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Summary of Proposal HYD0538

TitleHYDRO-TERRA. The retrieval and monitoring of Land Hydrological parameters for Risk and Water Resources Management
Investigator Pampaloni, Paolo - CNR-IFAC, Earth Observation
Team Member
Dr Paloscia, Simonetta - Institute of Applied Physiscs - IFAC-CNR, Earth Observ
Dr Santi, Emanuele - Institute of Applied Physiscs - IFAC-CNR, Earth Observ.
Dr. Pettinato, Simone - Institute of Applied Physiscs - IFAC-CNR, Earth Observ.
Dr Brogioni, Marco - Institute of Applied Physiscs - IFAC-CNR, Earth Observ.
SummaryThe objective of the research is the development and validation of advanced algorithms for the retrieval of land hydrological parameters (namely: soil moisture and surface roughness, vegetation cover and biomass of forests and crops, snow cover area and wetness) from X band Cosmo-Skymed data. Synergy with L-band data from ALOS and, when available, from SAOCOM will also be evaluated. The methodology will include: - Preliminary analysis of experimental relationships between X band data, taken in previous experiments (X-SAR and E-SAR), and land physical parameters - Implementation of wideband electromagnetic models for simulating X-band (and L-band) backscattering from bare soils, and soil covered by crops, forests and snow. Surface scattering from soil will be simulated by developing a polarimetric version of the Advanced Integral Equation Model (AIEM). Volume scattering from vegetation (crops and forests) and snow will be simulated respectively by using the conventional Radiative Transfer Theory and the coherent Dense Media Radiative Transfer. Combination of models (soil covered by vegetation or snow and by vegetation and snow) will be performed with appropriate approaches. - Validation of models with TerraSAR-X(and L-band) data taken on the selected test areas together with ground truth measurements. The latter will include all the conventional measurements concerning soil, vegetation and snow properties (parameters). - Development and implementation of inversion algorithms for the retrieval of the mentioned geophysical parameters. Different approaches will be evaluated based on statistical and iteration approaches to invert the e.m. models. Particular attention will be paid to neural networks, trained both with simulated and experimental data. - The analysis of the signal phase and coherence between images taken at different times to investigate the correlation of these quantities to snow water equivalent and vegetation biomass - Validation of retrieval algorithms with experimental data taken on the selected test areas - A few demonstration exercises to validate the developed approaches in practical hydrological and risk management applications. These will include: monitoring of the evolution of snow cover extent and the detection of snow melting and snow water equivalent in alpine areas for evaluating the risk of avalanches, estimating of wood biomass and detection of fired areas in forests, monitoring the evolution of soil moisture for estimating the risk of floods as well as and the extension of flooded areas The estiamted quantity of data requested to perform the research include 5 images (stripmap) of the Scrivia watershed, 5 images (stripmap) of Cordevole Waterhed and 1 Spotlight Mode (SL)on the site Montespertoli The deliverables of the projects will be: - a mid term report containing the validated electromagnetic models and the collected experimental data (backscattering and ground truth) - a final report containing the implemented validated retrieval algorithms and the results of the demonstration exercises

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DLR 2004-2016