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Advanced Thermal/Optical: Fire Applications
E. Chuvieco (Univ. of Alcala, Spain)
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RS is a basic tool to retrieve fire information
Elevation / DTM
Meteorology / climate
Socio-economic data
Soils
Fuel Types
Fuel moisture
Density Duration / size
Recurrence Intensity
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Questions RS may answer
• When will a fire occur? How much potential negative impact?
• Is there an active fire? Where? When did it start? How is it growing? How much energy? How many gas emissions?
• How much area is burned? How often? When in the year? How much biomass is consumed? Are fire characteristics changing?
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Questions RS may answer
• When will a fire occur? How much potential negative impact?
• Is there an active fire? Where? When did it start? How is it growing? How much energy? How many gas emissions?
• How much area is burned? How often? When in the year? How much biomass is consumed? Are fire characteristics changing?
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Fuels Heat source
Oxigen
When – where?
Dryness Lightning
Human
Wind
Terrain Fire ignition
Fire Propagation
Weather - Climate Conditions
Socio-economic conditions
Amount
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Fuels Heat source
Oxigen
When – where?
Dryness Lightning
Human
Wind
Terrain Fire ignition
Fire Propagation
Weather - Climate Conditions
Socio-economic conditions
Amount
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Methods to estimate FMC from RS
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
B3 B4 B1 B2 B5 B6 B7
INVERSE
N Cab Cw Cm
DIRECT
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
B3 B4 B1 B2 B5 B6 B7
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Effects of FMC on leaf reflectance
Yebra et al., 2013 RSE
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Examples of FMC maps 10th June
28th August
geogra.uah.es/fireglobe
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Fuel parameters
Passive optical
Lidar Radar
Horizontal continuity some some some
Vertical distribution no yes some
Biomass loads no yes some
Surface conditions no some some
Crown bulk density no yes no
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Fuel characterization from Lidar
11 Riaño et al, 2003, RSE
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Estimation of Fuel properties
Variable Lidar Parameter
r2 (P<0.001)
Equations
Foliar Biomass FB
Tree height (CH)
0.85 FB=0.39*e(MLH*0.15)
Crown Volume (CV)
(P99-P1)*CH%
0.92 CV=1.11*(P99-P1)*CH%-1.71
CBD FB/CB 0.81 CBD=1.52*FB/CB-0.12
Riaño et al., 2004, RSE 12
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Generation of CBD
13
Colour Infrared Aerial photo
0 100 m N
Lidar flight line
CBD (kg/m3) 1.2
0 Riaño et al., 2004, RSE
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Estimation of Biomass fractions
Garcia et al., 2010, RSE 14
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Multi-sensor: Fuel classification
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Multi-scale: fuel parameters
16 Garcia et al. 2011, IJAEO
Ground Airborne
Garcia et al., 2010, RSE
Garcia et al., 2012, RSE
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Global fuel parameters
17 Pettinari et al. 2014, IJWF
Pettinari et al., 2014, IJWF
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Questions RS may answer
• When will a fire occur? How much potential negative impact?
• Is there an active fire? Where? When did it start? How is it growing? How much energy? How many gas emissions?
• How much area is burned? How often? When in the year? How much biomass is consumed? Are fire characteristics changing?
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Detection of active fires
Smoke
Satellite observation
Thermal Heat Visible - Light
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(Stephens y Matson, 1987)
MIR detection of fires
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MODIS thermal anomalies Aqua satellite of fires across Angola, Central Africa on June 16th 2007
Angola
DRC
Zambia
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Dedicated fire detection systems
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Average fire density (2000-2006)
Chuvieco et al., 2008, GCB
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Length of fire season (2000-2006)
Chuvieco et al., 2008b
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Interanual variability (2000-2006)
Chuvieco et al., 2008b
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0 2 4 6 8 10 12 14 16 18 20 22 24Local Hour
0 2 4 6 8 10 12 14 16 18 20 22 24Local Hour Giglio/Kendall/Justice Jan. 2001
Diurnal cycle
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Estimation of Fire Radiative Power
http://viirsfire.geog.umd.edu/pages/AFPE.php
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Fire radiative power from MODIS active fires (2000-2005)
Giglio et al., 2006, JGR
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Questions RS may answer
• When will a fire occur? How much potential negative impact?
