qwg7 icor atmospheric correction evaluation qwg7...آ  icor atmospheric correction modtran-5 based...

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  • QWG7 – iCOR atmospheric correction evaluation

    E. Wolters, S. Sterckx, S. Adriaensen

    03/05/2018 VITO Remote sensing

  • remotesensing.vito.be

    Contents

    • iCOR atmospheric correction

    • iCOR processing PROBA-V L2A

    • Evaluation setup

    • Results

    • Summary & recommendation

  • remotesensing.vito.be

    iCOR atmospheric correction  MODTRAN-5 based LUTs

     AOT retrieval based on Guanter et al. (2008)

     Superpixels of 30 x 30 km2  atmosphere invariant within area

     Dark target retrieval (max. AOT boundary), refinement by end- member inversion

     Implementation for PROBA-V:

     AOT LUTs computed for all cameras

     altitude dependent LUTs

     Rural aerosol model

     Application to Level 2A segments (TOA reflectance)

  • remotesensing.vito.be

    iCOR processing

    • 18 AERONET stations selected

    • Time period 2014 – 2015

    • iCOR LUTs for all cameras

    • ~3,500 1 km segments processed

    • Workflow adapted for MEP processing

    • Parallel processing, ~300 executors

    • Run time < 4 h

  • remotesensing.vito.be

    iCOR data processing

    • No iCOR AOT fall-back implemented yet

    • Outside of scope current research

    • Spectrally homogeneous areas: AOT retrieval extrapolated from distant macro- pixels

  • remotesensing.vito.be

    AERONET stations

    AERONET station Coordinates [olon, olat] Altitude [m] Site information Category

    West Africa Banizoumbou (Niger) 2.665 E, 13.541 N 250 Cultivated sandy area. Bare soil

    IER Cinzana (Mali) 5.934 W, 13.278 N 285 Cultivated area. Bare soil

    Zinder Airport (Niger) 8.990 E, 13.777 N 456 Semi-arid cultivated area (from June – October) just south of Zinder.

    Bare soil

    East Asia Beijing (China) 116.381 E, 39.977 N 92 Urban area; instruments located at

    research institute’s rooftop. Urban

    Western Europe

    Aubière LAMP (France) 3.111 E, 45.761 N 423 Located near Clermond Ferrand, urban area.

    Urban

    Bure OPE (France) 5.505 E, 48.562 N 393 Open grassland area near Hourdelaincourt.

    Vegetated

    Carpentras (France) 5.058 E, 44.083 N 100 Cultivated area about 5 km north of Carpentras.

    Vegetated

    Mainz (Germany) 8.300 E, 49.999 N 150 Mixture of urban and rural area, within 1 km from the Main River, moderate to

    highly polluted region.

    Urban

    Murcia (Spain) 1.171 W, 38.001 N 69 Located in rural and dry area, few km west of the city.

    Vegetated

    Toulouse Météo France (France) 1.374 E, 43.575 N 150 Located in rural/urban area southwest of Toulouse.

    Urban

    Davos (Switzerland) 9.844 E, 46.813 N 1596 Located at the northern edge of Davos, close to Davosersee. Clean air.

    Vegetated

    Hohenpeißenberg DWD (Germany) 11.012 E, 47.802 N 990 Located at a mountain top just outside the village.

    Vegetated

    South America

    Alta Floresta (Brazil) 56.104 W, 9.871 S 277 Located near an airport, west of Alta Floresta.

    Vegetated

    Ji Parana SE (Brazil) 61.852 W, 10.934 S 218 In pasture, surrounded by trees. Vegetated

    La Paz (Bolivia) 68.066 W, 16.539 S 3439 Located at the edge of La Paz, air contains mixture of urban and biomass

    burning.

    Bare soil

    North America

    Bonanza Creek (AK, USA) 148.316 W, 64.743 N 150 Field site surrounded by conifer trees. Vegetated

    Goldstone (NV, USA) 116.972 W, 35.233 N 1100 Location in Mojave desert, within Deep Space Network Telescope area.

    Bare soil

    Monterey (CA, USA) 121.855 W, 36.593 N 50 Located near Monterey Airport, ~2 km from a bay.

