North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube)
The Meteosat Second Generation (MSG) geostationary platform equipped with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument provides observations of the Earth every 15 min since 2004. Based on those measurements, we present a new method called North African Sandstorm Survey (NASC...
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ftdoajarticles:oai:doaj.org/article:d9126e0b0c174a16ac1382d844ae25b8 2023-05-15T13:06:18+02:00 North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) Louis Gonzalez Xavier Briottet 2017-08-01T00:00:00Z https://doi.org/10.3390/rs9090896 https://doaj.org/article/d9126e0b0c174a16ac1382d844ae25b8 EN eng MDPI AG https://www.mdpi.com/2072-4292/9/9/896 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs9090896 https://doaj.org/article/d9126e0b0c174a16ac1382d844ae25b8 Remote Sensing, Vol 9, Iss 9, p 896 (2017) SEVIRI sandstorm day and night AOD retrieval North Africa Saudi Arabia Science Q article 2017 ftdoajarticles https://doi.org/10.3390/rs9090896 2022-12-31T11:06:07Z The Meteosat Second Generation (MSG) geostationary platform equipped with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument provides observations of the Earth every 15 min since 2004. Based on those measurements, we present a new method called North African Sandstorm Survey (NASCube) to: (i) generate day/night remote sensing images in order to detect sandstorms over the Sahara and Saudi Arabia; and (ii) estimate day and night aerosol optical depth (AOD). This paper presents a method to create true color day and night images from the SEVIRI instrument level 1.5 products and the complete operational data processing system to detect sandstorms and quantify the AOD over the desert areas of North Africa and Saudi Arabia. The designed retrieval algorithms are essentially based on the use of artificial neural networks (ANN), which seems to be well suited to this issue. Our methods are validated against two different datasets, namely the Deep Blue NASA moderate-resolution imaging spectroradiometer (MODIS) product and AErosol RObotic NETwork (AERONET) acquisitions located in desert areas. It is shown that NASCube products deliver better estimations for high AOD (>0.2) over land areas than Deep Blue products. The open-public web platform will help researchers to identify, quantify and retrieve the impact of sandstorms over desert regions. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Remote Sensing 9 9 896 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
SEVIRI sandstorm day and night AOD retrieval North Africa Saudi Arabia Science Q |
spellingShingle |
SEVIRI sandstorm day and night AOD retrieval North Africa Saudi Arabia Science Q Louis Gonzalez Xavier Briottet North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
topic_facet |
SEVIRI sandstorm day and night AOD retrieval North Africa Saudi Arabia Science Q |
description |
The Meteosat Second Generation (MSG) geostationary platform equipped with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument provides observations of the Earth every 15 min since 2004. Based on those measurements, we present a new method called North African Sandstorm Survey (NASCube) to: (i) generate day/night remote sensing images in order to detect sandstorms over the Sahara and Saudi Arabia; and (ii) estimate day and night aerosol optical depth (AOD). This paper presents a method to create true color day and night images from the SEVIRI instrument level 1.5 products and the complete operational data processing system to detect sandstorms and quantify the AOD over the desert areas of North Africa and Saudi Arabia. The designed retrieval algorithms are essentially based on the use of artificial neural networks (ANN), which seems to be well suited to this issue. Our methods are validated against two different datasets, namely the Deep Blue NASA moderate-resolution imaging spectroradiometer (MODIS) product and AErosol RObotic NETwork (AERONET) acquisitions located in desert areas. It is shown that NASCube products deliver better estimations for high AOD (>0.2) over land areas than Deep Blue products. The open-public web platform will help researchers to identify, quantify and retrieve the impact of sandstorms over desert regions. |
format |
Article in Journal/Newspaper |
author |
Louis Gonzalez Xavier Briottet |
author_facet |
Louis Gonzalez Xavier Briottet |
author_sort |
Louis Gonzalez |
title |
North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
title_short |
North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
title_full |
North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
title_fullStr |
North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
title_full_unstemmed |
North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube) |
title_sort |
north africa and saudi arabia day/night sandstorm survey (nascube) |
publisher |
MDPI AG |
publishDate |
2017 |
url |
https://doi.org/10.3390/rs9090896 https://doaj.org/article/d9126e0b0c174a16ac1382d844ae25b8 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing, Vol 9, Iss 9, p 896 (2017) |
op_relation |
https://www.mdpi.com/2072-4292/9/9/896 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs9090896 https://doaj.org/article/d9126e0b0c174a16ac1382d844ae25b8 |
op_doi |
https://doi.org/10.3390/rs9090896 |
container_title |
Remote Sensing |
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9 |
container_issue |
9 |
container_start_page |
896 |
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1766000002390294528 |