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VALIDATION OF THE NPP VIIRS ACTIVE FIRE PRODUCT. Ivan Csiszar 1 , Wilfrid Schroeder 2 , Louis Giglio 2 , Evan Ellicott 2 , Christopher O. Justice 2 1 NOAA/NESDIS Center for Satellite Applications and Research, Camp Springs, MD 2 University of Maryland, College Park, MD. Outline.

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Validation of the npp viirs active fire product

VALIDATION OF THE NPP VIIRS ACTIVE FIRE PRODUCT

Ivan Csiszar1, Wilfrid Schroeder2, Louis Giglio2, Evan Ellicott2, Christopher O. Justice2

1NOAA/NESDIS Center for Satellite Applications and Research, Camp Springs, MD

2University of Maryland, College Park, MD


Outline

  • VIIRS active fire product overview

  • Active fire validation approach

  • Reference datasets

  • NPP VIIRS validation plan and recent results

  • Conclusion

I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


VIIRS: Visible Infrared Imager Radiometer Suite

Primary fire bands

http://www.ipo.noaa.gov/

I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


Viirs fire product overview
VIIRS fire product overview

  • VIIRS will provide radiometric measurements that offer useful information for the detection and characterization of active fires

    • principal bands: M13 (MIR) and M15 (TIR)

  • Fire Mask Application Related Product (ARP) Baseline algorithm: moderate resolution M13 and M15

    • aggregated native resolution pixels

    • MODIS heritage algorithm

  • Fire detection capability is driven by fire fraction – no direct continuity with any heritage sensor

  • Goal is continuation of (AVHRR-) MODIS heritage

    • Real-time applications

    • Long-term monitoring (GCOS Essential Climate Variable)

I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


Based on modeling using aster fire masks

Example of expected VIIRS detection

(based on modeling using ASTER fire masks)

VIIRS (aggregated)

MODIS

7 Aug 2004 1405 UTC ~11.7o S 56.6o W

(Brazil)

I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


Based on modeling using aster fire masks1

Example of expected VIIRS detection

(based on modeling using ASTER fire masks)

VIIRS (aggregated)

MODIS

7 Aug 2004 1405 UTC ~11.7o S 56.6o W

(Brazil)

I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


Modis vs viirs simulation results
MODIS vs. VIIRS – simulation results

1000 m

750 m

90% probability of detection; boreal forest; nadir view

L. Giglio

I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


Satellite active fire product validation approach
Satellite Active Fire Product Validation Approach

Primary Validation: “The process of assessing by independent means the quality of the data products derived from the system outputs” [Justice et al., 2000]

  • Use of independent data to directly estimate product uncertainty

  • Use of in-situ, airborne or spaceborne reference data sets

    • Scaling-up methods can benefit from more than one coincident reference data set

Layers Normally Used When Scaling-up Fire Data

Ground (point data)

Airborne (<10m)

Spaceborne (10<>100m)

Satellite Product

(~1-4km)

  • Secondary Validation

    • Can be used to verify product consistency (e.g., spatial and temporal distribution of fires)

      • Example of application includes assessment of product performance immediately after launch when reference data aren’t available

      • Ideally, the secondary data set must be validated especially when using similar algorithms/methods

    • May complement primary validation

I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


Reference data requirements spatial
Reference Data Requirements: spatial

PSF MODIS

Reference data must provide good spatial coverage to include effective pixel area plus background

True Positive (MOD14)

False Positive (MOD14)

PSF GOES

MODIS/Terra FRP (MW)

A = Nominal pixel area

B = Effective pixel area

Adjusted Values (PSF):

Left pixel = 69.81 MW

Right pixel = 63.03 MW

Credit: Schroeder et al, 2010

I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


Reference data requirements temporal
Reference Data Requirements: temporal

Maximum separation between satellite fire and independent reference data must be limited to ~15min

