AIMC Topic: Urbanization

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Multi-modal deep learning for intelligent landscape design generation: A novel CBS3-LandGen model.

PloS one Jul 24, 2025
With the acceleration of the global urbanization process, landscape design is facing increasingly complex challenges. Traditional manual design methods are gradually unable to meet the needs for efficiency, precision, and sustainability. To address t...
Urbanization Models, Theoretical Conservation of Natural Resources Humans Deep Learning
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A bird species occurrence dataset from passive audio recordings across dense urban areas in Gothenburg, Sweden.

Scientific data Jul 10, 2025
Bird species occurrence datasets are a valuable resource for understanding the effects of urbanization on various biotic conditions (e.g., species occupancy and richness). Existing datasets offer promising opportunities to explore variations among ci...
Birds Machine Learning Sweden Urbanization Cities Animals
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Monitoring temporal changes in large urban street trees using remote sensing and deep learning.

PloS one Jun 26, 2025
In the rapidly changing dynamics of urbanization, urban forests offer numerous benefits to city dwellers. However, the information available on these resources is often outdated or non-existent, leading in part to inequitable access to these benefits...
Humans Ecosystem Remote Sensing Technology Forests Trees Deep Learning Cities San Francisco Urbanization
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Unsupervised deep clustering of high-resolution satellite imagery reveals phenotypes of urban development in Sub-Saharan Africa.

The Science of the total environment Jun 5, 2025
Sub-Saharan Africa and other developing regions have urbanized extensively, leading to complex urban features with varying presence and types of roads, buildings and vegetation. We use a novel hierarchical deep learning framework and high-resolution ...
Phenotype Deep Learning Africa South of the Sahara Satellite Imagery Cities Urbanization Environmental Monitoring
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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...
Environmental Monitoring Conservation of Natural Resources Urbanization Cities Models, Theoretical Neural Networks, Computer Machine Learning China
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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...
Urbanization Cities Environmental Monitoring Machine Learning Nigeria
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Exploring the impact of natural and human activities on vegetation changes: An integrated analysis framework based on trend analysis and machine learning.

Journal of environmental management Jan 17, 2025
Climate, human activities and terrain are crucial factors influencing vegetation changes. Despite their crucial role, there is a notable lack of research exploring the nonlinear relationships between them and vegetation changes, especially over exten...
Humans Machine Learning China Plants Human Activities Urbanization Climate Pattern Analysis, Machine
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Exploring the impact of land use on bird diversity in high-density urban areas using explainable machine learning models.

Journal of environmental management Jan 11, 2025
Amid rapid urbanization, land use shifts in cities globally have profound effects on ecosystems and biodiversity. Birds, as a crucial component of urban biodiversity, are highly sensitive to environmental changes and often serve as indicator species ...
Cities Biodiversity Urbanization Conservation of Natural Resources Ecosystem Birds China Machine Learning Animals
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Spatiotemporal analysis of land surface temperature and land cover changes in Prešov city using downscaling approach and machine learning algorithms.

Environmental monitoring and assessment Jan 3, 2025
In recent decades, global climate change and rapid urbanization have aggravated the urban heat island (UHI) effect, affecting the well-being of urban citizens. Although this significant phenomenon is more pronounced in larger metropolitan areas due t...
Machine Learning Support Vector Machine Climate Change Spatio-Temporal Analysis Slovakia Urbanization Algorithms Temperature Cities Environmental Monitoring
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Ensemble intelligence prediction algorithms and land use scenarios to measure carbon emissions of the Yangtze River Delta: A machine learning model based on Long Short-Term Memory.

PloS one Dec 9, 2024
Land use in urban agglomerations is the main source of carbon emissions, and reducing them and improving land use efficiency are the keys to achieving sustainable development goals (SDGs). To advance the literature on densely populated cities and hig...
Sustainable Development China Urbanization Carbon Humans Cities Machine Learning Rivers Neural Networks, Computer Environmental Monitoring Algorithms
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