A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery-Reference-Cited by-同舟云学术

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A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery

Published:2021-06 Issue:6 Volume:8 Page:
ISSN:2333-5084
Container-title:Earth and Space Science
language:en
Short-container-title:Earth Space Sci

Author:

Berndt E. B.¹²^ORCID,Elmer N. J.³²^ORCID,Junod R. A.⁴²^ORCID,Fuell K. K.⁴²,Harkema S. S.⁵²,Burke A. R.⁵²,Feemster C. M.⁵²

Affiliation:

1. NASA Marshall Space Flight Center Huntsville AL USA

2. Short‐term Prediction Research and Transition Center Huntsville AL USA

3. Universities Space Research Association Huntsville AL USA

4. University of Alabama in Huntsville Earth System Science Center Huntsville AL USA

5. University of Alabama in Huntsville College of Atmospheric & Earth Science Huntsville AL USA

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021EA001788

Reference38 articles.

1. Using the radiative temperature difference at 3.7 and 11 μm to tract dust outbreaks

2. Remote sensing aerosols using satellite infrared observations

3. Aeolian dust as a transport hazard

4. The sensitivity of the colour of dust in MSG-SEVIRI Desert Dust infrared composite imagery to surface and atmospheric conditions

5. A Methodology to Determine Recipe Adjustments for Multispectral Composites Derived from Next-Generation Advanced Satellite Imagers

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1. A transformer boosted UNet for smoke segmentation in complex backgrounds in multispectral LandSat imagery;Remote Sensing Applications: Society and Environment;2024-11

2. DustSCAN: A Five Year (2018-2022) Hourly Dataset of Dust Plumes From SEVIRI;Scientific Data;2024-06-08

3. Application of artificial intelligence algorithms and low-cost sensors to estimate respirable dust in the workplace;Environment International;2023-12

4. Detecting turbid plumes from satellite remote sensing: State-of-art thresholds and the novel PLUMES algorithm;Frontiers in Marine Science;2023-07-17

5. Dust Detection Over East Asia From Multispectral and Multi‐Temporal Himawari‐8/AHI Thermal Infrared Observations;Earth and Space Science;2023-02

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