Credit: Schroeder et al, 2008

Credit: Giglio, 2007

Credit: Csiszar and Schroeder, 2008

I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


Reference data status ground
Reference Data Status : Ground

  • Collaboration with US Forest Service being established

    • Leverage existing field campaigns

      • Prescribed fire intensive monitoring site in the Florida Panhandle (Rx-CADRE/Eglin Air Force Base) being supported by the Joint Fire Science Program

        • Fire intensity (radiative power), temperature and size measurements

        • Smoke characterization (particulate matter, trace gases)

      • Precribed fires monitoring in National Parks

        • Fire temperature and size

  • Collaboration with Kings College London (M. Wooster – through GOFC-GOLD) being established

    • Prescribed fires in UK

      • Fire intensity (radiative power), temperature and size measurements

      • Smoke characterization (particulate matter, trace gases)

  • Potential for collaboration with researchers in the Amazon (links already established through LBA)

    • Pending approval of regional projects

  • Other collaboration with GOFC-GOLD partners (e.g. Australian partners) being pursued

  • I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


    Reference data status airborne
    Reference Data Status : Airborne

    • Collaboration with US Forest Service and NASA already established

      • Wildfires and prescribed burns in Alaska –NASA/HQ (PI: Charles Ichoku/NASA)

        • Airborne (UAV) mapping of surface fires

        • Airborne (UAV) mapping of smoke plumes

        • Complemented by field survey data

      • Wildfires in Western US (Southern California) (NASA/Ames)

        • Airborne (BeechCraft Kingair) mapping of surface fires

      • Wildfires in Western US (Southern California) (USFS/Pacific Southwest Research Station)

        • Airborne (Beechcraft Kingair) mapping of surface fires (emergency response)

      • Wildfires in Wedstern US (Southern California) –Joint Fire Science Program (PI: Phil Riggan/USFS)

        • Airborne (Beechcraft Kingair) mapping of surface fires (includes validation component of spaceborne fire retrievals)

    I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


    Reference data status spaceborne
    Reference Data Status : Spaceborne

    • Landsat-class data (incl. ASTER) have been used for MODIS, GOES and GOES-R ABI fire detection validation

      • Primary reference data sets include USGS LDCM (Dec 2012), ESA Sentinel 2 (2013)

      • Seeking other complementary assets (national/international)

    • Early afternoon orbit of NPP/VIIRS prevent use of Landsat-class data acquired ~10am

      • Lack of reference data may impair regional-global assessment of VIIRS active fire data

      • Airborne data to fill in gap (limited sampling)

    • Collaboration with DLR being established

      • FireBIRD mission composed of TET-1 (May/2011) and BIROS (Dec/2012) sensors building on previous DLR fire science small satellite (BIRD)

      • Targeted data acquisition @360m resolution (178km swath)

      • Fire-dedicated bands provide quality data for use in support of VIIRS and ABI active fire product development and validation

      • BIROS orbit configuration still open

        • BIROS technical team demonstrated interest in supporting validation efforts

        • Ongoing discussion to increase overlap/coincident acquisition with VIIRS

  • Collaboration with CONABIO (Mexico) already established (RedLaTIF)

    • MIROS (2015) mission being proposed based on BIROS technical specs

    • Could augment targeted sampling capacity (increase data volume)

  • I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


    Modis bird coincident acquisition lake baikal russia
    MODIS-BIRD Coincident Acquisition : Lake Baikal (Russia)

    MODIS middle-infrared (fire) band

    BIRD middlfe-infrared (fire) band

    MODIS fire detection pixels

    BIRD fire detection pixels

    High quality reference data (in addition to primary mission objective of stand-alone monitoring)

    Further improvement is expected with HyspIRI

    Credit: Zhukov et al., 2006

    I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


    Heritage modis global fire product validation
    Heritage: MODIS Global Fire Product Validation

    Near-nadir pixels

    (using ~2,500 coincident ASTER scenes)

    Off-nadir pixels

    (using ~3,700 near-coincident TM scenes)

