AIMC Topic: Satellite Imagery

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Towards sustainable coastal management: aerial imagery and deep learning for high-resolution mapping.

PeerJ Sep 23, 2024
The massive arrival of pelagic on the coasts of several countries of the Atlantic Ocean began in 2011 and to date continues to generate social and environmental challenges for the region. Therefore, knowing the distribution and quantity of in the o...
Mexico Atlantic Ocean Conservation of Natural Resources Sargassum Satellite Imagery Deep Learning Bathing Beaches Environmental Monitoring Humans Algorithms
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Comparison of conventional and machine learning regression models for accurate prediction of selected optical active components - A case study: The Gulf of Izmit.

Marine pollution bulletin Sep 14, 2024
This study hypothesizes that advanced machine learning (ML) models can more accurately predict certain critical water quality parameters in marine environments compared to conventional regression techniques. We specifically evaluated the spatio-tempo...
Machine Learning Ecosystem Environmental Monitoring Chlorophyll Chlorophyll A Water Quality Satellite Imagery Seawater
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STransU2Net: Transformer based hybrid model for building segmentation in detailed satellite imagery.

PloS one Sep 12, 2024
As essential components of human society, buildings serve a multitude of functions and significance. Convolutional Neural Network (CNN) has made remarkable progress in the task of building extraction from detailed satellite imagery, owing to the pote...
Neural Networks, Computer Image Processing, Computer-Assisted Algorithms Satellite Imagery Humans
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Mapping of temperate upland habitats using high-resolution satellite imagery and machine learning.

Environmental monitoring and assessment Aug 31, 2024
Upland habitats provide vital ecological services, yet they are highly threatened by natural and anthropogenic stressors. Monitoring these vulnerable habitats is fundamental for conservation and involves determining information about their spatial lo...
Machine Learning Ireland Satellite Imagery Remote Sensing Technology Conservation of Natural Resources Ecosystem Environmental Monitoring
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Deep Learning with Pretrained Framework Unleashes the Power of Satellite-Based Global Fine-Mode Aerosol Retrieval.

Environmental science & technology Aug 3, 2024
Fine-mode aerosol optical depth (fAOD) is a vital proxy for the concentration of anthropogenic aerosols in the atmosphere. Currently, the limited data length and high uncertainty of the satellite-based data diminish the applicability of fAOD for clim...
Satellite Imagery Atmosphere Environmental Monitoring Deep Learning Aerosols
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Utilizing deep learning algorithms for automated oil spill detection in medium resolution optical imagery.

Marine pollution bulletin Jul 30, 2024
This study evaluates the performance of three typical convolutional neural network based deep learning algorithms for oil spill detection using medium-resolution optical satellite imagery from Sentinel-2 MSI, Landsat-8 OLI, and Landsat-9 OLI2. Oil sl...
Satellite Imagery Petroleum Pollution Neural Networks, Computer Algorithms Environmental Monitoring Remote Sensing Technology Deep Learning
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Advancements in urban scene segmentation using deep learning and generative adversarial networks for accurate satellite image analysis.

PloS one Jul 18, 2024
In the urban scene segmentation, the "image-to-image translation issue" refers to the fundamental task of transforming input images into meaningful segmentation maps, which essentially involves translating the visual information present in the input ...
Satellite Imagery Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms
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Machine learning-based estimation of land surface temperature variability over a large region: a temporally consistent approach using single-day satellite imagery.

Environmental monitoring and assessment Jul 16, 2024
Accurate retrieval of LST is crucial for understanding and mitigating the effects of urban heat islands, and ultimately addressing the broader challenge of global warming. This study emphasizes the importance of a single day satellite imageries for l...
Machine Learning Temperature Satellite Imagery Global Warming Environmental Monitoring Seasons
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Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HEAT Center study protocol.

BMJ open Jun 18, 2024
INTRODUCTION: African cities, particularly Abidjan and Johannesburg, face challenges of rapid urban growth, informality and strained health services, compounded by increasing temperatures due to climate change. This study aims to understand the compl...
Hot Temperature Satellite Imagery Climate Change Heat Stress Disorders Humans Machine Learning Cities South Africa Research Design
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Novel artificial intelligence assisted Landsat-8 imagery analysis for mango orchard detection and area mapping.

PloS one Jun 14, 2024
The mango fruit plays a crucial role in providing essential nutrients to the human body and Pakistani mangoes are highly coveted worldwide. The escalating demand for agricultural products necessitates enhanced methods for monitoring and managing agri...
Artificial Intelligence Machine Learning Remote Sensing Technology Pakistan Agriculture Mangifera Satellite Imagery Fruit Humans Crops, Agricultural
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