AIMC Topic: Environmental Monitoring

Clear Filters Showing 81 to 90 of 1085 articles

Evaluating the change and trend of construction land in Changsha City based GeoSOS-FLUS model and machine learning methods.

Scientific reports Mar 20, 2025
This study systematically analyzes the land use changes in Changsha City from 2000 to 2023. Three classification models-Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and Artificial Neural Network (ANN) were employed to evaluate the accu...
China Cities Neural Networks, Computer Machine Learning Conservation of Natural Resources Models, Theoretical Urbanization Environmental Monitoring
View on PubMed DOI

Urban change detection: assessing biophysical drivers using machine learning and Google Earth Engine.

Environmental monitoring and assessment Mar 20, 2025
Urban areas are experiencing rapid transformations, driven by population growth, economic development, and policy changes. Understanding and monitoring these dynamic changes is crucial for sustainable urban planning and management. This study leverag...
Nigeria Cities Machine Learning Environmental Monitoring Urbanization
View on PubMed DOI

Machine learning-based habitat mapping of the invasive Prosopis juliflora in Sharjah, UAE.

Environmental monitoring and assessment Mar 20, 2025
Prosopis juliflora, one of the most invasive trees, adversely affects the ecosystem and native plant communities in arid lands. This disrupts biodiversity and depletes water resources, posing significant ecological and economic challenges. Several at...
Environmental Monitoring United Arab Emirates Prosopis Introduced Species Machine Learning Ecosystem
View on PubMed DOI

Evaluating the performance of random forest, support vector machine, gradient tree boost, and CART for improved crop-type monitoring using greenest pixel composite in Google Earth Engine.

Environmental monitoring and assessment Mar 19, 2025
The development of machine learning algorithms, along with high-resolution satellite datasets, aids in improved agriculture monitoring and mapping. Nevertheless, the use of high-resolution optical satellite datasets is usually constrained by clouds a...
Crops, Agricultural Satellite Imagery India Machine Learning Agriculture Environmental Monitoring Algorithms Support Vector Machine Random Forest
View on PubMed DOI

How monitoring crops and drought, combined with climate projections, enhances food security: Insights from the Northwestern regions of Bangladesh.

Environmental monitoring and assessment Mar 19, 2025
Crop and drought monitoring are vital for sustainable agriculture, as they ensure optimal crop growth, identify stress factors, and enhance productivity, all of which contribute to food security. However, climate projections are equally important as ...
Climate Droughts Climate Change Agriculture Environmental Monitoring Food Security Bangladesh Crops, Agricultural
View on PubMed DOI

Explainable no-code OECD-compliant machine learning models to predict the mutagenic activity of polycyclic aromatic hydrocarbons and their radical cation metabolites.

The Science of the total environment Mar 18, 2025
Polycyclic aromatic hydrocarbons (PAHs) are persistent pollutants with well-known genotoxic and mutagenic effects, posing risks to ecosystems and human health. Their hydrophobic nature promotes accumulation in soils and aquatic environments, increasi...
Environmental Monitoring Models, Chemical Environmental Pollutants Machine Learning Risk Assessment Mutagenicity Tests Cations Polycyclic Aromatic Hydrocarbons Organisation for Economic Co-Operation and Development Mutagens
View on PubMed DOI

Optimizing deep neural networks for high-resolution land cover classification through data augmentation.

Environmental monitoring and assessment Mar 18, 2025
This study presents an innovative approach to high-resolution land cover classification using deep learning, tackling the challenge of working with an exceptionally small dataset. Manual annotation of land cover data is both time-consuming and labor-...
Conservation of Natural Resources Spain Deep Learning Environmental Monitoring Neural Networks, Computer
View on PubMed DOI

Artificial intelligence based detection and control strategies for river water pollution: A comprehensive review.

Journal of contaminant hydrology Mar 17, 2025
Water quality (WQ) is a metric for assessing the overall health and safety of water bodies like a river. Owing to the habitation of anthropogenic habitation around its basin, the rivers can become one of the most contaminated water sources globally. ...
Water Quality Rivers Water Pollutants, Chemical Water Pollution Artificial Intelligence Environmental Monitoring Neural Networks, Computer
View on PubMed DOI

Comparing the performance of 10 machine learning models in predicting Chlorophyll a in western Lake Erie.

Journal of environmental management Mar 17, 2025
Algal blooms, which have substantial adverse effects, are increasingly occurring worldwide in the context of global warming and eutrophication. Machine learning models (MLMs) are emerging as efficient and promising tools for predicting algal blooms. ...
Machine Learning Chlorophyll A Lakes Environmental Monitoring Water Quality Eutrophication Chlorophyll
View on PubMed DOI

Prediction of suspended sediment load in Sungai Semenyih using extreme learning machines and metaheuristic optimization approach.

Journal of environmental management Mar 17, 2025
Suspended sediment load (SSL) refers to sediment particles, such as silt and clay, that are suspended in water. It plays a critical role in hydrology and water quality management, influencing factors such as water quality, river erosion, sedimentatio...
Machine Learning Rivers Geologic Sediments Extreme Learning Machines Environmental Monitoring Water Quality
View on PubMed DOI
Popular Topics
Recent Journals