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Fire Measurements Introduction Pre- and Active Fire Measures Ryan and Noste CBI Spatial Severity Assessments. FOR 274: Forest Measurements. Shifting Earth Science Priorities.

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for 274 forest measurements

Fire Measurements

  • Introduction
  • Pre- and Active Fire Measures
  • Ryan and Noste
  • CBI
  • Spatial Severity Assessments

FOR 274: Forest Measurements


Shifting Earth Science Priorities

Research is needed to understand the complex inter-connected roles of biological and climate systems, while understanding the consequences for society, mitigation, and feedbacks in a changing climate.

Reid et al. (Science, 2009)


Shifting Earth Science Priorities

To make meaningful management decisions in the face of uncertainty, physical drivers of climate and their biological response need to be mechanistically connected.

However, understanding of the impacts of climate change is lacking at regional and local scales, where on-the-ground management activities are implemented.

Evaluating Progress of the U.S. Climate Change Science Program: Methods and Preliminary Results (NRC, 2007))


Importance of Wildland Fires

  • Key element in the Earth system.
  • Disturbance agent that rapidly transfers biogeochemical and hydrological stocks stored in terrestrial vegetation to the atmosphere.
  • Affects vegetation, soils, and airflow with substantial effects on the terrestrial, subterranean, and atmospheric cycles within regional water- and air-sheds.
  • Considerable ecological, economic, and social impacts, prompting policy changes and other societal responses to land management.

Wildland Fire Challenges

  • The principal challenges are to quantify the:
  • Structure and heterogeneity of pre-fire fuels
  • Energy released during combustion
  • Landscape-scale impacts on soils and vegetation

The Grand Challenge is how to integrate the pre-, active-, and post-fire measurements and physical process models into a robust and well documented framework

Kremens, Smith and Dickinson (2010)


The Next Generation of Fire Spread Models

The WFDS model has been developed by the National institute of Standards and Technology (NIST)



These physics-based fire spread models require parameterization and validation with real-world examples.

This highlights the need to measure the pre-fire fuels, active fire properties, and post-fire effects in a coincident manner.

The data inputs to these models have to be of an adequate spatial and temporal scale to capture natural variations

The research outputs need to sync with those predicted by the models!


Characterization of the Pre-Fire Fuels

Ground based LiDAR enable fuel voxels to be characterized.

Hiers et al (2009)

Image Source: MJ Falkowski


Introducing the Fire Energy Field

This describes the radiant, conductive, and convective energy flow produced by a wildland fire.

To fully characterize the energy field the directions and magnitude of all the component would be known – this would enable reliable predictions of fire effects

fire remote sensing essentials emittance

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

q  = ε T4 [ = 5.67 x 10-8 watts/m2/K4]

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

Fire-Remote Sensing Essentials: Emittance

fires follow the curve

Fires follow the curve

Wooster et al 2005


How Much Fuel (Carbon) is Combusted?

Fire Line Intensity: I = HWR

H is known

Need Measurement of:

W – Fuel Combusted

R – Rate of Spread

In Crown Fires W can be ‘very Difficult’


Energy= εσT4

Andrews and Rothermel 1982 – Heat Per Unit Area:

this equation can be applied to satellite data

This 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,


0 3 6 9 11

Day of Burn


A 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 Africa



= 3.2 million tonnes (1.5 Mtonnes C)

(4.3-5.1 million tonnes adj. for cloud)

Cloud effect

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

using heat flux vs smoke emission relations improving regional emissions air quality modeling

Using Heat Flux vs. Smoke Emission Relations: Improving Regional Emissions/Air Quality Modeling

Ichoku and Kaufman (2005)

improving measures of the wildfire background

Evaluate Contributions Relative to Agriculture/Industry

Improving Measures of the Wildfire Background

With Fire Inputs Without Fire Inputs Difference

Smith, Lamb (WSU), and Potter (PNW) – JFSP (in review)


Remote Sensing of Fires: Surface Changes

Pre-fire surfaces: The fuels or green and yellow (senesced) vegetation

Post-fire surfaces: charred vegetation, mineral (white) ash, exposed soils


Remote Sensing of Fires: Surface Changes

Visible (TM bands 1-3): sharp drop that generally recovers with re-growth

Near infrared (TM band 4): very sharp drop that slowly recovers with re-growth


Remote Sensing of Fires: Surface Changes

Long Near-infrared (TM bands 5 and 7): increase post-fire

Thermal (TM band 6): increase post-fire


Remote Sensing of Fires: Surface Changes

These noticeable changes allow us to easily produce maps of the area burned


Remote Sensing of Fires: Surface Changes

Several options exist: One of the most popular in N. America is the dNBR method




Where, dNBR = NBRprefire – NBRpostfire

In terms of fire management, dNBR maps are often used to produce Burned Area


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 Severity are used inconsistently in the Remote Sensing literature

the severity concern

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

Subjective & Value Laden Term

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

The Severity Concern


Highlights need to evaluate alternative methods


The Burn Severity Map Concern

Multiple Agency’s use the dNBR method

dNBR is a good Measure of Current Canopy Condition




The Severity Concern

  • Value Laden Term
  • Negative Connotations: severity = bad
  • Public & Policy Miscommunication
  • Multiple Definitions in the Literature

* 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


Pre-Fire Condition

Post Fire Effects

Active Fire Characteristics

During Combustion

Following Combustion

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
field measures of post fire effects ryan and noste

The method describes fire severity in terms of the heat received by overstory vegetation and the soil.

  • 5 flame length classes (feet)
  • Class scorch ht. tree mortality (dbh)
  • 1. 0-2 ft 0-9 < 1.0
  • 2. 2-4 ft 9-24 1 - 4.9
  • 3. 4-8 ft 24-64 5 - 8.9
  • 4. 8-12 ft 64-116 9 - 13
  • 5. >12 ft >116 > 13
  • Ground char classes:
  • %Deep %Mod %Light
  • Light Char <2% <15% >80%
  • Moderate <10% >15%
  • Deep >10% >80%

Field Measures of Post-Fire Effects: Ryan and Noste

field measures of post fire effects cbi

Used with dNBR

  • Measures scaled 0-3
  • 15m radius plots
  • Uses 5 Strata:
  • Soil
  • Understory
  • Shrubs / saplings
  • sub-canopy trees
  • overstory

Field Measures of Post-Fire Effects: CBI

With dNBR or CBI how do you know whether effects are caused by the fire and if they are what magnitude of those effects are due to the fire?


“Byram’s Fire Intensity equation contains about as much information about a fire’s behavior as can be crammed into one number.”

Van Wagner (1977)