An algorithm based on neural networks for generating multi-temporal soil moisture maps from ENVISAT/ASAR images

Paolo Pampaloni; Simonetta Paloscia; Simone Pettinato; Emanuele Santi

doi:10.1117/12.693054

9 October 2006 An algorithm based on neural networks for generating multi-temporal soil moisture maps from ENVISAT/ASAR images

Paolo Pampaloni, Simonetta Paloscia, Simone Pettinato, Emanuele Santi

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Proceedings Volume 6363, SAR Image Analysis, Modeling, and Techniques VIII; 636306 (2006) https://doi.org/10.1117/12.693054
Event: SPIE Remote Sensing, 2006, Stockholm, Sweden

Abstract

In this paper the actual capabilities of ENVISAT/ASAR images in providing soil moisture maps have been tested. Several SAR images were collected on two test areas: a flat agricultural region in the Alessandria area, in Italy, and the natural area of Kemijoki river system, in Finland. An inversion algorithm based on Artificial Neural Networks (ANN) for the retrieval 4-5 levels of soil moisture from backscattering data was tested and successfully compared to ground measurements.

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Paolo Pampaloni, Simonetta Paloscia, Simone Pettinato, and Emanuele Santi "An algorithm based on neural networks for generating multi-temporal soil moisture maps from ENVISAT/ASAR images", Proc. SPIE 6363, SAR Image Analysis, Modeling, and Techniques VIII, 636306 (9 October 2006); https://doi.org/10.1117/12.693054

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KEYWORDS

Soil science

Backscatter

Agriculture

Evolutionary algorithms

Synthetic aperture radar

Data modeling

Neurons

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