D4.2, D4.3 EUMETSAT, UCL, BC, NPL, JRC, RF QA4ECV Mid-Term Review - - PowerPoint PPT Presentation

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D4.2, D4.3 EUMETSAT, UCL, BC, NPL, JRC, RF QA4ECV Mid-Term Review - - PowerPoint PPT Presentation

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QA4ECV WP4 T4.2 - Development of harmonised retrieval for surface BRDF/albedo, D4.2, D4.3 EUMETSAT, UCL, BC, NPL, JRC, RF QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016 BRDF/Albedo Plan A Overview Development of GlobAlbedo approach

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

QA4ECV WP4 T4.2 - Development of harmonised retrieval for surface BRDF/albedo, D4.2, D4.3

EUMETSAT, UCL, BC, NPL, JRC, RF

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

BRDF/Albedo Plan A

Overview Development of GlobAlbedo approach

  • Linear BRDF models (‘kernel models’)
  • Constraints:

– Heterogeneous observations – Smoothness – Prior mean

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

New setup

  • Stack datasets in time

– So process spatial stack of time series – (e.g. 256x256 blocks)

  • Constraints:

– Heterogeneous satellite observations – Regularisation

  • 2 scales: dt = 1 year; dt = 1 day

– No prior

  • not needed if feed in MODIS observations
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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Plan B Processing Chain

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

GlobAlbedo/Plan B

Approximate optimal solution using weighting on Cobs in time

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Plan A

Formal linear optimisation framework: g smoothness control

Dx at day and year period

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Solution

Low pass filter

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

QA4ECV Plan A

uncertainty

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Heterogeneous

  • bservations

Linear mapping to common spectral basis Hainich

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Spectral mapping: MODIS-MERIS

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Solution

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Speed up

  • Regularisation in time using DCT

– Convenient (reflexive) boundary conditions – Very fast

  • So can afford multiple passes
  • Outlier detection

– Can integrate with uncertainty framework – Can optimise smoothing parameter

  • Fixed in globalbedo (GA)
  • Use GA value as prior and solve for this
  • Or, use Generalised Cross Validation (fast in DCT)
  • So, smoothness then adaptive
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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Summary

  • New approach
  • Full formal linear optimisation system
  • Constraints:

– Observations (inc. MODIS, MERIS, VGT, Proba-V) – Dx (1 day) Dx (1 year) – No need for prior

  • Options for further speedup (DCT)
  • Order datasets by time to make best use
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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Plan B Processing : AVHRR+GEO

MERIS l1b VGT l1p

L1 → SDR Orbit → Tile

SDR

by /sensor/tile/year/day/ti me/

SDR → BBDR/MODIS (Spectral to BB)

BBDR → BB BRDF SDR → Spectral BRDF

MOD/MYD09 (MODIS SDR) SDR → SDR/MODIS

(Spectral mapping)

BRDF-Prior

(Spectral & BB) by /tile/day/

BRDF → Albedo

Albedo (Spectral & BB)

by /tile/year/day/ & /mosaic/year/day/

Proba-V l1b

AVHRR/GEO SDR BB

SDR BB → BBDR/MODIS

(Broadband mapping )

SDR BB

by /sensor/tile/year/da y/

Orbit/disk → Tile

BRDF (Spectral & BB)

by /tile/year/day/

Tiles → Mosaics

(Upscaling by energy conservation)

BRDF (Spectral & BB)

by /mosaic/year/day/ Weights by /sensor/modis- band/time/ SDR/MODIS→ BBDR/MODIS (Spectral to BB) (Weights creation) prior creation

Uniformity

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

T4.2 Development of harmonised retrieval for surface BRDF/albedo

  • Development of harmonised retrieval for surface BRDF/albedo, LAI & FAPAR :
  • New methods for BRDF/albedo retrieval:
  • New instruments:
  • Ingestion of AVHRR-LTDR to broadband BRDF/albedo retrieval
  • Ingestion of GEO (MVIRI+SEVIRI) to broadband BRDF/albedo retrieval
  • New spectral bands:
  • From broadband to spectral BRDF/albedo using MODIS spectral bands
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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Ingestion of AVHRR-LTDR surface reflectance products

  • Use new AVHRR-LTDR reader module recently developed for BEAM/SNAP
  • Supported products are:
  • AVH02C1 (TOA reflectances, daily, global, 0.05deg (7200x3600 pixel))
  • AVH09C1 (Surface reflectances, daily, global, 0.05deg (7200x3600 pixel))
  • The AVHRR-LTDR products are provided by JRC and provide:
  • TOA or Surface reflectances at 630nm and 865nm
  • a quality flag, including a cloud mask
  • Idea: fill AVHRR gaps with Meteosat GEO (MVIRI+SEVIRI) data

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

T4.2 Development of harmonised retrieval for surface BRDF/albedo

Ingestion of AVHRR-LTDR surface reflectance products

  • From global products to MODIS SIN tiles:
  • generate reasonable subsets with BEAM/SNAP subsetting tool
  • reproject to all MODIS SIN tiles (1/20deg resolution as in GlobAlbedo)

which have an intersection with the subset

  • The reprojection module is available in the existing GlobAlbedo processing

chain and has been used for MERIS and VGT in the BBDR retrieval. Adaptation to other sensors is straightforward.

