AIMC Topic: Satellite Imagery

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Fusing satellite imagery and ground-based observations for PM air pollution modeling in Iran using a deep learning approach.

Scientific reports Jul 1, 2025
With the rapid advancement of urbanization and industrialization in cities, air pollution has become one of the significant environmental challenges and issues in many countries. The concentration of particulate matter with an aerodynamic diameter of...
Deep Learning Particulate Matter Models, Theoretical Iran Air Pollutants Environmental Monitoring Satellite Imagery Air Pollution Humans Neural Networks, Computer
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Global dominance of seasonality in shaping lake-surface-extent dynamics.

Nature May 28, 2025
Lakes are crucial for ecosystems, greenhouse gas emissions and water resources, yet their surface-extent dynamics, particularly seasonality, remain poorly understood at continental to global scales owing to limitations in satellite observations. Alth...
Ecosystem Satellite Imagery Lakes Seasons
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Satellite data to support air quality assessment and management.

Journal of the Air & Waste Management Association (1995) May 28, 2025
Satellite data have long been recognized as valuable for air quality applications. These applications are in a stage of rapid growth: new geostationary satellites provide hourly or sub-hourly data; improvements in algorithms convert measured waveleng...
United States Environmental Monitoring Air Pollution Satellite Imagery Air Pollutants Risk Assessment
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Enhanced wheat yield prediction through integrated climate and satellite data using advanced AI techniques.

Scientific reports May 24, 2025
Wheat plays a vital role in Pakistan's economy and food security, making accurate yield forecasting essential for planning and resource management. Traditional approaches-such as manual field surveys and remote sensing-have been widely used, but thei...
Remote Sensing Technology Triticum Deep Learning Agriculture Climate Satellite Imagery Pakistan Crops, Agricultural Machine Learning Forecasting
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Spatiotemporal variations in Pearl River plume dispersion over the last decade based on VIIRS-derived sea surface salinity.

Marine pollution bulletin May 22, 2025
A river plume indicates the dispersion and transport path of pollutants from runoff, monitoring the spatiotemporal variation of river plume distribution from space is crucial for marine environmental governance. This study focuses on the Pearl River ...
Salinity Satellite Imagery Water Movements Rivers Seawater China Environmental Monitoring Machine Learning Spatio-Temporal Analysis
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Modeling land use and land cover dynamics of Bale Mountains National Park using Google Earth Engine and cellular automata-artificial neural network (CA-ANN) model.

PloS one Apr 30, 2025
This research aimed to assess the observed land use and land cover (LULC) changes of Bale Mountains National Park (BMNP) from 1993 to 2023 and its future projections for the years (2033 and 2053). The study utilized multi-date Landsat imagery from 19...
Parks, Recreational Algorithms Humans Satellite Imagery Conservation of Natural Resources Forests Neural Networks, Computer
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U-shaped deep learning networks for algal bloom detection using Sentinel-2 imagery: Exploring model performance and transferability.

Journal of environmental management Apr 3, 2025
Inland water sources, such as lakes, support diverse ecosystems and provide essential services to human societies. However, these valuable resources are under increasing pressure from rapid climate changes and pollution resulting from human activitie...
Environmental Monitoring Climate Change Satellite Imagery Algorithms Ecosystem Lakes Deep Learning Eutrophication
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Beyond the Greater Angkor Region: Automatic large-scale mapping of Angkorian-period reservoirs in satellite imagery using deep learning.

PloS one Mar 26, 2025
Archaeologists often use high-resolution satellite imagery to identify potential archaeological sites or features, including ancient settlements, burial mounds, roads, and even subtle differences in vegetation or topography. Over the last several dec...
Archaeology Humans Satellite Imagery Deep Learning Cambodia
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Soil and crop interaction analysis for yield prediction with satellite imagery and deep learning techniques for the coastal regions.

Journal of environmental management Mar 25, 2025
Crop yield is a significant factor in world income and poverty alleviation as well as food production through agriculture. Conventional crop yield forecasting approaches that employ subjective estimates including farmers' perceptions are imprecise an...
Neural Networks, Computer Soil Crops, Agricultural Agriculture Satellite Imagery Deep Learning
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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...
Environmental Monitoring Support Vector Machine Crops, Agricultural Satellite Imagery Random Forest India Agriculture Machine Learning Algorithms
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