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Environmental Monitoring

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Utilizing machine learning to evaluate heavy metal pollution in the world's largest mangrove forest.

The Science of the total environment
The world's largest mangrove forest (Sundarbans) is facing an imminent threat from heavy metal pollution, posing grave ecological and human health risks. Developing an accurate predictive model for heavy metal content in this area has been challengin...

A new attention-based CNN_GRU model for spatial-temporal PM prediction.

Environmental science and pollution research international
Accurately predicting the spatial-temporal distribution of PM is challenging due to missing data and selecting an appropriate modeling method. Effective imputation of missing data must consider the relationships between variables while preserving the...

Artificial Neural Network and Remote Sensing combined to predict the Aboveground Biomass in the Cerrado biome.

Anais da Academia Brasileira de Ciencias
Cerrado is the second largest biome in Brazil, and it is responsible for providing us several ecosystem services, including the functions of storing Carbon and biodiversity conservation. In this study, we developed a modeling approach to predict the ...

Real-time chlorophyll-a forecasting using machine learning framework with dimension reduction and hyperspectral data.

Environmental research
Since water is an essential resource in various fields, it requires constant monitoring. Chlorophyll-a concentration is a crucial indicator of water quality and can be used to monitor water quality. In this study, we developed methods to forecast chl...

Assessing spirlin Alburnoides bipunctatus (Bloch, 1782) as an early indicator of climate change and anthropogenic stressors using ecological modeling and machine learning.

The Science of the total environment
Combining single-species ecological modeling with advanced machine learning to investigate the long-term population dynamics of the rheophilic fish spirlin offers a powerful approach to understanding environmental changes and climate shifts in aquati...

Integrating automated machine learning and metabolic reprogramming for the identification of microplastic in soil: A case study on soybean.

Journal of hazardous materials
The accumulation of polyethylene microplastic (PE-MPs) in soil can significantly impact plant quality and yield, as well as affect human health and food chain cycles. Therefore, developing rapid and effective detection methods is crucial. In this stu...

Rapid estimation of soil water content based on hyperspectral reflectance combined with continuous wavelet transform, feature extraction, and extreme learning machine.

PeerJ
BACKGROUND: Soil water content is one of the critical indicators in agricultural systems. Visible/near-infrared hyperspectral remote sensing is an effective method for soil water estimation. However, noise removal from massive spectral datasets and e...

Utilizing machine learning to classify persistent organic pollutants in the serum of pregnant women: a predictive modeling approach.

Environmental science and pollution research international
Polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs), and per- and poly-fluoroalkyl substances (PFAS) are persistent organic pollutants (POPs) that remain de...

Estimation of 100 m root zone soil moisture by downscaling 1 km soil water index with machine learning and multiple geodata.

Environmental monitoring and assessment
Root zone soil moisture (RZSM) is crucial for agricultural water management and land surface processes. The 1 km soil water index (SWI) dataset from Copernicus Global Land services, with eight fixed characteristic time lengths (T), requires root zone...

Exploring the response and prediction of phytoplankton to environmental factors in eutrophic marine areas using interpretable machine learning methods.

The Science of the total environment
Coastal marine areas are frequently affected by human activities and face ecological and environmental threats, such as algal blooms and climate change. The community structure of phytoplankton-primary producers in marine ecosystems-is highly sensiti...