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

From global product to latitude subset:

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Reprojection of latitude subset onto MODIS SIN tiles:

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Ingestion of AVHRR-LTDR surface reflectance products QA quality flag coding:

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Ingestion of Meteosat GEO MVIRI+SEVIRI surface reflectance products

  • We consider the Meteosat GEO MVIRI+SEVIRI BRF daily/10-day ‘disk’ products,

as seen from the satellites’ Equatorial position at different longitudes

  • Use new Meteosat GEO reader module developed for BEAM/SNAP, which uses a

special geolocation algorithm to handle off-planet pixels in the disk product.

  • The ‘disk’ products are reprojected onto a lat/lon grid (1/30deg) and then also
  • nto MODIS SIN tiles (1/120deg) to be merged with AVHRR
  • The products provide: :
  • BRF from wavelength range 0.45 – 1.0 μm and corresponding uncertainty
  • corresponding geometry (SZA, VZA, rel. azimuth) does not come with the

products , their computation was implemented separately

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

From ‘disk’ to lat/lon grid:

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

MODIS SIN tiles within lat/lon area:

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

GEO BRF on 4 MODIS SIN tiles:

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

AVHRR + Meteosat GEO MVIRI+SEVIRI: From BRF to BBDR to BRDF/albedo

  • BRDF/albedo algorithm inherited from GlobAlbedo requires 3 ‘broadband’ input

reflectances: BB_VIS, BB_NIR, BB_SW

  • AVHRR: conversion from band 1 and 2 (630nm and 865nm) to the three

broadbands using coefficients provided by Liang et al. (2000). Corresponding uncertainties are computed from simple error propagation arithmetics

  • MVIRI+SEVIRI: the ‘shortwave broadband’ (representing 0.3 – 3.0 μm, obtained

using the method described by Loew and Govaerts (2010)) is taken as BB_SW

  • sample. No BB_VIS, BB_NIR samples fed into the retrieval
  • Computation of BRDF/albedo with GlobAlbedo algorithm can then be done

separately (using AVHRR or MVIRI/SEVIRI samples only) or by combining the samples

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Albedo from AVHRR and/or MVIRI: examples

  • BRDF/albedo algorithm was used to compute albedo for selected MODIS SIN

tiles for the 8-day periods in year 2005

  • Computations were done with samples from
  • AVHRR alone
  • MVIRI alone
  • AVHRR + MVIRI
  • Examples shown below are BHR/DHR albedo for African tiles h18v06 (Sahara

desert) and h19v08 (tropical rain forest) for 2005, DoY 121. Comparisons with GlobAlbedo results retrieved from MERIS+VGT

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

BHR/DHR h18v06. Left: AVHRR; centre: AVHRR+MVIRI; right: GlobAlbedo

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

BHR/DHR h19v08. Left: AVHRR; centre: AVHRR+MVIRI; right: GlobAlbedo

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

BHR/DHR h18v06 (desert): AVHRR and AVHRR+MVIRI vs. GlobAlbedo MERIS+VGT

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

BHR/DHR h19v08 (rain forest): AVHRR and AVHRR+MVIRI vs. GlobAlbedo MERIS+VGT

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

BHR/DHR h18v06: MSA_Albedo standard product (left) vs AVHRR+MVIRI (right)

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

BHR/DHR h19v08: MSA_Albedo standard product (left) vs AVHRR+MVIRI (right)

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

BHR/DHR h18v06/h19v08: AVHRR+MVIRI vs. MSA_Albedo standard product

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Next steps

  • WP 4.2
  • Complete and test implementation of MODIS spectral mapping

scheme as proposed and presented by UCL.

