AIMC Topic: Remote Sensing Technology
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Assessing foraging landscape quality in Quebec's commercial beekeeping through remote sensing, machine learning, and survival analysis.
Journal of environmental management
Jan 21, 2025
Honey bees (Apis mellifera) play an important role in our agricultural systems. In recent years, beekeepers have reported high colony mortality rates in several parts of the world. Inadequate foraging landscapes are often cited as a major factor dete...
Spatiotemporal variation in biomass abundance of different algal species in Lake Hulun using machine learning and Sentinel-3 images.
Scientific reports
Jan 21, 2025
Climate change and human activities affect the biomass of different algal and the succession of dominant species. In the past, phytoplankton phyla inversion has been focused on oceanic and continental shelf waters, while phytoplankton phyla inversion...
Integrating Remote Sensing and Soil Features for Enhanced Machine Learning-Based Corn Yield Prediction in the Southern US.
Sensors (Basel, Switzerland)
Jan 18, 2025
Efficient and reliable corn ( L.) yield prediction is important for varietal selection by plant breeders and management decision-making by growers. Unlike prior studies that focus mainly on county-level or controlled laboratory-scale areas, this stud...
Field-scale detection of Bacterial Leaf Blight in rice based on UAV multispectral imaging and deep learning frameworks.
PloS one
Jan 17, 2025
Bacterial Leaf Blight (BLB) usually attacks rice in the flowering stage and can cause yield losses of up to 50% in severely infected fields. The resulting yield losses severely impact farmers, necessitating compensation from the regulatory authoritie...
Remote Tongue-Based Control of a Wheelchair Mounted Assistive Robotic Manipulator and the Effect of Adaptive Semi-Automation.
IEEE transactions on bio-medical engineering
Jan 15, 2025
Increasing the independence of individuals with tetraplegia is a challenging task. One potential solution is to allow for use of an assistive robotic manipulator (ARM), when solving tasks in personal and remote space. There is a lack in available con...
Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of Grapevines.
Sensors (Basel, Switzerland)
Jan 13, 2025
Assessing vines' vigour is essential for vineyard management and automatization of viticulture machines, including shaking adjustments of berry harvesters during grape harvest or leaf pruning applications. To address these problems, based on a standa...
XIS-temperature: A daily spatiotemporal machine-learning model for air temperature in the contiguous United States.
Environmental research
Jan 12, 2025
The challenge of reconstructing air temperature for environmental applications is to accurately estimate past exposures even where monitoring is sparse. We present XGBoost-IDW Synthesis for air temperature (XIS-Temperature), a high-resolution machine...
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...
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