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Soil

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Terrain Characterization via Machine vs. Deep Learning Using Remote Sensing.

Sensors (Basel, Switzerland)
Terrain traversability is critical for developing Go/No-Go maps for ground vehicles, which significantly impact a mission's success. To predict the mobility of terrain, one must understand the soil characteristics. In-situ measurements performed in t...

Soil carbon content prediction using multi-source data feature fusion of deep learning based on spectral and hyperspectral images.

Chemosphere
Visible near-infrared reflectance spectroscopy (VNIR) and hyperspectral images (HSI) have their respective advantages in soil carbon content prediction, and the effective fusion of VNIR and HSI is of great significance for improving the prediction ac...

Fuzzy-based models' performance on qualitative and quantitative land suitability evaluation for cotton cultivation in Sarayan County, South Khorasan Province, Iran.

Environmental monitoring and assessment
Using appropriate models in the land use planning process will help increase the accuracy and precision of decisions made by designers. The aim of this study was to investigate and compare fuzzy-based models (fuzzy set theory, fuzzy-AHP, and fuzzy-AN...

Combining Deep Learning and Hydrological Analysis for Identifying Check Dam Systems from Remote Sensing Images and DEMs in the Yellow River Basin.

International journal of environmental research and public health
Identifying and extracting check dams is of great significance for soil and water conservation, agricultural management, and ecological assessment. In the Yellow River Basin, the check dam, as a system, generally comprises dam locations and dam-contr...

Prediction of Soil Water-Soluble Organic Matter by Continuous Use of Corn Biochar Using Three-Dimensional Fluorescence Spectra and Deep Learning.

Computational intelligence and neuroscience
The purpose is to study the soil's water-soluble organic matter and improve the utilization rate of the soil layer. This exploration is based on the theories of three-dimensional fluorescence spectroscopy, deep learning, and biochar. Chernozem in Har...

Comparison of machine learning and deep learning models for evaluating suitable areas for premium teas in Yunnan, China.

PloS one
BACKGROUND: Tea is an important economic crop in Yunnan, and the market price of premium teas such as Lao Banzhang is significantly higher than ordinary teas. For planting lands to promote, the tea industry to develop and minority lands' economies to...

As good as human experts in detecting plant roots in minirhizotron images but efficient and reproducible: the convolutional neural network "RootDetector".

Scientific reports
Plant roots influence many ecological and biogeochemical processes, such as carbon, water and nutrient cycling. Because of difficult accessibility, knowledge on plant root growth dynamics in field conditions, however, is fragmentary at best. Minirhiz...

Design of a special rigid wheel for traversing loose soil.

Scientific reports
Wheels play an important role in mobile robotics, wheelchairs and vehicles and represent an ideal solution for traversing rigid ground due to higher efficiency. Through traversing loose soil, the rigid wheels lose traction because of sinking and high...

Statistical evaluation of testing conditions on the saturated hydraulic conductivity of Brazilian lateritic soils using artificial intelligence approaches.

Scientific reports
The saturated hydraulic conductivity, k, is a crucial variable to describe the hydromechanical behavior of soils. The value of k of lateritic soils that are typically found in tropical regions is highly affected by the soil's structure, void ratio, a...

A Machine Learning Architecture Replacing Heavy Instrumented Laboratory Tests: In Application to the Pullout Capacity of Geosynthetic Reinforced Soils.

Sensors (Basel, Switzerland)
For economical and sustainable benefits, conventional retaining walls are being replaced by geosynthetic reinforced soil (GRS). However, for safety and quality assurance purposes, prior tests of pullout capacities of these materials need to be perfor...