AIMC Topic: Environmental Monitoring

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Temporal insights into ecological community: Advancing waterbird monitoring with dome camera and deep learning.

Journal of environmental management
Biodiversity monitoring is critical for conservation and management. However, efficient species monitoring is often hindered by the complexities of ecological dynamics and the constraints of conventional techniques. This study presents an automated o...

Revealing the impacts of the built environment factors on pedestrian-weighted air pollutant concentration using automated and interpretable machine learning.

Journal of environmental management
Urban air pollution poses significant health risks, especially to pedestrians due to their proximity to pollutants and lack of physical protection. Understanding the influence of built environment factors is essential to mitigate this pollution and s...

Data-Driven Detection of Nocturnal Pollen Fragmentation Triggered by High Humidity in an Urban Environment.

Environmental science & technology
Biological particulate matter (BioPM) in the urban environment can affect human health and climate. Pollen, a key BioPM component, produces smaller particles when fragmented, significantly impacting public health. However, detecting pollen fragmentat...

Long-term water quality simulation and driving factors identification within the watershed scale using machine learning.

Journal of contaminant hydrology
Understanding long-term trends and analyzing their driving factors are essential to effectively enhance water quality in watersheds. In China, although the overall quality of surface water continues to improve, significant issues remain in certain re...

Multi-machine learning methods for rapid and synergistic inversion of groundwater contamination source, hydrogeologic parameter and boundary condition.

Journal of contaminant hydrology
The application of machine learning methods to the groundwater pollution inversion problem has become a hot research topic in recent years. However, applying machine learning methods to achieve synergistic and rapid identification of pollution source...

Machine learning-based prediction of ambient CO and CH concentrations with high temporal resolution in Seoul metropolitan area.

Environmental pollution (Barking, Essex : 1987)
Machine learning has the potential to support the growing need for high-resolution greenhouse gas monitoring in urban and industrial environments, where deploying extensive sensor networks is often limited by cost and operational challenges. This stu...

Evaluating marine environmental pollution using Fuzzy Analytic Hierarchy Process (FAHP): A comprehensive framework for sustainable coastal and oceanic management.

Marine pollution bulletin
Marine pollution poses a significant threat to ecosystems, biodiversity, and human health, necessitating a structured evaluation framework. This study applies the Fuzzy Analytic Hierarchy Process (FAHP) to prioritize five major marine pollution sourc...

A lightweight spatial and spectral CNN model for classifying floating marine plastic debris using hyperspectral images.

Marine pollution bulletin
Marine plastic debris poses a significant environmental threat. In order to study and combat this pollution, efficient and automated detection methods are essential. Hyperspectral imaging and deep learning provide a robust framework for classifying f...

Integrating bioassay and machine learning data for ecological risk assessments of herbicide use on Ulva australis.

Marine pollution bulletin
Herbicide contamination of aquatic ecosystems poses a critical risk to biodiversity. Bioassays provide useful ecological insights on responses to herbicides; however, they require a model organism. Ulva australis is an ideal candidate for herbicide t...

Spatio-temporal prediction of groundwater vulnerability based on CNN-LSTM model with self-attention mechanism: A case study in Hetao Plain, northern China.

Journal of environmental sciences (China)
Located in northern China, the Hetao Plain is an important agro-economic zone and population centre. The deterioration of local groundwater quality has had a serious impact on human health and economic development. Nowadays, the groundwater vulnerabi...