Copernicus Global Land Vegetation Title...

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First name SURNAMEPosition

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Copernicus Global Land Vegetation

Products

Fernando CAMACHOGlobal Land consortium

Copenhagen, 19/10/2015

EOLAB

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New Horizons for European and Global land monitoring - Copernicus

products and services ready to use, 19-20/10/2015, Copenhagen

Introduction

To monitor the changes on continental biomes, the Copernicus Global Land serviceprovides, in a timely manner, a set of biophysical variables describing the state, thedynamism and the disturbances of the terrestrial vegetation.

Useful for global crop monitoring and the food security applications; environmentalmanagement (desertification, drought, soil erosion risk); land carbon modelling, and weather and climate forecasting.

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Vegetation products

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VariableTemporal Coverage

Temporal resolution

Spatial coverage

Spatial resolution

Sensor Timeliness

LAI / FAPAR / FCOVER 1999 – present 10 days Global 1km PROBA-VSPOT/VGT

3 days

NDVI / VCI / VPI 1999 – present 10 days Global 1kmPROBA-VSPOT/VGT

3 days

Dry Matter Productivity (DMP)

2009 – present 10 days Global 1kmPROBA-V SPOT/VGT

3 days

Burnt Areas (BA) 1999 – present 1 day Global 1kmPROBA-VSPOT/VGT

3 days

• Format: Default (HDF5)

• Projection: Lat/Lon• Native distribution • Documentation: Product User Manual, Algorithm Theoretical Basis Document and Validation Reports• Additional information on product quality: Error estimate, Quality Flags (LAI/FAPAR/FCover)

Cooming soon (1Q2016): 2014 - present, global, 1/3 km, PROBA-V

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GEOVi products

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The algorithms for LAI, FAPAR and FCOVER, developed by INRA, are based

on Neuronal Network trained over existing satellite products. Threedifferent product versions:

GEOV1 (1 km); First version based on fused MODIS and CYCLOPES products. Input: VIS/NIR/SWIR bands. 30-days compositing window, with 12 days of real time (RT) lag.

GEOV2 (1 km); Includes RT estimates, smoothing and gap filling using climatology based on GEOV1. Input: VIS/NIR/SWIR bands. Release 1Q-2016

GEOV3 (1/3 km); For PROBA-V 333m. Includes RT estimates, and smoothing. No climatology at 333m. Input VIS/NIR bands. Release 1Q-2016

NRT &

consolidated

modes

LAI, FAPAR, FCOVER

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LAI, FAPAR, FCOVER

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The Leaf Area Index is defined as half the total area of leaves per unit horizontal ground area. The satellite-derived value corresponds to the total green LAI of all the canopy layers, including the understory. Typicallyranges between 0-7 m2/m2

Temporal profile

Animación

SPOT/VGT PROBA-V

1999

LAI GEOV1

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products and services ready to use, 19-20/10/2015, Copenhagen 6

LAI, FAPAR, FCOVER

The FAPAR quantifies the fraction of the solar radiation absorbed by green leaves for the photosynthesis activity ( 0 – 1

unitless). It is dependent of illumination conditions. The satellite values corresponds to direct illumination at the satellite overpass (10:15 solar local time), which is close to a daily integrated value.

FAPAR GEOV1

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• The Fraction of Vegetation Cover (FCOVER) corresponds tothe fraction of ground covered by green vegetation ( 0 – 1 unitless).

Bit = 0 Bit = 1

Bit 1: Land/Sea Land Sea

Bit 2: Not used

Bit 3: Filled No filled The number of valid observations at (at least)

one side (the left side in the NRT case) of the

±60-day period is lower than 6 and a gap filling

procedure (Bit 13-14) is applied

Bit 4 : Not used

Bit 5: Not used

Bit 6: Input status OK All valid data within ±60 days (- 60 days in the

NRT case) are outside the definition domain

Bit 7: LAI status OK, in expected range

including tolerance

Out of range or invalid

Bit 8: fAPAR status OK, in expected range

including tolerance


Bit 9: FCOVER status OK, in expected range

including tolerance


Bit 10: HLAT status The pixel’s latitude is lower

than 50°

The pixel's latitude is higher than 50º

Bit 11: EBF status Pixel is not recognized as

Evergreen Broadleaf Forest

Pixel is recognized as

Evergreen Broadleaf Forest

Bit 12: BS status Pixel is not recognized as

Bare Soil

Pixel recognized as Bare Soil

Bit 13: Climatology Not filled Filled with climatology

Bit 14: Gap filling Not filled Filled with interpolation

Fcover Error

LAI, FAPAR, FCOVER

FCOVER GEOV1

Quality Flag

LAI/FAPAR/FCOVER are provided with Error field and Quality Flag

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LAI, FAPAR, FCOVER - GEOV3 333m products

1 km

1/3 kmFAPAR

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LAI, FAPAR, FCOVER - GEOV3 333m products

La Reina agricultural site, Córdoba – Spain

1 km

Improved spatial characterisation of vegetation variables at 333m

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NDVI/VCI/VPI

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Evolution to 300m product, including gap-filling (smoothing) methods

The Normalized Difference Vegetation Index (NDVI) is an indicator of thegreenness of the biomes.

