1. IGARSS 2011 International Geosience and Remote Sensing Symposium MODELLING COASTAL PROCESSES BY MEANS OF INNOVATIVE INTEGRATION OF REMOTE SENSING TIME SERIES ANALYSIS Taramelli A.1, Valentini E.1, Dejana M.1, Zucca F.2, Mandrone S.1 1ISPRA –InstituteforEnvironmentalProtection and Research Rome– Italy 2Universita degli Studi di Pavia

3. multiscale approach;

4. in situ data for remote data characterization;

5. satellite imagery data fusion;

7. MODELLING Biochemistry LANDSCAPE SEASCAPE COASTAL PROXY INDEX

8. Feedback from geomorphological and sedimentology indicators Biological indicators selection and quantification within habitats (both emerged and submerged) Upscaling Land/sea form system pattern Habitat selection: landscape scale definition Downscal i ng Multisensor data collection (Satellite and field survey) Selection of nearshore extent in each area of interest

9. Scientific Hypotesis i) Reflectance signature and biophysical parameters are related to each other via morphology ii) Morphological and SAR data are able to enhance hyperspectral interpretation III) Integration of different methods (Spectral Mixture Analysis, Change Detection and SBAS) to process SAR, hyperspectral and in situ data in two different ecosystems enhance our ability to detect coastal trend

10. Data Sources: CAT1 Proposal C1P.7963 LANDSAT, CHRIS PROBA, ASTER SAR, LiDAR IN SITU (vegetation pattern distribution and morphological parameters)

11. Studysites South Po delta and foce Bevano (Ravenna), Italy Plymouth and Erme saltmarsh, UK Erme saltmarsh Foce Bevano

12. Methodology 1) Change detection NDVI analisystohighlightinter-annualchangeofvegetation 2) Change detection fractionsmapanalisysto integrate inter and intra-annualchange detection mapsofvegetationusing SMA (Small, 2001; Taramelli and Melelli, 2009) 3) Interferometric Low resolution SBAS Approach(Berardinoet al., 2002)to produce deformation and spatiotemporalvariationsmaps and Lidar morphometricanalisys(Taramelliet al., 2010) 4) Fieldvalidation and data integrationfortimeseriesanalisys

13. CHANGE DETECTION ANALYSIS: Po delta and Wetlands of Comacchio valley calculated NDVI Δ image NDVI image data 2001-08-26, path 192 row 29 NDVI (2001) – NDVI (1991) Landsat 7 ETM+ data 2001-08-26 path 192 row 29 No change Loss Gain change detection NDVI from 1991 up to 2010 with a focus on twodecades 1991-2001 and 2001-2010

14. METHODOLOGY SMA Endmemberscollection SpectralMixtureAnalysis classifies individual mixed pixels according to the distribution of spectrally pure end member fractions and provides a tool for discrimination and classification of surface topography. Spectral characteristics of the surface topography show significant differences between the spectral reflectance of different land-form surfaces. A mixing space can be thought of as a coordinate system in which reflectance spectra are represented as linear mixtures of spectrally pure endmember spectra Water Wet Soil Vegetation

15. Pincipal Component Analysis PCA ENDMEMBER COLLECTION

16. Unmixing with three pure endmebers Hyperspectralendmembers fractions map Red: anthropic/sand Green: vegetation Yellow: substrate/soil SpectralMixtureAnalysis (SMA) classifies individual mixed pixels according to the distribution of spectrally pure end member fractions. R: antropic/sand G: vegetation B: substrate/soil

17. In Situ vegetation and morphometric field validation A B N

19. reference pixel is chosen by the operator

21. DataAssimilation NDVI change analysis; mean ground velocity map vegetation fraction change analysis using fraction map.

22. Results Gain (green) No change (white) Loss (red) Statistics within the difference image of the fraction maps and within the difference image of the NDVI Ground in central and upper part moved away from satellite with rates up to 10 cm/y Taramelli A., Valentini E., Dejana M., Zucca F., Mandrone S., 2011, MODELLING COASTAL PROCESSES BY MEANS OF INNOVATIVE INTEGRATION OF REMOTE SENSING TIME SERIES ANALYSIS, IGARSS 2011 International Geosience and Remote Sensing Symposium.

25. Thankyouforyourattention! andrea.taramelli@isprambiente.it