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Estimation of Soil Moisture at Different Soil Levels Using Machine Learning Techniques and Unmanned Aerial Vehicle (UAV) Multispectral Imagery

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Title Estimation of Soil Moisture at Different Soil Levels Using Machine Learning Techniques and Unmanned Aerial Vehicle (UAV) Multispectral Imagery
Creator Aboutalebi, Mahyar Allen, L. Niel Torres-Rua, Alfonso F. McKee, Mac Coopmans, Calvin
Description Soil moisture is a key component of water balance models. Physically, it is a nonlinear function of parameters that are not easily measured spatially, such as soil texture and soil type. Thus, several studies have been conducted on the estimation of soil moisture using remotely sensed data and data mining techniques such as artificial neural networks (ANNs) and support vector machines (SVMs). However, all models developed based on these techniques are limited to site-specific applications...
Date 2019-05-14T07:00:00Z
Type text
Format application/pdf
Identifier https://digitalcommons.usu.edu/aggieair_pubs/27 info:doi/10.1117/12.2519743 https://digitalcommons.usu.edu/context/aggieair_pubs/article/1028/viewcontent/AGAIRcenter2019AboutalebiAllenTorres_Rua_EstimationSoilMoisture.pdf
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Source AggieAir Publications
Publisher Hosted by Utah State University Libraries
Contributor International Society for Optical Engineering
Subject Soil science Unmanned aerial vehicles Machine learning Computer programming Data modeling Multispectral imaging Aviation

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