Machine Learning Applications to Dust Storms: A Meta-Analysis
Abstract Dust storms are natural hazards that affect both people and properties. Therefore, it is important to mitigate their risks by implementing an early notification system. Different methods are used to predict dust storms, such as observing satellite images, analyzing meteorological data, and...
Saved in:
Main Authors: | Reem K. Alshammari, Omer Alrwais, Mehmet Sabih Aksoy |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer
2022-10-01
|
Series: | Aerosol and Air Quality Research |
Subjects: | |
Online Access: | https://doi.org/10.4209/aaqr.220183 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Synoptic- and Remote Sensing-based Analysis of a Severe Dust Storm Event over Central Asia
by: Parya Broomandi, et al.
Published: (2023-01-01) -
Organic Carbon and Elemental Carbon in Two Dust Plumes at a Coastal City in North China
by: Wenhua Wang, et al.
Published: (2024-03-01) -
Long-term Measurements of PM2.5 Concentrations in Lubbock, Texas
by: Mary C. Kelley, et al.
Published: (2020-04-01) -
Coping with sand and dust storms: Developing and validating of an adaptation assessment tool
by: Shiva Salehi, et al.
Published: (2024-12-01) -
Effects of coal mine dust on lung function in rats
by: LIU Yang, LI Meng, LU Liyuan, WANG Ru, YANG He, ZHANG Huifang
Published: (2025-01-01)