-1 -3 -6 ) str (Wm Radiance x 10

Analysis of Long

Analysis of Long - - Term Fire Term Fire Dynamics and Impacts on the Dynamics and Impacts on the

Amazon Using Integrated Amazon Using Integrated Multi

Multi - - Source Fire Observations Source Fire Observations

Ivan Csiszar

Ivan Csiszar

, Christopher Schmidt , Christopher Schmidt

, Wilfrid , Wilfrid Schroeder

Schroeder

, Elaine Prins , Elaine Prins

, Alberto Setzer , Alberto Setzer

, Karla , Karla Longo

Longo

and Saulo Freitas and Saulo Freitas

LBALBA--ECO Phase III ECO Phase III --LCLC-35 group-35 group

1

1NOAA/NESDIS Center for Satellite Research and Applications, Camps Springs, NOAA/NESDIS Center for Satellite Research and Applications, Camps Springs, MDMD

22CIMSS/Space Science Engineering Center, University of WisconsinCIMSS/Space Science Engineering Center, University of Wisconsin--Madison, WIMadison, WI

33Earth System Science Interdisciplinary Center, College Park, MDEarth System Science Interdisciplinary Center, College Park, MD

44Consultant in environmental remote sensing applications, Grass Valley, CAConsultant in environmental remote sensing applications, Grass Valley, CA

5

5CPTEC/INPE, Brazil CPTEC/INPE, Brazil

ftp://lba.cptec.inpe.br/presentations/LBA-IV-conference-Nov2008-Manaus/Nov20,2008/Parallel_Sessions_D/AE_656-664/

Regional fire product validation and intercomparison

Online archival of GOES data for South America

(1995-present)

Fire product reprocessing

Communicate validation results to biomass emissions

model

Build emissions inventory for 10+ years of GOES data

LC LC - - 35: Major Tasks 35: Major Tasks

UMD-NASA-NOAA

U. Wisconsin

CPTEC CPTEC

„„

Mass Mass of of the the tracer tracer emitted

emitted : :

α : aboveground biomass density (dry matter basis, kg m

)

β : combustion factor (%)

E

: emission factor (g[η] / kg): gives the total amount of the tracer emitted in terms of the total biomass consumed

a

burnt area

[ ]

[ ] _veg

.

.

.

, M

= α β Ε

a

Source

Source Emission Emission Parameterization Parameterization for for biomass biomass burning

burning

Biomass burning emissions inventory Biomass burning emissions inventory

Regional scale

Regional scale – – daily basis daily basis

[ ]

[ ] _veg

.

.

.

, M

= α β Ε

a

density of carbon data

land use data

near real time fire product

emission & combustion factors

mass estimation CO source emission (kg m^-2day^-1)

Brazilian Biomass Burning Emission model, daily resolution

Validation

Validation – – rates of omission and commission rates of omission and commission

162 ASTER Scenes:

2001 – 06 2002 – 66 2003 – 52 2004 – 29 2005 – 08

122 ETM+ Scenes:

2000 – 1 2001 – 49 2002 – 61 2003 – 12

Jan: 3 Feb: 3 Mar: 2 Apr: 5 May: 5 Jun: 7 Jul: 15 Aug: 47 Sep: 21 Oct: 13 Nov: 1 Dec: 1 Jan: 14

Feb: 5 Mar: 0 Apr: 0 May: 12 Jun: 8 Jul: 3 Aug: 65 Sep: 32 Oct: 19 Nov: 4

Dec: 0 Higher Resolution imagery used to

validate:

119 GOES 8 and 12 images

17,300 fire pixels analyzed 563 WF-ABBA fire detections

135 MODIS Terra images

7,300 fire pixels analyzed 1,640 MOD14 fire detections

ASTER data available free of cost through EOS Data Gateway (special NASA affiliated user account)

ETM+ data available free of cost through GLCF (57) and INPE (65)

ETM+ 10am

ASTER 10:30am

0 5 10 15 20 25 30 35 40 45

0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00

Radiance x 10-6 (Wm-3 str-1 )

