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Effects of different spectral processing methods on soil organic matter prediction based on VNIR-SWIR spectroscopy in karst areas, Southwest China
PurposeSoil organic matter (SOM) is an important indicator of soil fertility in karst area. A more effective alternative to conventional soil...
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Conversion of carbonaceous materials into solid acids for tylosin mitigation: effect of preprocessing methods on the reactivity of sulfonation reaction
Carbon-based solid acids have been successfully employed as acidic catalysts for pollutant mitigation in wastewater. To fully tap the potentials of...
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A coastal band spectral combination for water body extraction using Landsat 8 images
The explosive rate of population growth demands a revision of existing protective measures to address water scarcity that urges water body monitoring...
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Investigating heavy-metal soil contamination state on the rate of stomach cancer using remote sensing spectral features
Heavy metal (HM) contamination in agricultural soils has been a serious environmental and health problem in the past decades. High concentration of...
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A critical systematic review on spectral-based soil nutrient prediction using machine learning
The United Nations (UN) emphasizes the pivotal role of sustainable agriculture in addressing persistent starvation and working towards zero hunger by...
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Use of a UAV for statistical-spectral analysis of vegetation indices in sugarcane plants in the Eastern Amazon
The use of unmanned aerial vehicles is increasingly present in agricultural activities, representing an important innovation tool, being...
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Estimation of heavy metal concentrations (Cd and Pb) in plant leaves using optimal spectral indicators and artificial neural networks
The necessity of continuously monitoring the agricultural products in terms of their health has enforced the development of rapid, low-cost, and...
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Estimation of multi-media metal(loid)s around abandoned mineral processing plants using hyperspectral technology and extreme learning machine
Hyperspectral techniques are promising alternatives to traditional methods of investigating potentially toxic metal(loid) contamination. In this...
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Prediction of heavy metals in polluted mangrove soils in Brazil with the highest reported levels of mercury using near-infrared spectroscopy
Infrared reflectance spectroscopy has demonstrated potential as a tool for monitoring and preventing contamination in different environments. The...
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Basic research for identification and classification of organophosphorus pesticides in water based on ultraviolet–visible spectroscopy information
In this study, the goal was to develop a method for detecting and classifying organophosphorus pesticides (OPPs) in bodies of water. Sixty-five...
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Estimation of metal elements content in soil using x-ray fluorescence based on multilayer perceptron
X-ray fluorescence (XRF) is widely used to rapidly detect heavy metals in soil. Spectra processing has been an important research topic to improve...
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A novel method for multi-pollutant monitoring in water supply systems using chemical machine vision
Drinking water is vital for human health and life, but detecting multiple contaminants in it is challenging. Traditional testing methods are both...
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MSTL-NNAR: a new hybrid model of machine learning and time series decomposition for wind speed forecasting
Wind speed forecasting is essential for various domains, such as renewable energy generation, aviation, agriculture, and disaster management....
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UAV hyperspectral remote sensor images for mango plant disease and pest identification using MD-FCM and XCS-RBFNN
To diminish disease transmission together with promoting effective management techniques, it is crucial to monitor plant health and detect pathogens...
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Application of fractional-order differential and ensemble learning to predict soil organic matter from hyperspectra
PurposeAccurate estimation of soil organic matter (SOM) content is crucial for agricultural production. The integral-order differential hyperspectral...
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Benthic Habitats
Shallow-water coastal benthic habitats, which can comprise seagrasses, sandy soft bottoms, and coral reefs are essential ecosystems, supporting...
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Evaluation of preprocessing techniques for improving the accuracy of stochastic rainfall forecast models
Accurate rainfall forecasting is one of the most important and challenging hydrological modeling tasks with significant benefits for many sectors of...
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Evaluation of data pre-processing and regression models for precise estimation of soil organic carbon using Vis–NIR spectroscopy
PurposeRapid and accurate estimation of soil organic carbon (SOC) based on near-infrared spectroscopy can assist sustainable agricultural...
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Monitoring pollution pathways in river water by predictive path modelling using untargeted GC-MS measurements
To safeguard the quality of river water, a comprehensive approach is required within the European Water Framework Directive. It is vital to conduct...
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The application of laser‑induced fluorescence in oil spill detection
Over the past two decades, oil spills have been one of the most serious ecological disasters, causing massive damage to the aquatic and terrestrial...