  • Compare/verify BRFs derived from this with MODIS MOD09

BRFs for selected tiles

  • generate broadband BRDF/albedo from Proba-V (2014-

present) for selected tiles using spectral mapping scheme to VGT wavelengths

  • Test and assess Plan A (NO MODIS prior) scheme from UCL-

Geography on selected tiles

T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Plan B Processing Schema

MERIS l1b VGT l1p

L1 → SDR Orbit → Tile

SDR

by /sensor/tile/year/day/ti me/

SDR → BBDR/MODIS (Spectral to BB)

BBDR → BB BRDF SDR → Spectral BRDF

MOD/MYD09 (MODIS SDR) SDR → SDR/MODIS

(Spectral mapping)

BRDF-Prior

(Spectral & BB) by /tile/day/

BRDF → Albedo

Albedo (Spectral & BB)

by /tile/year/day/ & /mosaic/year/day/

Proba-V l1b

AVHRR/GEO SDR BB

SDR BB → BBDR/MODIS

(Broadband mapping )

SDR BB

by /sensor/tile/year/da y/

Orbit/disk → Tile

BRDF (Spectral & BB)

by /tile/year/day/

Tiles → Mosaics

(Upscaling by energy conservation)

BRDF (Spectral & BB)

by /mosaic/year/day/ Weights by /sensor/modis- band/time/ SDR/MODIS→ BBDR/MODIS (Spectral to BB) (Weights creation) prior creation

Uniformity

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Spectral Mapping

Surface reflectance from sat X Surface reflectance from sat MODIS

Scan for samples close in angle and time and over homogenous and flat areas

MODIS Snow MODIS Landcover DEMs BRDF prior

When CoV is low use Weighted least squares regression: 1st and 2nd order Stage-1 Stage-2

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Tests on North-Africa MERIS: 2002..2011

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Tests on North-Africa MERIS: 2002..2011

Linear least-squares Quadratic least-squares

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Tile: h20v06 (Egypt) Date_Modis: 11 Aug 2011 Date_Meris: 08 Aug 2011 Difference in angles: <5deg MERIS is transformed into the equivalent MODIS Spectral bands and compared. Example: desert MODIS MERIS MERIS vs MODIS

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

T4.2 - DEVELOPMENT OF HARMONISED RETRIEVAL FOR SURFACE BRDF/ALBEDO, LAI & FAPAR

Rayference: Develop atmospheric and surface BRDF retrieval algorithm for MSG/SEVIRI instruments to derive surface albedo in the 0.6, 0.8 and HRVIS bands

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

  • Development of a new algorithm (Combined Inversion of

Surface and AeRosol) for the retrieval of surface albedo and aerosol

  • Several improvements wrt the version used at EUMETSAT

(GSA)

  • Aerosol scattering coupled with water vapour absorption
  • Improved aerosol model with no limitation on the

maximum AOT

  • Continuous variations of the surface parameters in the

solution space (no LUTs)

CISAR ALGORITHM

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

GEO BRF Input

MERIS l1b VGT l1p

L1 → SDR Orbit → Tile

SDR

by /sensor/tile/year/day/ti me/

SDR → BBDR/MODIS (Spectral to BB)

BBDR → BB BRDF SDR → Spectral BRDF

MOD/MYD09 (MODIS SDR) SDR → SDR/MODIS

(Spectral mapping)

BRDF-Prior

(Spectral & BB) by /tile/day/

BRDF → Albedo

Albedo (Spectral & BB)

by /tile/year/day/ & /mosaic/year/day/

Proba-V l1b

AVHRR/GEO SDR BB

SDR BB → BBDR/MODIS

(Broadband mapping )

SDR BB

by /sensor/tile/year/da y/

Orbit/disk → Tile

BRDF (Spectral & BB)

by /tile/year/day/

Tiles → Mosaics

(Upscaling by energy conservation)

BRDF (Spectral & BB)

by /mosaic/year/day/ Weights by /sensor/modis- band/time/ SDR/MODIS→ BBDR/MODIS (Spectral to BB) (Weights creation) prior creation

Uniformity

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

METEOSAT surface albedo archive

Time Range Dataset Satellite DOI 1982-2006 Prime at 0° Meteosat-2,7 10.15770/EUM_SEC_CLM_0001 1998-2006 Indian Ocean Data Coverage at 63°E Meteosat-5 10.15770/EUM_SEC_CLM_0002 2006-ongoing Indian Ocean Data Coverage at 57°E Meteosat-7 10.15770/EUM_SEC_CLM_0003 1991-1983 Atlantic Data Coverage at 50°W Meteosat-3 10.15770/EUM_SEC_CLM_0004 1993-1995 Extended Atlantic Data Coverage at 75°W Meteosat-3 10.15770/EUM_SEC_CLM_0005

Meteosat First Generation have different SSR. For comparing them a spectral conversion is necessary. The method by Loew and Govaerts, 2010 has been applied

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Albedo from METEOSAT

Processing of MVIRI and SEVIRI HRVIS data for generating BRF after 2006 (QA4ECV)

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Spectral BRF Estimation with uncertainty: Processing

ASSUMPTION: The RPV model parameters (K, THETA, R0) retrieved for one day within a 10 days period are assumed to be applicable to the all 10

  • days. This is equivalent to the assumption of not

changing surface properties. The local noon Sun Zenith Angle is calculated and used for estimating the BRF for each day.