Fire x 10^-2 700ºC Sun x 10^-6

6000ºC

ASTER Channel 3N

ASTER Channel 8

( m) ETM+

Channel 4

ETM+

Channel 7

Generating ETM+ Active Fire Masks Generating ETM+ Active Fire Masks

ASTER

ETM+

ASTER bands 3 and 8 and ETM+ bands 4 and 7

0 10 20 30 40 50 60 70

1 2 3 4 5 6 7 8 9 10

Fire Clusters per MODIS pixel

Frequency (%)

ASTER ETM+

Phase II

Validation: impact of non Validation: impact of non - - simultaneous reference data simultaneous reference data

Same- Same - day ASTER (10:30) and Landsat day ASTER (10:30) and Landsat -7 (10:00) imagery - 7 (10:00) imagery

(Csiszar and Schroeder, submitted)

Same Same - - day ETM+ and ASTER day ETM+ and ASTER

Red:

ASTER

Blue:

TM+

Validation:

Validation:

impact of non impact of non - -

simultaneous simultaneous reference data reference data

MODIS detection rates

0.08

0.38

0.51

0.07

0.28 0.33

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

20 40 60

Number of 30m fire pixels

Detection rate

ETM+

ASTER

GOES detection rates

0.01

0.20

0.44

0.66

0.01

0.19

0.40

0.70

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

80 160 240 320

Number of 30m pixels

Detection rate

ETM+

ASTER

ETM+: temporally biased ASTER: simultaneous

Temporally unbiased

NASA

Detection rates as a function of the number of 30m pixels within the pixel footprint

Validation and product

Validation and product intercomparison intercomparison : : what we have learned so far

what we have learned so far

„„

Hot spot counts and detection rates from Hot spot counts and detection rates from daily aggregated GOES detections are

daily aggregated GOES detections are comparable with those from lower

comparable with those from lower

frequency, higher resolution observations frequency, higher resolution observations

„„

Many false detections are associated with Many false detections are associated with land clearing

land clearing

• • false alarm rates lower in the afternoon false alarm rates lower in the afternoon

• • scale scale -dependent - dependent – – different for MODIS and different for MODIS and

GOES GOES

Online GOES Data Archival and Reprocessing Online GOES Data Archival and Reprocessing

„„

The GOES The GOES - - 8 data base for 1995 8 data base for 1995 – – 1999 has been retrieved from 1999 has been retrieved from archive tape and reprocessing has started at SSEC.

archive tape and reprocessing has started at SSEC.

•• 1995 and 1996 data are found to be noisy –1995 and 1996 data are found to be noisy – correction necessarycorrection necessary

•• NCEP model output data are used in reprocessing effortNCEP model output data are used in reprocessing effort

„„

Version 6.5 of the GOES WF_ABBA code provides additional Version 6.5 of the GOES WF_ABBA code provides additional parameters and meta data:

parameters and meta data:

- -

-- Fire Fire RadiativeRadiative Power (FRP) product in addition to Dozier output of Power (FRP) product in addition to Dozier output of instantaneous estimates of fire size and temperature

instantaneous estimates of fire size and temperature

-- block-block-out zones due to solar reflectance, clouds, extreme view out zones due to solar reflectance, clouds, extreme view angles, biome type, etc.

angles, biome type, etc.

-- fire/meta data maskfire/meta data mask

-- revised ASCII fire product output: latitude, longitude, satellite view revised ASCII fire product output: latitude, longitude, satellite view angle, pixel size, 4 and 11 micron brightness temperatures, fire

angle, pixel size, 4 and 11 micron brightness temperatures, fire size size and temperature, FRP, biome type, fire confidence flag

and temperature, FRP, biome type, fire confidence flag

Application of GOES WF_ABBA (version 6.5) Application of GOES WF_ABBA (version 6.5)

Land/Water/Biome Mask Block-out

Zone

Opaque Cloud Mask

GOES 11 micron image

GOES visible image Fire Mask

GOES visible image

GOES 3.9 micron image

Fire Mask

(fire location/confidence, opaque clouds, land/water mask, other biome masks,

block-out zones, bad data indicator, processing region, etc.)