    Urban

    vegetated

    urban

    Bare soil

  • remotesensing.vito.be

    Performance metrics • Accuracy (A):

    𝐴 = 1

    𝑛 𝜀𝑖

    𝑛

    𝑖=1

    • Precision (P):

    𝑃 = 1

    𝑛 − 1 (𝜀𝑖 − 𝐴)

    2

    𝑛

    𝑖=1

    • Uncertainty (U):

    𝑈 = 1

    𝑛 𝜀𝑖

    2

    𝑛

    𝑖=1

  • remotesensing.vito.be

    iCOR AOT evaluation • AERONET Level 2.0 data

    𝐴𝑂𝑇0.55 = 𝐴𝑂𝑇0.44 𝜆

    𝜆𝑜

    −𝛼

    • AERONET median over +/- 30 min from overpass

    • Cloud cover < 60% over 50 × 50 pixels around station

    • iCOR median over 9 × 9 pixels

  • remotesensing.vito.be

    iCOR TOC reflectance evaluation • Rayference reference dataset (single-pixel)

    • iCOR single pixel values

    • Cloud cover < 60% over 50 × 50 pixels

    • Current operational (‘OP’) TOC from S1 TOC data

    • Temporal collocation using S1 TIME grid

  • remotesensing.vito.be

    Results: iCOR AOT

  • remotesensing.vito.be

    Results: current AOT retrieval AOT retrieval AOT latitudinal fall-back

  • remotesensing.vito.be

    Results: iCOR TOC BLUE

    iCOR

    OP S1

  • remotesensing.vito.be

    Results: iCOR TOC RED

    iCOR

    OP S1

  • remotesensing.vito.be

    Results: iCOR TOC NIR

    iCOR

    OP S1

  • remotesensing.vito.be

    Results: iCOR TOC SWIR

    iCOR

    OP S1

  • remotesensing.vito.be

    Results: time series examples Aubière (France, urban) Cinzana (Mali, BS)

  • remotesensing.vito.be

    Results: time series examples Monterey (USA, urban) Carpentras (France, veg)

  • remotesensing.vito.be

    Summary AOT

    • iCOR compares well against AERONET over vegetated and urban areas

    • Low agreement over bare soils  lack of spectral variability, fall-back necessary

    • Results conform ACIX evaluation (LS 8 & S-2A)

  • remotesensing.vito.be

    Summary TOC reflectance

    • Performance differences iCOR vs OP S1 TOC small

    • Slight improvement for BLUE, RED over vegetation

    • iCOR performance slightly lower than OP S1 for NIR and SWIR

    • Performance iCOR AOT  iCOR TOC, aerosol models MODTRAN?

  • remotesensing.vito.be

    iCOR vs SMAC aerosol models

    Aerosol type relative contribution

    Water soluble Dust-like Soot ωo @ 0.55 µm [-]

    iCOR (MODTRAN5) 70% 30% 0% 0.943

    SMAC (6S) 29% 70% 1% 0.893

    • Different contributions of water soluble and dust-like aerosols • Small soot contribution in 6S  more absorption

  • remotesensing.vito.be

    Options for C2 AC baseline 1. Maintain SMAC with BLUE/SWIR AOT retrieval

     Provide additional SMAC accuracy information to users (e.g. good, acceptable, unreliable, bad)

     Replace latitudinal fall-back with CAMS NRT/climatology

     Effort 30 – 50 WD

    2. Implement iCOR (given the good AOT retrievals)  Additional research for NIR and SWIR TOC required

     Impact of different aerosol microphysical properties 6S and MODTRAN?

     Larger effort: 70 – 80 WD

  • remotesensing.vito.be

    SMAC: accuracy vs SZA+VZA, WV Proud et al. (2010), SMAC on SEVIRI RED – SWIR, Africa:

    • SMAC accuracy decreases for a.o. joint SZA+VZA > ~100o, WV > 2.0 g cm-2

    Joint SZA+VZA SZA

    AOT WV

  • THANK YOU

    remotesensing.vito.be

    Sentinel-2 image Copernicus Sentinel data (2016)

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