AIMC Topic: Remote Sensing Technology
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Cyanobacteria hot spot detection integrating remote sensing data with convolutional and Kolmogorov-Arnold networks.
The Science of the total environment
Jan 6, 2025
Prompt and accurate monitoring of cyanobacterial blooms is essential for public health management and understanding aquatic ecosystem dynamics. Remote sensing, in particular satellite observations, presents a good alternative for continuous monitorin...
Multi-level feature fusion networks for smoke recognition in remote sensing imagery.
Neural networks : the official journal of the International Neural Network Society
Jan 4, 2025
Smoke is a critical indicator of forest fires, often detectable before flames ignite. Accurate smoke identification in remote sensing images is vital for effective forest fire monitoring within Internet of Things (IoT) systems. However, existing dete...
Integrating machine learning and remote sensing for long-term monitoring of chlorophyll-a in Chilika Lagoon, India.
Environmental monitoring and assessment
Dec 26, 2024
Chlorophyll-a (Chla) is recognized as a key indicator of water quality and ecological health in aquatic ecosystems, offering valuable insights into ecosystem dynamics and changes over time. This study aimed to to develop and validate a robust ML mode...
Wastewater treatment plant site selection using advanced decision tree machine learning and remote sensing techniques.
Environmental science and pollution research international
Dec 16, 2024
Wastewater treatment plants in Coimbatore South are under pressure from rapid urbanization, inadequate infrastructure, and industrial pollution, leading to environmental and public health concerns. This study aimed to identify suitable locations for ...
Extraction of agricultural plastic greenhouses based on a U-Net convolutional neural network coupled with edge expansion and loss function improvement.
Journal of the Air & Waste Management Association (1995)
Dec 12, 2024
Agricultural plastic greenhouses (APGs) are crucial for sustainable agricultural planting, and accurate spatial distribution information acquisition is crucial. Deep learning network models can extract target features from remote sensing images more ...
Multitemporal monitoring of forest indicator species using UAV and machine learning image recognition.
Environmental monitoring and assessment
Dec 2, 2024
In natural restoration, it is important to improve the efficiency of monitoring. Remote sensing using unmanned aerial vehicle (UAV) platforms plays a major role in improving monitoring efficiency. UAV platforms are particularly suited for monitoring ...
Assessing Huanglongbing Severity and Canopy Parameters of the Huanglongbing-Affected Citrus in Texas Using Unmanned Aerial System-Based Remote Sensing and Machine Learning.
Sensors (Basel, Switzerland)
Nov 29, 2024
Huanglongbing (HLB), also known as citrus greening disease, is a devastating disease of citrus. However, there is no known cure so far. Recently, under Section 24(c) of the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), a special local ...
Gross primary productivity estimation through remote sensing and machine learning techniques in the high Andean Region of Ecuador.
International journal of biometeorology
Nov 27, 2024
Accurately estimating gross primary productivity (GPP) is crucial for simulating the carbon cycle and addressing the challenges of climate change. However, estimating GPP is challenging due to the absence of direct measurements at scales larger than ...
Understanding ecosystem services of detailed forest and wetland types using remote sensing and deep learning techniques in Northern China.
Journal of environmental management
Nov 20, 2024
Spanning both temperate and sub-frigid zones, Northeast China boasts typical boreal forests and abundant wetland resources. Because of these attributes, the region is critically significant for global climate regulation, carbon sequestration, and bio...
Long-term water quality assessment in coastal and inland waters: An ensemble machine-learning approach using satellite data.
Marine pollution bulletin
Nov 16, 2024
Accurate estimation of coastal and in-land water quality parameters is important for managing water resources and meeting the demand of sustainable development goals. The water quality monitoring based on discrete water sample analysis is limited to ...
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