AIMC Topic: Environmental Monitoring

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A hybrid deep learning model for regional O and NO concentrations prediction based on spatiotemporal dependencies in air quality monitoring network.

Environmental pollution (Barking, Essex : 1987)
Short-term prediction of urban air quality is critical to pollution management and public health. However, existing studies have failed to make full use of the spatiotemporal correlations or topological relationships among air quality monitoring netw...

Prediction of monthly precipitation using various artificial models and comparison with mathematical models.

Environmental science and pollution research international
Precipitation (PP) prediction is an interesting topic in the meteorology or hydrology field since it is directly related to agriculture, the management of water resources in hydrologic basins, and water scarcity. Selecting the right model to predict ...

Evaluation and prediction of irrigation water quality of an agricultural district, SE Nigeria: an integrated heuristic GIS-based and machine learning approach.

Environmental science and pollution research international
Poor irrigation water quality can mar agricultural productivity. Traditional assessment of irrigation water quality usually requires the computation of various conventional quality parameters, which is often time-consuming and associated with errors ...

Farmland quality assessment using deep fully convolutional neural networks.

Environmental monitoring and assessment
Farmland is the cornerstone of agriculture and is important for food security and social production. Farmland assessment is essential but traditional methods are usually expensive and slow. Deep learning methods have been developed and widely applied...

Remote Sensing and Nonlinear Auto-regressive Neural Network (NARNET) Based Surface Water Chemical Quality Study: A Spatio-Temporal Hybrid Novel Technique (STHNT).

Bulletin of environmental contamination and toxicology
In recent days, the quality of water in inland water bodies has been threatened by various natural and anthropogenic activities. Henceforth, the continuous monitoring of water quality is mandatory to control the pollution level in surface water bodie...

Hourly Water Level Forecasting in an Hydroelectric Basin Using Spatial Interpolation and Artificial Intelligence.

Sensors (Basel, Switzerland)
In this work, a new hydroelectric basin modelling approach is described and applied to the Pontecosi basin, Italy. Several types of data sources were used to learn the model: a number of weather stations, satellite observations, the reanalysis datase...

Deep learning-based ensemble modeling of Vibrio parahaemolyticus concentration in marine environment.

Environmental monitoring and assessment
Vibrio parahaemolyticus (V.p) is a marine pathogenic bacterium that poses a high risk to human health and shellfish industry, yet an effective regional-scale nowcasting model for managing the risk remains lacking. This study presents the first region...

Urban Heat Island Intensity Changes in Guangdong-Hong Kong-Macao Greater Bay Area of China Revealed by Downscaling MODIS LST with Deep Learning.

International journal of environmental research and public health
The urban heat island (UHI) effect caused by urbanization negatively impacts the ecological environment and human health. It is crucial for urban planning and social development to monitor the urban heat island effect and study its mechanism. Due to ...

Computer-aided classification of successional stage in subtropical Atlantic Forest: a proposal based on fuzzy artificial intelligence.

Environmental monitoring and assessment
STATEMENT OF PROBLEM: Due to the continuous variability of the forest regeneration process, patterns of indicator variables with membership in more than one successional stage may occur, making the classification of such stages a challenging and comp...

Examining the Relationship between Land Use/Land Cover (LULC) and Land Surface Temperature (LST) Using Explainable Artificial Intelligence (XAI) Models: A Case Study of Seoul, South Korea.

International journal of environmental research and public health
Understanding the relationship between land use/land cover (LULC) and land surface temperature (LST) has long been an area of interest in urban and environmental study fields. To examine this, existing studies have utilized both white-box and black-b...