Airborne Radiometric Surveys and Machine Learning Algorithms for Revealing Soil Texture
Soil texture is key information in agriculture for improving soil knowledge and crop performance, so the accurate mapping of this crucial feature is imperative for rationally planning cultivations and for targeting interventions. We studied the relationship between radioelements and soil texture in...
Main Authors: | Andrea Maino, Matteo Alberi, Emiliano Anceschi, Enrico Chiarelli, Luca Cicala, Tommaso Colonna, Mario De Cesare, Enrico Guastaldi, Nicola Lopane, Fabio Mantovani, Maurizio Marcialis, Nicola Martini, Michele Montuschi, Silvia Piccioli, Kassandra Giulia Cristina Raptis, Antonio Russo, Filippo Semenza, Virginia Strati |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-08-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/14/15/3814 |
Similar Items
-
Accuracy of Flight Altitude Measured with Low-Cost GNSS, Radar and Barometer Sensors: Implications for Airborne Radiometric Surveys
by: Matteo Albéri, et al.
Published: (2017-08-01) -
External effective dose from natural radiation for the Umbria region (Italy)
by: Kassandra Giulia Cristina Raptis, et al.
Published: (2022-07-01) -
Proximal Gamma-Ray Spectroscopy: An Effective Tool to Discern Rain from Irrigation
by: Andrea Serafini, et al.
Published: (2021-10-01) -
Thorium Removal, Recovery and Recycling: A Membrane Challenge for Urban Mining
by: Geani Teodor Man, et al.
Published: (2023-08-01) -
Combining Precision Viticulture Technologies and Economic Indices to Sustainable Water Use Management
by: Adele Finco, et al.
Published: (2022-05-01)