AIMC Topic: Environmental Monitoring

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Spatial point patterns generation on remote sensing data using convolutional neural networks with further statistical analysis.

Scientific reports
Continuous technological growth and the corresponding environmental implications are triggering the enhancement of advanced environmental monitoring solutions, such as remote sensing. In this paper, we propose a new method for the spatial point patte...

Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter.

Environmental pollution (Barking, Essex : 1987)
From hourly ozone observations obtained from three regions⸻Houston, Dallas, and West Texas⸻we investigated the contributions of meteorology to changes in surface daily maximum 8-h average (MDA8) ozone from 2000 to 2019. We applied a deep convolutiona...

Estimation and uncertainty analysis of groundwater quality parameters in a coastal aquifer under seawater intrusion: a comparative study of deep learning and classic machine learning methods.

Environmental science and pollution research international
Excessive withdrawal of groundwater for agricultural irrigation can cause seawater intrusion into coastal aquifers. Such a case will in turn results in deterioration of irrigation water quality. Determination of irrigation water quality with traditio...

Generating a long-term (2003-2020) hourly 0.25° global PM dataset via spatiotemporal downscaling of CAMS with deep learning (DeepCAMS).

The Science of the total environment
Generating a long-term high-spatiotemporal resolution global PM dataset is of great significance for environmental management to mitigate the air pollution concerns worldwide. However, the current long-term (2003-2020) global reanalysis dataset Coper...

Application of artificial intelligence models for prediction of groundwater level fluctuations: case study (Tehran-Karaj alluvial aquifer).

Environmental monitoring and assessment
The nonlinear groundwater level fluctuations depend on the interaction of many factors such as evapotranspiration, precipitation, groundwater abstraction, and hydrogeological characteristics, making groundwater level prediction a complex task. Ground...

Detecting the sources of chemicals in the Black Sea using non-target screening and deep learning convolutional neural networks.

The Science of the total environment
The Black Sea is an important ecosystem, which is affected by various anthropogenic pressures, such as shipping activities and wastewater inputs from large coastal cities. Significant loads of chemical pollutants are being continuously brought in by ...

Renewing and improving the environmental risk assessment of chemicals.

The Science of the total environment
The processes underpinning the environmental risk assessment (ERA) of chemicals have not changed appreciably in the last 30 years. It is unclear how successful these processes are in protecting the environment from any adverse effects of chemicals. T...

Research on Cyanobacterial-Bloom Detection Based on Multispectral Imaging and Deep-Learning Method.

Sensors (Basel, Switzerland)
Frequent outbreaks of cyanobacterial blooms have become one of the most challenging water ecosystem issues and a critical concern in environmental protection. To overcome the poor stability of traditional detection algorithms, this paper proposes a m...

New Deep Learning Model to Estimate Ozone Concentrations Found Worrying Exposure Level over Eastern China.

International journal of environmental research and public health
Ozone (O3), whose concentrations have been increasing in eastern China recently, plays a key role in human health, biodiversity, and climate change. Accurate information about the spatiotemporal distribution of O3 is crucial for human exposure studie...

A Low-Cost AI Buoy System for Monitoring Water Quality at Offshore Aquaculture Cages.

Sensors (Basel, Switzerland)
The ocean resources have been rapidly depleted in the recent decade, and the complementary role of aquaculture to food security has become more critical than ever before. Water quality is one of the key factors in determining the success of aquacultu...