Three years Three years of GOES fire of GOES fire

data data

„ „ Data noisy in Data noisy in first two years first two years

„ „ Further Further

corrections are corrections are

necessary necessary

„„

Noisy data Noisy data

„„

Cloud Cloud

obscuration obscuration

„„

Angular Angular

effects

effects

Twelve years of GOES fire data (2/1) Twelve years of GOES fire data (2/1)

„ „ Data noisy in Data noisy in first two years first two years

„ „ Further Further

corrections are corrections are

necessary necessary

„„

Noisy data Noisy data

„„

Cloud Cloud

obscuration obscuration

„„

Angular Angular effects

effects

Twelve years of GOES fire data (2/2) Twelve years of GOES fire data (2/2)

„ „ Data noisy in Data noisy in first two years first two years

„ „ Further Further

corrections are corrections are

necessary necessary

„„

Noisy data Noisy data

„„

Cloud Cloud

obscuration obscuration

„„

Angular Angular effects

effects

Time series of GOES detections Time series of GOES detections

Based on medium and high possibility fire pixels; no coverage correction

Time series of GOES detections Time series of GOES detections

Based on medium and high possibility fire pixels; no coverage correction

Time series of GOES detections Time series of GOES detections

Based on medium and high possibility fire pixels; no coverage correction

Correction for Omission Correction for Omission

Errors from Cloud Errors from Cloud

Obscuration Obscuration

•Simple approach:

probability of fire under cloud cover

=

probability of fire over cloud-free areas

•Correction based on cloud fraction

•Probabilistic estimation:

•Fire climatology

•Precipitation

•Diurnal fire cycle

-Cloud processing analysis 11% increment

- Simple rule approach: 33% / 40% increments for 40 /120km sampling areas Results for WF

Results for WF--ABBA 2005ABBA 2005

(Schroeder et al., 2008)

Basin wide increment in WF-ABBA fire detections (%)

Correction for Omission Errors from Cloud Obscuration

Correction for Omission Errors from Cloud Obscuration

Angular effects Angular effects

Time series of AVHRR fire counts (nine-day periodicity of view angles)

Number of MODIS fire pixels vs.

sample number within scanline number of fires

detected depends on the position of target area within swath

Different local times

Different seasons

Viewing angles Topography effects

(fixed over time)

Sun angle, glint (changes over time)

Geostationary imagery: geometrical considerations

Product integration Product integration

Terra MODIS

WF_ABBA

Aqua MODIS

Integrated

Yearly detections Integrated product:

correction for

cloud obscuration and

commission errors

Future plans Future plans

„ „ Complete reprocessing 2000 Complete reprocessing 2000 - - 2005 GOES 2005 GOES data with version 6.5

data with version 6.5

„ „ Generate fully corrected time series Generate fully corrected time series

„ „ Compare / Compare / intercalibrate intercalibrate GOES GOES - - only vs. only vs.

merged product for 2000

merged product for 2000 - - 2005 2005

„ „ Evaluate GOES area retrievals using 30m Evaluate GOES area retrievals using 30m data data

„ „ Derive statistics of instantaneous burning Derive statistics of instantaneous burning using 30m observations

using 30m observations

„ „ Generate emission time series Generate emission time series

Related activities Related activities

„ „ Extend GOES system to global Extend GOES system to global geostationary network

geostationary network

„ „ FRP validation FRP validation

„ „ Transition to GOES Transition to GOES - - R and VIIRS R and VIIRS

„ „ GOFC GOFC - - GOLD GOLD

„„

Long Long - - term time series, geo network, transition term time series, geo network, transition

„ „ CGMS CGMS

„„

Sensor characterization Sensor characterization

„ „ CEOS CEOS

„„

Calibration/validation Calibration/validation