• Is there an active fire? Where? When did it start? How is it growing? How much energy? How many gas emissions?
• How much area is burned? How often? When in the year? How much biomass is consumed? Are fire characteristics changing?
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How much area is burned?
FRA2010 From satellite images
•L3JRC: 3.5 - 4.5 Mkm² (2000-07) •MCD45 c5: 3.3 - 3.6 Mkm² (2000–2006) •GFED v2: 2.97 – 3.74 Mkm² (2001–2004) •GFED v3: 3.39 - 4.31 Mkm² (1997-2009). •Fire_CCI: 3.5-3.7 MKm2
From official FAO statistics (FRA2010): 0.6 Mkm². Based on information from 78 countries
GFED v3
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Total Burned Area (2008) from Fire_CCI
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1 180 365 DoY
Date of Detection (2008) from Fire_CCI
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Burned patch analysis
Mouillot et al., 2015
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Validation aspects / metrics
• Global accuracy. • Error balance. • Temporal stability.
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Sites for validation
• A new full dataset of fire perimeters was derived from multitemporal pairs of Landsat TM/ETM+ data.
• All files are documented following standard CEOS Cal-Val guidelines.
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Landsat images used for validation
• Pre fire post fire BA_result
• Yellow=not burned • Blue=no data (clouds,...) • Red=Burned
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Spatial variation of accuracy (2008)
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Intercomparision
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Intercomparision
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BA trends of different products
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Burn severity
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Comparison with empirical model results
R2= 0.66 Variables included: dNDVI+Sat Tendency to smooth CBI values
R2= 0.63 Supervised simulation
Dr. Viegas
(De Santis and Chuvieco, 2007)
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Other sites
De Santis and Chuvieco, 2009, RSE
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Don miss the global approach!
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Source: Ward et al., 2012
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“Implementation Plan for the Global Observing System for Climate in Support of the UNFCCC
(2010 Update)”
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Essential Climate Variables (ECV)
ECV Fire Disturbance The following is required for this ECV: • Burnt area (T.10) • Active-fire maps (supplemental to T.10) • Fire radiative power (FRP) (supplemental to T.10)
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ESA-CCI programme (ECV)
Aerosol cci Cloud cci
Fire cci
GHG cci
Glaciers cci
Land Cover cci
Ocean Colour cci
Ozone cci
Sea-level cci
Sea Ice cci
Sea Surface Temperature cci Ice Sheets
CMUG
Soil moisture
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Connections of Fire and other ECVs
Aerosol cci
Cloud cci
Fire cci
GHG cci
Land Cover cci
Ozone cci
Sea Surface Temperature cci
CMUG
Soil moisture
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Biomass emissions
• Bottom-up model: Seiler and Crutzen [1980] model:
• FRP related
BA (Burned Area)
CC (Combustion
Completeness)
FL (Fuel Loads)
EF (Emission
Factor)
E (Emissions of Gas N) =
Wooster et al., 2014
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Annual mean fire emissions 1997-2009
Van der Werf et al., 2013 GFED3.1 Global Total: 4.0 Pg year-1
DM burned [g DM m-2 year-1]
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Seasonal trends in carbon emissions
Yue et al., 2015
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Emilio Chuvieco University of Alcalá (Spain)
Final remarks
53
• Fire is a very relevant global and regional issue.
• RS can contribute to the three phases of fire management:
• Pre-fire: Fuel conditions and amount. • Active fires: detecion and fire properties. • Post-fire: burned area, severity and emissions.