Monday, 08 May 2023 11:14

IEEE-GRS29-Italy’s 2022 Best Remote Sensing Award to Davide Palmisano for his PhD Thesis carried out at IREA

IMG 20230302 174218bThe ceremony of Italy’s Best Remote Sensing Award (IEEE-GRS29) was held in March 2023. The competition, jointly organized again this year by the IEEE Geoscience Remote Sensing Central-North Italy (GRS29-CNI) and South Italy (GRS29-SI) Chapters, saw the awarding of the three best PhD theses and the three best M.Sc. theses on topics of Geoscience and Remote Sensing, defended from 1st of June, 2021 to 31st of May, 2022. Among this year’s candidates, Davide Palmisano has been the winner of the PhD thesis “Time series analysis of synthetic aperture radar data for surface soil moisture retrieval at high resolution” carried out at CNR-IREA and defended at Sapienza University of Rome in February 2022.

The thesis has investigated the use of dense time series of synthetic aperture radar (SAR) data for retrieving SSM at high spatial and temporal resolution. The topic is of great scientific and application interest because it bears on understanding the hydrological cycle and improving land applications, such as numerical weather prediction (NWP), flood forecasting, and drought monitoring and prediction.

The Thesis has focused on three thematic insights. The first one has concerned with the retrieval of Surface Soil Moisture (SSM) over agricultural soils using SAR data from the European mission Sentinel-1, acquired at incidence angles higher than 40 degrees. Indeed, the incidence angle is a crucial parameter modulating the SAR data sensitivity to SSM. Davide’s activity has consisted of quantifying the SSM retrieval accuracy as a function of the incidence angle and the agricultural crop. The sensitivity analysis to SSM has been further investigated in the project “SARSense”, funded by the European Space Agency (ESA), organized in view of the future ROSE-L mission. In particular, Davide has been participating in the data collection during the campaign on the Selhausen site (Germany) and has contributed to the data analysis.

A second important focus of the thesis has been on developing a mathematical scheme for SSM retrieval that combines the information content of temporal changes of the SAR interferometric phase and intensity. The underlying motivation is the new availability of dense time series of SAR data that makes timely the integration of incoherent and coherent change detection approaches for surface parameter retrieval.

A third pillar of the thesis concerns the experimental assessment of SAR SSM through in situ measurements. Worldwide, there exist several hydrologic networks, continuously recording in situ SSM, which are used to test the accuracy of retrieved SSM from satellite data. In the near future, various SAR SSM products will likely be available on a large scale on a continuous temporal basis. Davide has investigated aspects related to the development of validation protocols tailored to high spatial resolution SSM products.

Currently, Davide is an assistant researcher at the IREA’s Bari office, where he pursues his research on the retrieval of land biophysical parameters from earth observation data.


 SSM map at ~100 m resolution over Castilla y León, Spain, on 17th of June, 2021. SSM was retrieved using the SMOSAR code (Soil MOisture retrieval from multi-temporal SAR data) developed at CNR-IREA. Left panel: zoom of the SSM map over an agricultural area (parcel borders are in black). Right panel: SSM over the entire area. Higher SSM due to precipitations is in blue. In the inset, the Castilla y León region is reported in red.


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