This special section focuses on the use of remote sensing tools in some of these areas, including monitoring the volume and turbidity in lake fresh water resources, retrieving soil organic matter from spectral information with particular attention to abandoned croplands and areas affected by wildfires, and identification and monitoring of natural and agricultural vegetation through emerging techniques such as shallow and deep learning algorithms. These data mining and analysis approaches are particularly promising and include convolutional neural network and the application of back propagation neural network algorithms for soil water content monitoring and the extraction of other canopy information.

Maltese, A., Neale, C.M.U. (2018). Special Section Guest Editorial: Advances in Agro-Hydrological Remote Sensing for Water Resources Conservation [10.1117/1.JRS.12.042801].

Special Section Guest Editorial: Advances in Agro-Hydrological Remote Sensing for Water Resources Conservation

Maltese, Antonino
;
2018-01-01

Abstract

This special section focuses on the use of remote sensing tools in some of these areas, including monitoring the volume and turbidity in lake fresh water resources, retrieving soil organic matter from spectral information with particular attention to abandoned croplands and areas affected by wildfires, and identification and monitoring of natural and agricultural vegetation through emerging techniques such as shallow and deep learning algorithms. These data mining and analysis approaches are particularly promising and include convolutional neural network and the application of back propagation neural network algorithms for soil water content monitoring and the extraction of other canopy information.
2018
Earth and Planetary Sciences (all)
Maltese, A., Neale, C.M.U. (2018). Special Section Guest Editorial: Advances in Agro-Hydrological Remote Sensing for Water Resources Conservation [10.1117/1.JRS.12.042801].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/355482
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