thought deeply about the matter and concluded that it was far too difficult a subject. With some reluctance, I then turned to physics as an alternative.”

- Albert Einstein