The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Taklimakan Desert, located in southwest Xinjiang Uyghur Autonomous Region, is one of the predominant dust origin in China. Dust is one of the main types of atmospheric aerosol in this region. Emerging remote sensing imagery from geostationary meteorological satellite undeniably becomes an ideal mean for monitoring large regional distribution and intensity of dust storms. Among them, Indian National...
A comparison between the algorithm for Land Aerosol property and Bidirectional reflectance Inversion by Time Series technique (LABITS) and a daily estimation of aerosol optical depth (AOD) algorithm (AERUS-GEO) over land surface using MSG/SEVIRI data over North Africa is presented. To obtain indications about the quantitative performance of two AOD retrieval methods mentioned above, daily SEVIRI AOD...
Aerosol Optical Thickness (AOT) retrieval over very bright surface is a great challenge because the surface contribution dominates the Top Of Atmosphere (TOA) signal. In this paper, we presented a method for AOT retrieval over snow-covered surface. For the first step, the surface is assumed to be a mixture between snow and ice. The main idea is that the ratio between nadir and forward observation...
The determination of aerosol's effect contains much uncertainty. During quantification of aerosols via remote sensing, surface reflectance error of 0.01 could bring Aerosol Optical Depth (AOD) error of 0.1. In order to avoid this, simultaneous retrieval of AOD and surface properties would be a promising method. In this paper, we present a novel analytic solution to atmospheric radiative transfer equation...
The algorithm is based on the assumption that TOA reflectance increase with the aerosol load as well as the surface reflectance at same time gradually changes on different days within 14 days. Then the surface reflectance is derived from FengYun-2D (FY2D) measurements every 1 hour as the second darkest of reflectance for each time of day to minimize the effect of geometry change and cloud. The “true...
Aerosol optical depth (AOD) is a significant indicator of dust episode. However, AOD retrieval over land still remains a difficult task because the measured signal is a composite of reflectance of sunlight by the variable surface covers and back scattering by the semitransparent aerosol layer. In this paper, an approach using bi-angle with Moderate Resolution Imaging Spectroradiometer (MODIS) data...
Atmospheric remote sensing offers us a view to estimate air quality in describing the aerosol distribution either for a local or global coverage because aerosol parameters, such as aerosol optical depth (AOD) are significant indicators of the air quality. However, AOD retrieval over land still remains a difficult task because the measured signal is a composite of reflectance of sunlight by the variable...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.