development of biophysical products for proba-v interest of 300m resolution
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Development of biophysical products for PROBA-V Interest of 300m resolution. F. Baret, M. Weiss & L. Suarez. Interest of 300m resolution for Agriculture. Patch/ object identification. Impact of the spatial resolution. Variability within pixels: - PowerPoint PPT PresentationTRANSCRIPT
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Development of biophysical products for PROBA-VInterest of 300m resolution
F. Baret, M. Weiss & L. Suarez
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Interest of 300m resolution for Agriculture
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Patch/object identification
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Impact of the spatial resolutionVariability within pixels:Normalized Standard Deviation (NSRDV)
Number of patches per pixel
Number of classes per pixel
Purity (patches/classes)
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Conclusion (obvious)
• High spatial resolution is mandatory for agriculture applications (field/species level)– Large differences between 1km and 300m resolution– But large difference also between 300m and 100m!
• Impact on:– classification – disaggregation – LAI estimates (non linearity)
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Development of LAI, FAPAR, FCOVER near real time products from PROVA-V
Objective: Develop biophysical products for PROBA-V• LAI, FAPAR, FCOVER• 10 days frequency• Near real time• Consistent with VEGETATION products (GEOV1/2)• 300m resolution
Impact of higher spatial resolution• No climatology available• Climatology/pixel meaningless• No use of SWIR
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General principles
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Step A: Instantaneous estimates
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Learning from CYCLOPES and MODIS
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Instantaneous estimates
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25 parameters to control step B
Step B: Compositing
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Near real time
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Compositing: eliminating outliers
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Compositing: EBF case
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Compositing: no_EBF case
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GEOV3GEOV1MODIS
Compositing: Filling small gaps
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Conclusion• Associated quality indicators
– Flag– RMSE– Confidence interval from polynomial fit
• Consistency between variables– Same selection of observations used (mostly based on LAI)
• Importance of the compositing step– Without climatology– For short term projection
• Needs to be done:– Implementation of the algorithm– Verification/Validation– Checking consistency with GEOV2 (aggregation at 1km)
• Updating the algorithm when enough actual PROBA-V data will be available• Building a longer time series: process back the MERIS archive?• Combination with S2 -> 20m observations every day?