The course aims at providing a complete picture about the possibility to map soil moisture and inundation at high resolution using Synthetic Aperture Radar (SAR). An introduction to the SAR technique is firstly given to understand the measured quantities, the main image quality parameters and radiometric and geometric fidelity one can obtain from space. The forward models and physical principles needed to interpret the data are briefly illustrated. The satellite missions presently available and planned in the near future are presented. Then the course illustrates several methods to generate soil moisture and flood extension maps, including approaches aiming to fulfill operational requirements, such as those specified in the frame of the Copernicus service. Examples of what is done in the frame of civil protection activities by dedicated research centers are also illustrated.
Prerequisiti
Basic knowledge about physics (electromagnetic waves), remote sensing sensors (passive and active sensors) and data (digital numbers, processing levels).
Metodi didattici
Lectures and interactive discussion.
Verifica Apprendimento
A list of questions covering the topics of the course will be proposed at the end of the week. They will include multiple choices questions as well as simple numerical exercises.
Testi
The slides used by the teacher will be provided, together with a list of relevant books and literature papers.
Contenuti
Introduction. Synthetic Aperture Radar principles Main characteristics of a SAR image: speckle, calibration, polarization, geometric and radiometric distortions Radar observables: backscattering coefficient, phase, coherence and the radar equation Dielectric constant of terrain. Penetration depth. Introduction to surface and volume scattering Scattering from rough soil. Physical Optics, Geometric Optics and Small Perturbation Models Volume scattering from vegetation. The Water Cloud Model. Double Bounce Mechanisms and polarization Bayesian inversion of forward model: single acquisition and multitemporal Soil moisture from microwave radiometry, scatterometer, GNSS-R and possible sinergy SAR based missions: Sentinel-1, Saocom, Alos. future missions: Nisar, ROSE-L SAR-based flood mapping principles SAR-based flood mapping over bare soils or scarcely vegetated areas SAR-based flood mapping over vegetated areas SAR-based flood mapping over urban areas Sources of errors in SAR-based automatic flood mapping algorithms Identification of regions where SAR sensors are “blind” to detect floodwater Automatic large-Scale Flood Maps Record derived from SAR data Automatic and systematic SAR-based floodwater mapping system based on cloud computing platform Probabilistic flood mapping using SAR data SAR-based deep learning approaches to map floodwater Main characteristics of Sentinel-1 products (revisit time, spatial resolution, advantages over other sensors) Availability of Sentinel data (Sentinel Hub, DIAS) Preprocessing of Sentinel-1 data using the SNAP tool Application of a simple thresholding method to detect flooded areas: implementation using SNAP and visualization using QGIS Operational flood mapping using Sentinel-1: on-demand procedures. The Copernicus Emergency Service Operational flood mapping using Sentinel-1: an example of an automatic algorithm. General information on multispectral data Main characteristics of Sentinel-2 products and flood mapping using Sentinel-2. Operational soil moisture monitoring using Sentinel-1.