Despite it is not a physical property of surfaces, it is still very used due to itssimple formulation: NDVI = (NIR – Red)/(NIR + Red)

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VCI / VPI

●VCI is computed as:VCI yp = (NDVI - MINp) / (MAXp - MINp)with NDVI the observed NDVI value

•The VCI “Vegetation Condition Index” and the VPI “Vegetation Production Index” are two easyways to assess the overall vegetation condition by referencing the current value of the NDVIwith the long-term statistics for the same period.

● The VPI is apercentile ranking ofthe current NDVIvalue against itshistorical range ofvariability.

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Dry Matter Productivity

DMP, or Dry Matter Productivity, represents the overall growth rate or dry biomass increase ofthe vegetation, expressed in kilograms of dry matter per hectare per day (kgDM/ha/day).

DMP is directly related to NPP (Net Primary Productivity, in gC/m²/day), customized for agro-statistical purposes.

Light Use Efficiency model

(similar to Monteith, 1972)

ongoing evolution: improved accuracies through (i) using GEOV2 FAPAR (smoother), (ii) biome specific settings and (iii) use water limitation.

300m product using GEOV3 FAPAR

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The Burnt Area product maps the burnt scars, and gives temporal information on the fire season.

The maps of Burnt Area are recognized as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS).

LAYER NAME DESCRIPTION

CP_DEKAD Contamined Pixel dekad composite:Number of days than do not provide data during the dekad composite

BA_DEKADBurned Area dekad composite:Number of days during the dekad composite the pixel was burned

FDOB_DEKAD First Date Of Burn in the dekad

FDOB_SEASONFirst date of burn just after the season reset:hence a cumulated FDOB value. Dates are reset by seasonal resets.

Burnt Areas

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Comparison with EFFISComparison with Copernicus Emergency

Burnt Areas

Evolution at 333m will allow:

a better characterization of fire shape and perimeter;

the detection of smaller burned areas that are not seen at 1km

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Product Accuracies

Variable User RequirementsGCOS

RequirementsMatch

LAI N/AMax (20%; 0.5)

Not possible to meet GCOS requirements with current ground uncertainties

FAPAR / FCOVERThreshold: 20% Target: 10% Optimal: 5%

Max (10%; 0.05) Yes, Thresholdbiome dependent

NDVI / VCI / VPIOptimal : 0.05

N/A Yes, biome dependent

Dry Matter Productivity (DMP)Threshold: 20% Target: 15%Optimal: 5%

10 daysNot, except for shurblands

Burnt Areas (BA)Accuracy should be competitive with MODIS values

15% (omission and commission) compared to 30 m observations

No, but expected with algorithm evolution ongoing

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Applications

Drought monitoring

Two examples of using FAPAR anomalies as indicator of drought

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Pasture productivity over agro-forestal areas

The GEOV1 FAPAR 1 km product was used as input for monitoring pasture productivity in agro-forestal areas of Andalucia.

The better accuracy of GEOV3 (333m) will improve the use of vegetation products for regional applications

Applications

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Monitoring Soil Erosion Risk

USLE Model (Wischmeier, 1978)

The GEOV1 FCover have been used as indicator of the protective capacity of vegetation against erosion. This allows to provide qualitative maps of the degree of erosion.

For quantitative results of soil loss the FCover should be calibrated mainly for dense natural vegetation (shurbs and forest).

Applications

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DMP can be used for monitoring pastures areas

The DMP is also used in agro-meteorological models to estimate and forecast the crop yield.

Food security

Applications

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Copernicus Global Land is providing operationally a set of global products related with the status and dynamic of vegetation.

Long-time series available since 1999 based on SPOT/VGT

Continuity achieved thanks to PROBA-V, showing good consistency with SPOT/VGT through inter-calibrations across sensors.

Good Quality as compared to ground data and existing sources of information

Global Land is evolving

Adaptation to Sentinels data

Enhanced spatial resolution (up to 100m) for regional applications

Add new products (e.g., Phenology).

Need for R&D

Improve accuracy of existing products

Increase maturity of new products

Investigate the retrieval of new variables

Summary

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Thank you!

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