A review of machine learning in geochemistry and cosmochemistry: Method improvements and applications
The development of analytical and computational techniques and growing scientific funds
collectively contribute to the rapid accumulation of geoscience data. The massive amount of …
collectively contribute to the rapid accumulation of geoscience data. The massive amount of …
[HTML][HTML] Root zone soil moisture estimation with Random Forest
Accurate estimates of root zone soil moisture (RZSM) at relevant spatio-temporal scales are
essential for many agricultural and hydrological applications. Applications of machine …
essential for many agricultural and hydrological applications. Applications of machine …
Soil moisture estimation using novel bio-inspired soft computing approaches
R Moazenzadeh, B Mohammadi… - … of Computational Fluid …, 2022 - Taylor & Francis
Soil moisture (SM) is of paramount importance in irrigation scheduling, infiltration, runoff,
and agricultural drought monitoring. This work aimed at evaluating the performance of the …
and agricultural drought monitoring. This work aimed at evaluating the performance of the …
Spatiotemporal modelling of soil moisture in an A tlantic forest through machine learning algorithms
VA de Oliveira, AF Rodrigues… - european Journal of …, 2021 - Wiley Online Library
Understanding the spatiotemporal behaviour of soil moisture in tropical forests is
fundamental because it mediates processes such as infiltration, groundwater recharge …
fundamental because it mediates processes such as infiltration, groundwater recharge …
Downscaling satellite soil moisture using geomorphometry and machine learning
Annual soil moisture estimates are useful to characterize trends in the climate system, in the
capacity of soils to retain water and for predicting land and atmosphere interactions. The …
capacity of soils to retain water and for predicting land and atmosphere interactions. The …
Machine learning approach to estimate soil matric potential in the plant root zone based on remote sensing data
RF Maia, CB Lurbe, J Hornbuckle - Frontiers in Plant Science, 2022 - frontiersin.org
There is an increasing interest in using the Internet of Things (IoT) in the agriculture sector to
acquire soil-and crop-related parameters that provide helpful information to manage farms …
acquire soil-and crop-related parameters that provide helpful information to manage farms …
A technical overview of the North Carolina ECONet
SM Saia, SP Heuser, MD Neill… - … of Atmospheric and …, 2023 - journals.ametsoc.org
Regional weather networks—also referred to as mesonets—are imperative for filling in the
spatial and temporal data gaps between nationally supported weather stations. The North …
spatial and temporal data gaps between nationally supported weather stations. The North …
Towards new soil water flow equations using physics‐constrained machine learning
Abstract The Richardson–Richards equation (RRE) is a widely used partial differential
equation (PDE) for modeling moisture dynamics in unsaturated soil. However, field soil …
equation (PDE) for modeling moisture dynamics in unsaturated soil. However, field soil …
A low-power IoT device for measuring water table levels and soil moisture to ease increased crop yields
The simultaneous measurement of soil water content and water table levels is of great
agronomic and hydrological interest. Not only does soil moisture represent the water …
agronomic and hydrological interest. Not only does soil moisture represent the water …
Digital mapping of soil landscape parameters
Model performance depends on the variables used to represent soil–landscape
relationships. Therefore variable selection is an important aspect of digital mapping …
relationships. Therefore variable selection is an important aspect of digital mapping …