Review of soil salinity assessment for agriculture across multiple scales using proximal and/or remote sensors

DL Corwin, E Scudiero - Advances in agronomy, 2019 - Elsevier
Map** and monitoring soil spatial variability is particularly problematic for temporally and
spatially dynamic properties such as soil salinity. The tools necessary to address this classic …

A higher prediction accuracy–based alpha–beta filter algorithm using the feedforward artificial neural network

J Khan, E Lee, K Kim - CAAI Transactions on Intelligence …, 2023 - Wiley Online Library
The alpha–beta filter algorithm has been widely researched for various applications, for
example, navigation and target tracking systems. To improve the dynamic performance of …

Satellite data integration for soil clay content modelling at a national scale

T Loiseau, S Chen, VL Mulder, MR Dobarco… - International Journal of …, 2019 - Elsevier
Soil clay content is a key parameter that influences many other soil properties and
processes. The potential of adding new and contemporary satellite data for soil property …

Large-scale soil map** using multi-configuration EMI and supervised image classification

C Brogi, JA Huisman, S Pätzold, C Von Hebel… - Geoderma, 2019 - Elsevier
Reliable and high-resolution subsurface characterization beyond the field scale is of great
interest for precision agriculture and agro-ecological modelling because the shallow soil …

EMagPy: Open-source standalone software for processing, forward modeling and inversion of electromagnetic induction data

P McLachlan, G Blanchy, A Binley - Computers & Geosciences, 2021 - Elsevier
Frequency domain electromagnetic induction (EMI) methods have had a long history of
qualitative map** for environmental applications. More recently, the development of multi …

Characterization of field-scale soil variation using a stepwise multi-sensor fusion approach and a cost-benefit analysis

S Chatterjee, AE Hartemink, J Triantafilis, AR Desai… - Catena, 2021 - Elsevier
The potential of a stepwise fusion of proximally sensed portable X-ray fluorescence (pXRF)
spectra and electromagnetic induction (EMI) with remote Sentinel-2 bands and a digital …

Improving accuracy of the Kalman filter algorithm in dynamic conditions using ANN-based learning module

I Ullah, M Fayaz, DH Kim - Symmetry, 2019 - mdpi.com
Prediction algorithms enable computers to learn from historical data in order to make
accurate decisions about an uncertain future to maximize expected benefit or avoid potential …

Repeated electromagnetic induction measurements for map** soil moisture at the field scale: Validation with data from a wireless soil moisture monitoring network

E Martini, U Werban, S Zacharias… - Hydrology and Earth …, 2017 - hess.copernicus.org
Electromagnetic induction (EMI) measurements are widely used for soil map**, as they
allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa) …

An improved alpha beta filter using a deep extreme learning machine

J Khan, M Fayaz, A Hussain, S Khalid… - IEEE …, 2021 - ieeexplore.ieee.org
This paper introduces new learning to the prediction model to enhance the prediction
algorithms' performance in dynamic circumstances. We have proposed a novel technique …

Using apparent electrical conductivity as indicator for investigating potential spatial variation of soil salinity across seven oases along Tarim River in Southern **njiang …

J Ding, S Yang, Q Shi, Y Wei, F Wang - Remote Sensing, 2020 - mdpi.com
Soil salinization is a major soil health issue globally. Over the past 40 years, extreme
weather and increasing human activity have profoundly changed the spatial distribution of …