Soil Moisture Retrieval Model Design with Multispectral and Infrared Images from Unmanned Aerial Vehicles Using Convolutional Neural Network

Soil Moisture Retrieval Model Design with Multispectral and Infrared Images from Unmanned Aerial Vehicles Using Convolutional Neural Network

This paper deals with a soil moisture retrieval model design with airborne measurements for remote monitoring of soil moisture level in large crop fields. A small quadrotor unmanned aerial vehicle (UAV) is considered as a remote sensing platform for high spatial resolutions of airborne images and ea...

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Bibliographic Details
Main Authors: Min-Guk Seo, Hyo-Sang Shin, Antonios Tsourdos
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Agronomy
Subjects:
remote sensing
supervied learning
sensor fusion
estimation
Online Access:https://www.mdpi.com/2073-4395/11/2/398

Internet

https://www.mdpi.com/2073-4395/11/2/398

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