    17K MOD14 pixels sampled

    120K MODIS pixels with 1+ ASTER fire pixel

    12K MOD14 pixels sampled

    270K MODIS pixels with 1+ TM fire pixel

    I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


    Global validation data sets mod14
    Global Validation Data Sets (MOD14)

    Near-nadir pixels

    (using ~2,500 coincident ASTER scenes)

    Off-nadir pixels

    (using ~3,700 near-coincident TM scenes)

    ASTER 2001-2006

    SWIR detector problem > May 2007

    Landsat5 TM 2001-2010

    Fire-related artifacts – saturation/bleeding

    MODIS/ASTER 19 Jan 2006 0852UTC (near nadir)

    MODIS/TM 04 Aug 2007 1533UTC (52o scan angle)

    I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


    Global validation data sets mod141
    Global Validation Data Sets (MOD14)

    Near-nadir pixels

    (using ~2,500 coincident ASTER scenes)

    Off-nadir pixels

    (using ~3,700 near-coincident TM scenes)

    ASTER 2001-2006

    SWIR detector problem > May 2007

    Landsat5 TM 2001-2010

    Fire-related artifacts – saturation/bleeding

    MODIS/ASTER 19 Jan 2006 0852UTC (near nadir)

    MODIS/TM 04 Aug 2007 1533UTC (52o scan angle)

    I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


    View angle effects
    View angle effects

    MODIS Fire Pixels Detected per Sample

    VIIRS Detector Aggregation Scheme

    Diurnal cycle

    Pixel size effect

    JPSS program

    MODIS probability of detection (off nadir)

    MODIS commission error (off nadir)

    I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


    Airborne Data for Validation of Fire Detection and Characterization

    NASA/Ames AMS image of California fire in 2007

    I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


    Current status and plans
    Current status and plans Characterization

    • Cal/val rehearsal – July 18-22, 2011

      • Establish data access

      • Ingest and display of proxy VIIRS Active Fire EDR

      • Comparison with Aqua/MODIS detections

      • Reporting findings through Cal/val Findings Tool

      • Monitoring SDR cal/val results

    • Proposed post-launch algorithm updates

      • Full fire mask

      • Fire Radiative Power

      • Compatibility with MODIS Collection 6

    • Explore potential of alternative and additional VIIRS bands

    • Coordinated efforts with NASA NPP Science Team

      • MODIS – VIIRS continuity

    I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


    Conclusion
    Conclusion Characterization

    • NPP VIIRS fire product validation builds on the validation of MODIS/Terra binary active fire detection data

      • Analyses benefited from the availability of coincident data (MODIS-ASTER pairing)

      • Open data policy (USGS Landsat) making large amounts of reference data available

    • Use of Landsat-class data has and will continue to provide valuable active fire reference data

    • Currently local afternoon hours still poorly sampled

      • Missing a good assessment of peak fire activity

      • Problem likely to persist over the next years

      • Fire data retrieval will be pursued for upcoming missions (LDCM, Sentinel-2, BIROS, HysPIRI)

    • Tropicalregions are more difficult to sample for off-nadir validation analysis

      • Will use secondary validation based on product inter-comparison (MODIS)

    • Development of more robust methods to simulate and test fire detection and characterization algorithms are being pursued

      • Lessons learned from previous MODIS/Terra validation studies to be incorporated

        • Account for pixel spatial response

        • Use of more realistic surface conditions (temperature fields as well as morphology)

        • Additional tests for small-scale heterogeneities (e.g. Deforestation) etc.

    • Fine resolution (airborne) data must be used to constrain simulations and allow product verification on a case-study basis

      • Sample size is not sufficient to resolve all the product dependencies although it can provide vital tie-points for product verification (reality check)

      • Costs can be prohibitive although by combining efforts with other groups the science output could pay off

    I. Csiszar (NOAA), W. Schroeder, L. Giglio, E. Ellicott and C. Justice (UMD)


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