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2016
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| Online Access: | https://doi.org/10.5281/zenodo.16732151 |
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| _version_ | 1866901471989071872 |
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| author | El-ossta, Esam |
| author_facet | El-ossta, Esam |
| contents | <p><span>Dust storms are one of the natural hazards whose<br>incidence has increased in the recent years over Sahara desert,<br>Australia and northern China. Thus, it is important to know the<br>causation, movement and radiation effects of dust storms.<br>Satellite remote sensing is the most common method for<br>monitoring Dust Storms but its use over sandy ground is still<br>limited as they have similar characteristics. Many researchers<br>have studied the detection of dust storms during daytime in a<br>number of different regions of the world including China,<br>Australia, America, and North Africa using a variety of satellite<br>data. However, there have been fewer studies for detecting dust<br>storms at night. The key elements of this study are to use a<br>back-propagation artificial neural network with Brightness<br>Temperature of band 31 and four Brightness Temperature<br>Differences calculated using data from the Moderate Resolution<br>Imaging Spectroradiometers on the Terra and Aqua satellites to<br>develop a method for detecting dust storms during both day and<br>night. Results have shown that the method can detect dust<br>storms at both day and night and also over different land<br>surfaces.</span> </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16732151 |
| institution | Zenodo |
| language | |
| publishDate | 2016 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Automatic Detection for Day and Night Time Dust Storms Using MODIS bands. El-ossta, Esam <p><span>Dust storms are one of the natural hazards whose<br>incidence has increased in the recent years over Sahara desert,<br>Australia and northern China. Thus, it is important to know the<br>causation, movement and radiation effects of dust storms.<br>Satellite remote sensing is the most common method for<br>monitoring Dust Storms but its use over sandy ground is still<br>limited as they have similar characteristics. Many researchers<br>have studied the detection of dust storms during daytime in a<br>number of different regions of the world including China,<br>Australia, America, and North Africa using a variety of satellite<br>data. However, there have been fewer studies for detecting dust<br>storms at night. The key elements of this study are to use a<br>back-propagation artificial neural network with Brightness<br>Temperature of band 31 and four Brightness Temperature<br>Differences calculated using data from the Moderate Resolution<br>Imaging Spectroradiometers on the Terra and Aqua satellites to<br>develop a method for detecting dust storms during both day and<br>night. Results have shown that the method can detect dust<br>storms at both day and night and also over different land<br>surfaces.</span> </p> |
| title | Automatic Detection for Day and Night Time Dust Storms Using MODIS bands. |
| url | https://doi.org/10.5281/zenodo.16732151 |