1. Spatial and Temporal Mapping of Soil Moisture Content with Polarimetric RADARSAT2 SAR Imagery in the Alpine Area Luca Pasolli1,2 Claudia Notarnicola2 Lorenzo Bruzzone1 Giacomo Bertoldi3 Georg Niedriest3 Ulrike Tappeiner3 Marc Zebisch2 Fabio Del Frate4 Gaia Vaglio Laurin4 E-mail: luca.pasolli@disi.unitn.it luca.pasolli@eurac.edu Web: http://rslab.disi.unitn.it http://www.eurac.edu

2. 2 Outline Introduction 1 Aim of the Work 2 Study Area and Dataset 3 Estimation System Description 4 Analysis of Results 5 Conclusion 6 IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

5. Mountain landscape (Alpine area)

7. Estimation of vegetation biomass (forest)

8. Investigation on the influence of soil and vegetation parameters in connection to natural hazard in Alpine regions.

9. Estimation of soil moisture content on bare and vegetated areas (alpine meadows and pastures) IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

11. flood and landslide prediction

13. sensitivityof microwave signals on different target properties (moisture content, roughness, vegetation, land use)

15. by exploiting an advanced retrieval algorithm based on the Support Vector Regression (SVR) methodL. Pasolli, C. Notarnicola, L. Bruzzone, G. Bertoldi, S. Della Chiesa, V. Hell, G. Niedrist, U. Tappeiner, M. Zebisch, F. Del Frate, G.V. Laurin, “EstimagionofSoilMoisture in an Alpine catchmentwith RADARSAT2 images”, Applied and EnvironmentalSoil Science, in press IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

16. 5 Aimof the Work ToFurther Investigate the RetrievalofSoilMoisture from RADARSAT2 SAR Images in Alpine Areas Byexploiting the fully-polarimetriccapabilityof RADARSAT2 in combinationwith standard and advancedfeatureextraction/selectionmethods Byextending the analysisin time and spacewith the availableimages IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

18. Land use

19. Soil moisture content conditionsIEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

21. DEM geocoded, filtered (Frost 7x7)

23. NDVI map extracted from MODIS Terra images (pixel size 250 m)

24. Land use map (meadows, pasture);IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

25. Estimation System 8 Polarimetric RADARSAT2 SAR image Data Pre-processing Feature Extraction & Selection Ancillary Data RetrievalAlgorithm EstimatedSoilMoistureContentMap IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

27. Multi-objective Model Selection ApproachPolarimetric RADARSAT2 SAR image Featuresfrom RemotelySensedImage Featuresfrom Ancillary Data Ground Truth ReferenceSamples Training Phase Data Pre-processing Validation Set Training Set K-Fold Cross Validation Performance Evaluation SVR Learning SVR Estimation Feature Extraction & Selection SVR ParametersConfig. Sub-Sample Generator Ancillary Data ModelSelection Multi-ObjectiveModelSelection RetrievalAlgorithm EstimationPerform. (MSE, R2) Estimation Operational Phase SVR Estimator Input Features (Image + Ancillary) Output SMC Value EstimatedSoilMoistureContentMap IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

29. Polarimetric backscattering coefficients

30. Polarimetric Combinations: Span (HH+HV+2HV), Polarization Ratio (HH/VV) and Linear Depolarization Ratio (HV/VV)

31. Polarimetric phase difference (PPD) and interferometric coherence

32. Polarimetric Decompositions

33. H/A/αdecomposition

34. Generalpurposefeatureextractiontechniques

37. RetrievalAlgorithmSettings:

38. SVR withGaussian RBF kernelfunction

39. Hyper-parametersranges: 10-3 < γ < 103 , 10-3< C < 103 , 10-3 < ε < 10

40. Multi-objectives model selection according to RMSE and R2 quality metrics

41. Performance assessment on 17 independent test reference samples according to:

42. Root Mean Squared Error (RMSE)

43. Determination coefficient (R2)

45. Generation ofsoilmoisturecontentmapsassociatedwith RADARSAT 2 SAR imagestimeseriesacquiredduringsummer 2010

46. Qualitative and quantitative assessmentwithpriorknowledge on the area and field station measurementsIEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

47. 11 Results: Experiment 1 HH feature HH HV/VV features ICA1 ICA4 features α Afeatures IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

48. 11 Results: Experiment 2 EstimatedSoilMoistureContentMap, June 2010 IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

49. 14 Results: Experiment 2 Estimated dielectric constant Map, October 2010 Estimated dielectric constant Map, August 2010 Estimated dielectric constant map, July 2010 Estimated Dielectric constant Map, June 2010 IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

53. Integration of data from different sensors (e.g., L-Band SAR images)IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011

54. 16 Thankyoufor the Attention!! Questions? luca.pasolli@disi.unitn.it luca.pasolli@eurac.edu IEEE International Geoscience and Remote Sensing Symposium IGARSS 2011 Vancouver, Canada – 24-29 July, 2011