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

After long interactions with JPL on polar sea-ice:

  • MISR projection and mapping into lat,lon sorted out
  • Automated ordering of MODIS tiles for sea-ice mask

now feasible for any pole-to-pole swath of MISR

  • Two sample months processed (June and September

2007)

  • Visualisation shows that MISR BRF values appear to

fluctuate too much but can now idnetify sea-ice patterns in albedo

  • JPL will shortly start processing all MISR data from

2000-2016 over both North & South poles T4.2 Development of harmonised retrieval for surface BRDF/albedo

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Sea-Ice animation of MISR: June & September 2007

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Close-up of Sea-Ice animation of MISR: June & September 2007

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Sea-Ice comparison of CLARA-SAL and MISR+MODIS: 20-25 June 2007

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Sea-Ice comparison of CLARA-SAL and MISR+MODIS: 25-30 June 2007

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Work Package 4 Deliverable 4.2 and 4.3: ECV algorithms for LAI and FAPAR

Nadine Gobron

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Deliverable 4.2: Recommendations on best practices for LAI and FAPAR retrieval

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

  • They

use actual sensor measurements (retrieval algorithm can be coded in any ground segment)

  • They are based on

physics, e.g. they take into account spectral response of individual band

  • …

 …

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Generic

  • They

use actual sensor measurements but algorithm depend 1) on past sensors data and results or 2) relationship are made with in-situ measurements.

  • They

are based

  • n

statistical methods

  • They cannot be ‘operational’

nor ‘generic’ by nature … Hybrid

Review Methodologies

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Surface level

  • Bidirectional

Reflectance Factors (BRFs) from multiple single (angular) spectral bands in visible to near- infrared (NIR) bands

  • Normalized

reflectance in visible to near-infrared (NIR) bands

  • Surface albedo in visible and

NIR broadband. Top of atmosphere level

  • BRFs from multiple single

bands in visible to near- infrared (NIR) bands

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Input data Output

Time scale

  • One day with assumption made
  • n anisotropy
  • 8-16 days (depend on time

scale inputs) Spatial Scale

  • Sensor’s spatial resolution pixel

Definition

  • FAPAR: Direct (time of

acquisition, fixed sun zenith angle) and/or diffuse.

  • Effective LAI

Assumption

  • Leaf scattering properties:

‘Green’, ‘Land Cover dependency’, ‘Polychrome’

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

FAPAR comes from energy balance: it is always derived from a canopy RT model: Surface albedo products and absorption should be physically consistent QA4ECV LAI/FAPAR algorithms are generic:

  • physical based (JRC TIP and semi-

discrete models)

  • respective canopy RT model has been

benchmark (RAMI and RAMI4PIPLS)

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Deliverable 4.3: JRC FAPAR

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

JRC FAPAR

  • Operational constraints

– Fast computations – Applying to each single acquisition image (generic algorithm)

  • Scientific constraints

– Take into account sensors spectral properties – Take into account geometries of illumination and view:

  • angular effects
  • (atmospheric effects)
  • Underneath/below vegetation soil

effects

Continuity of ESA MERIS/OLCI products – Instantaneous ‘Green’ FAPAR – Rectified values over both vegetated and soil surfaces. JRC retrieval method assumes that the leaves are alive and photosynthesizing, hence the name “green” FAPAR. It also means that the single scattering albedo of leaves is “fixed” to only one value representing such ‘green’ leaves. JRC-FAPAR also refers to the instantaneous and green value definition. The theoretical FAPAR values are computed with RT model using the closure of the energy balance inside the plant canopy in the spectral range 400 to 700 nm.

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016 58

15 January 2015

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

Optimization of RPV parameters and polynomial coefficients are achieved with RT canopy model simulations

Canopy

red NIR

VZA BRF

Polynomial FAPAR

JRC-FAPAR algorithm AVHRR: Optimization RPV

VZA BRF

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10 spectral responses + One virtual VIS for FAPAR simulations

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016 60

# canopies within TOA version, i.e. MERIS, OLCI, etc. More LAI values

After RPV

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016 61

Uncertainties

where σx

2 and σy 2 are the standard

deviation error of the rectified channels in Band 1 and Band 2, respectively.

We use here the specifications of the AVHRR surface reflectance accuracies (Claverie and Vermote, 2015, personal communication) which correspond to the double of the MODIS surface reflectance specifications ones:

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QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016 62

JRC Mask (Original) LDTR QA