AIMC Topic: Soil

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Global soil moisture data derived through machine learning trained with in-situ measurements.

Scientific data Jul 12, 2021
While soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term data...
Environmental Monitoring Humidity Machine Learning Soil
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Machine Learning Strategy for Soil Nutrients Prediction Using Spectroscopic Method.

Sensors (Basel, Switzerland) Jun 19, 2021
The research presented in this paper is based on the hypothesis that the machine learning approach improves the accuracy of soil properties prediction. The correlations obtained in this research are important for understanding the overall strategy fo...
Bayes Theorem Soil Nutrients Support Vector Machine Spectrum Analysis Machine Learning
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Soil Nutrient Estimation and Mapping in Farmland Based on UAV Imaging Spectrometry.

Sensors (Basel, Switzerland) Jun 6, 2021
Soil nutrient is one of the most important properties for improving farmland quality and product. Imaging spectrometry has the potential for rapid acquisition and real-time monitoring of soil characteristics. This study aims to explore the preprocess...
Least-Squares Analysis Soil Nutrients Farms Support Vector Machine
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Mapping soil salinity using a combined spectral and topographical indices with artificial neural network.

PloS one May 13, 2021
Monitoring the status of natural and ecological resources is necessary for conservation and protection. Soil is one of the most important environmental resources in agricultural lands and natural resources. In this research study, we used Landsat 8 a...
Iran Spectrum Analysis Geography Salinity Electric Conductivity Neural Networks, Computer Soil Models, Theoretical
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Predictive modeling of swell-strength of expansive soils using artificial intelligence approaches: ANN, ANFIS and GEP.

Journal of environmental management Apr 5, 2021
This study presents the development of new empirical prediction models to evaluate swell pressure and unconfined compression strength of expansive soils (PUCS-ES) using three soft computing methods, namely artificial neural networks (ANNs), adaptive ...
Soil Gene Expression Neural Networks, Computer Artificial Intelligence
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A model based on Bayesian confirmation and machine learning algorithms to aid archaeological interpretation by integrating incompatible data.

PloS one Mar 31, 2021
The interpretation of archaeological features often requires a combined methodological approach in order to make the most of the material record, particularly from sites where this may be limited. In practice, this requires the consultation of differ...
Archaeology Soil Bayes Theorem Plants Geology Machine Learning Algorithms
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vis-NIR and XRF Data Fusion and Feature Selection to Estimate Potentially Toxic Elements in Soil.

Sensors (Basel, Switzerland) Mar 30, 2021
Soil contamination by potentially toxic elements (PTEs) is intensifying under increasing industrialization. Thus, the ability to efficiently delineate contaminated sites is crucial. Visible-near infrared (vis-NIR: 350-2500 nm) and X-ray fluorescence ...
Soil Support Vector Machine Algorithms
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Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility.

Journal of environmental management Jan 28, 2021
The objective of this study is to assess the gully head-cut erosion susceptibility and identify gully erosion prone areas in the Meimand watershed, Iran. In recent years, this study area has been greatly influenced by several head-cut gullies due to ...
Soil Deep Learning Iran Conservation of Natural Resources Humans Machine Learning
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Comprehensive nutrient analysis in agricultural organic amendments through non-destructive assays using machine learning.

PloS one Dec 10, 2020
Portable X-ray fluorescence (pXRF) and Diffuse Reflectance Fourier Transformed Mid-Infrared (DRIFT-MIR) spectroscopy are rapid and cost-effective analytical tools for material characterization. Here, we provide an assessment of these methods for the ...
Soil Spectroscopy, Fourier Transform Infrared Machine Learning Spectrometry, X-Ray Emission Nutrients Organic Agriculture Fertilizers
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Degradation of poly(butylene adipate-co-terephthalate) by Stenotrophomonas sp. YCJ1 isolated from farmland soil.

Journal of environmental sciences (China) Oct 28, 2020
In recent years, poly (butylene adipate-co-terephthalate) (PBAT) has been widely used. However, PBAT-degrading bacteria have rarely been reported. PBAT-degrading bacteria were isolated from farmland soil and identified. The effects of growth factors ...
Adipates Farms Polyesters Alkenes Phthalic Acids Stenotrophomonas Soil
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