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Processing methodology for full exploitation of daily VEGETATION data C. Vancutsem, P. Defourny and P. Bogaert Environmetry and Geomatics (ENGE) Department.

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Presentation on theme: "Processing methodology for full exploitation of daily VEGETATION data C. Vancutsem, P. Defourny and P. Bogaert Environmetry and Geomatics (ENGE) Department."— Presentation transcript:

1 Processing methodology for full exploitation of daily VEGETATION data C. Vancutsem, P. Defourny and P. Bogaert Environmetry and Geomatics (ENGE) Department of Environmental Sciences and Land Use Planning UCL Université Catholique de Louvain BELGIUM Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002

2 Objective : Develop an operational compositing strategy to produce spatially and temporally consistent images over large areas Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002

3 State of issue Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Selection of specific angle configurations and atmospheric conditions Compositing criteria: BRDF correction: Requires stable land cover time series with low cloud frequency Use only 10% of the information (ten-days compositing) Requires the on-line use of a large archive of daily data

4 Mean compositing strategy Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 The most stable parameter of a distribution The mean NDVI already suggested with AVHRR simulations (Meyer et al., 1995) Robust and simple compositing Use of all the available information

5 Mean Compositing Strategy Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002

6 Prerequisites of the methodology Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march ) Good superposition of the daily images Multitemporal location error < 500m (http://vegetation.cnes.fr/userguide/userguide.htm)http://vegetation.cnes.fr/userguide/userguide.htm

7 Prerequisites of the methodology Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march ) Efficient cloud screening SWIR Blue > 2.48 (Cherlet et al., 2001)

8 Prerequisites of the methodology Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march ) VZA 5-days cycles Compensation between backward and forward angles

9 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Spatial consistency MEAN compositeBestcloudfree imageMVC NDVIMEAN compositeBestcloudfree image Mali, first decade of november 99, (Red, Nir, Mir) MEAN compositeBestcloudfree imageMVC NDVIMEAN compositeBestcloudfree image Nigeria, first decade of november 99, (Red, Nir, Mir)

10 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Spatial consistency First decade of november 99, RCA-Tchad (Red, Nir, Mir) Mean compositeMax NDVI composite

11 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Spatial consistency West Africa, first decade of november 99 (Mir, Nir, Red) Mean composite Max NDVI composite

12 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Spatial consistency West Africa, first decade of november 99 (Mir, Nir, Red) Max NDVI composite Mean composite

13 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Spatial consistency West Africa, first decade of november 99 (Mir, Nir, Red) Max NDVI composite Mean composite

14 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 NDVI channel NIR channel MVC Mean Best daily image Spatial consistency Mali, first decade of november 99

15 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Temporal consistency NDVI channel MVC Mean Tanzania, year 2000

16 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Temporal consistency MVC Mean Observations number Tanzania, year 2000

17 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Reduction of daily variations Tanzania, year % 2.43%8.3% 6.3% RED NIR

18 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Conclusions Robust and operational approach Large spatial and temporal consistency of the results Use all the available information Low sensibility to BRDF effects Accessibility for all users Flexible methodology

19 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Two applications

20 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 For more information : VANCUTSEM, C., BOGAERT, P., DEFOURNY, P., 2002, Mean compositing strategy as an operational temporal synthesis for high temporal resolution, IJRS in press. Contact :

21 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Rush

22 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Temporal consistency Mir channel MVC Mean Tanzania, year 2000 vancutsc: For each pixel, selection of the signal providing the maximum NDVI value amongst the last 10-day acquisitions At the end of 2001 the processing chain will be improved as the cloud screening The compositing strategy is not validated for spectral bands !!! vancutsc: For each pixel, selection of the signal providing the maximum NDVI value amongst the last 10-day acquisitions At the end of 2001 the processing chain will be improved as the cloud screening The compositing strategy is not validated for spectral bands !!!

23 Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Speckle effect MVC NDVI compositeMean composite Nigeria, first decade of november 99 vancutsc: For each pixel, selection of the signal providing the maximum NDVI value amongst the last 10-day acquisitions At the end of 2001 the processing chain will be improved as the cloud screening The compositing strategy is not validated for spectral bands !!! vancutsc: For each pixel, selection of the signal providing the maximum NDVI value amongst the last 10-day acquisitions At the end of 2001 the processing chain will be improved as the cloud screening The compositing strategy is not validated for spectral bands !!!

24 Frequency of compositing Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 & 22 march 2002 Sliding window vancutsc: The current compositing technique for VEGETATION data (VGT-S10 product) shows radiometric artefacts in the reflective bands that may cause a significant noise for subsequent retrievals of surface parameters. The performances of various compositing strategies are assessed as well for the reflective bands as for the NDVI composites. Dedicated indicators and statistical analysis are computed to provide quantitative results by zone and by band. The artefacts we can see on S1 products are more visible on S10 products vancutsc: The current compositing technique for VEGETATION data (VGT-S10 product) shows radiometric artefacts in the reflective bands that may cause a significant noise for subsequent retrievals of surface parameters. The performances of various compositing strategies are assessed as well for the reflective bands as for the NDVI composites. Dedicated indicators and statistical analysis are computed to provide quantitative results by zone and by band. The artefacts we can see on S1 products are more visible on S10 products

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