North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube)

• Published in: Remote Sensing
• Main Authors: Gonzalez, Louis, Briottet, Xavier
• Other Authors: Laboratoire d’Optique Atmosphérique - UMR 8518 (LOA), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), ONERA - The French Aerospace Lab Toulouse, ONERA
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2017
• Subjects: SANDSTORM; DAY AND NIGHT AOD RETRIEVAL; SEVIRI; NORTH AFRICA; SAUDI ARABIA; [SPI.OPTI]Engineering Sciences [physics]/Optics / Photonic; Aerosol Robotic Network
• Online Access: https://hal.science/hal-01629144; https://hal.science/hal-01629144/document; https://hal.science/hal-01629144/file/remotesensing-09-00896.pdf; https://doi.org/10.3390/rs9090896

International audience 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.