AIMC Topic: Snow
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Explainable machine learning for predictive modeling of blowing snow detection and meteorological feature assessment using XGBoost-SHAP.
PloS one
Mar 28, 2025
Accurate forecasting of blowing snow events is vital for improving numerical models of snow processes, yet traditional predictive methods often lack interpretability. This study leverages eXtreme Gradient Boosting (XGBoost) to detect blowing snow eve...
A Survey of Deep Learning-Based Image Restoration Methods for Enhancing Situational Awareness at Disaster Sites: The Cases of Rain, Snow and Haze.
Sensors (Basel, Switzerland)
Jun 22, 2022
This survey article is concerned with the emergence of vision augmentation AI tools for enhancing the situational awareness of first responders (FRs) in rescue operations. More specifically, the article surveys three families of image restoration met...
Capabilities of deep learning models on learning physical relationships: Case of rainfall-runoff modeling with LSTM.
The Science of the total environment
Aug 25, 2021
This study investigates the relationships which deep learning methods can identify between the input and output data. As a case study, rainfall-runoff modeling in a snow-dominated watershed by means of a long short-term memory (LSTM) network is selec...
Integrating camera imagery, crowdsourcing, and deep learning to improve high-frequency automated monitoring of snow at continental-to-global scales.
PloS one
Dec 27, 2018
Snow is important for local to global climate and surface hydrology, but spatial and temporal heterogeneity in the extent of snow cover make accurate, fine-scale mapping and monitoring of snow an enormous challenge. We took 184,453 daily near-surface...
Snow Height Sensors Reveal Phenological Advance in Alpine Grasslands.
Global change biology
May 1, 2025
Long-term phenological data in alpine regions are often limited to a few locations and thus, little is known about climate-change-induced plant phenological shifts above the treeline. Because plant growth initiation in seasonally snow-covered regions...
Deep learning to extract the meteorological by-catch of wildlife cameras.
Global change biology
Jan 1, 2024
Microclimate-proximal climatic variation at scales of metres and minutes-can exacerbate or mitigate the impacts of climate change on biodiversity. However, most microclimate studies are temperature centric, and do not consider meteorological factors ...
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