In the framework of a project funded by the Italian Space Agency (Algoritmi-METEMW), experimental activities based on airborne multi-frequency microwave radiometric measurements and simultaneous ground-truth data collection have been carried out in Central Italy, in an agricultural area close to Florence. The aim of the project was the development of innovative algorithms for the estimate of hydrological parameters integrating active and passive microwave data. The retrieval algorithms are based on Artificial Neural Networks (ANN). IFAC multi-frequency microwave radiometers (at L, C, and X bands) have been installed on ultralight helicopters, which overflew the area in concomitance with SMAP and Sentinel-1 (S-1) image acquisitions. Comparisons of new data with past results confirmed the already stated relationships between microwave indices and soil and vegetation parameters. Soil moisture content (SMC) values estimated from L-band radiometric data are very close to those retrieved using the ANN algorithm. This result confirms the possibility of validating satellite algorithms with airborne microwave radiometers.

Airborne multi-frequency microwave radiometric measurements in synergy with SAR data for the retrieval of soil moisture

Pilia S;Baroni F;Fontanelli G;Lapini A;Paloscia S;Pampaloni P;Pettinato S;Santi E;Santurri L;Cigna F
2020

Abstract

In the framework of a project funded by the Italian Space Agency (Algoritmi-METEMW), experimental activities based on airborne multi-frequency microwave radiometric measurements and simultaneous ground-truth data collection have been carried out in Central Italy, in an agricultural area close to Florence. The aim of the project was the development of innovative algorithms for the estimate of hydrological parameters integrating active and passive microwave data. The retrieval algorithms are based on Artificial Neural Networks (ANN). IFAC multi-frequency microwave radiometers (at L, C, and X bands) have been installed on ultralight helicopters, which overflew the area in concomitance with SMAP and Sentinel-1 (S-1) image acquisitions. Comparisons of new data with past results confirmed the already stated relationships between microwave indices and soil and vegetation parameters. Soil moisture content (SMC) values estimated from L-band radiometric data are very close to those retrieved using the ANN algorithm. This result confirms the possibility of validating satellite algorithms with airborne microwave radiometers.
2020
9781728170930
Artificial neural network (ANN)
Microwave radiometers
SAR
Soil moisture content
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/419881
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