Title | ||
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An improved mosaic method considering atmospheric diffusion in aerosol optical depth retrieval case |
Abstract | ||
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Aerosol optical depth (AOD) is a key parameter reflecting aerosol properties, and it is inevitable to mosaic multi-orbit data while making AOD datasets in some situations due to the limitation in scanning width of various instruments. This article summarizes some conventional methods eliminating seams of mosaic images, and introduces the idea of combining the Gaussian dispersion model into mosaic process in the AOD retrieval case. In this article, we elaborate the principle of the Gauss plume model and put forward the improved method. Based on the AOD products from the Synergetic Retrieval of Aerosol Properties (SRAP) model from the Moderate Resolution Imaging Spectroradiometer (MODIS) data, we conduct experiments on improved methods, and evaluate the processing effect. |
Year | DOI | Venue |
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2012 | 10.1109/IGARSS.2012.6351033 | IGARSS |
Keywords | Field | DocType |
aerosol properties,atmospheric techniques,improved mosaic method,atmospheric diffusion,mosaic,scanning width,srap model,aerosol optical depth (aod),aerosols,gauss plume model,processing effect,atmospheric movements,seams,aod datasets,data acquisition,modis data,synergetic retrieval of aerosol properties,gaussian processes,gaussian dispersion model,mosaic process,aerosol optical depth retrieval case,moderate resolution imaging spectroradiometer,mosaic images,multi-orbit data mosaic,dispersion,atmospheric modeling,meteorology,optical imaging | Meteorology,Dispersion (optics),Optical depth,Moderate-resolution imaging spectroradiometer,Computer science,Remote sensing,Data acquisition,Aerosol,Gaussian,Gaussian process,AOD products | Conference |
ISSN | ISBN | Citations |
2153-6996 E-ISBN : 978-1-4673-1158-8 | 978-1-4673-1158-8 | 0 |
PageRank | References | Authors |
0.34 | 1 | 7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jia Liu | 1 | 10 | 5.97 |
Yong Xue | 2 | 118 | 57.61 |
Hui Xu | 3 | 26 | 8.13 |
Yingjie Li | 4 | 45 | 15.79 |
Jie Guang | 5 | 50 | 26.12 |
Chi Li | 6 | 3 | 5.32 |
Leiku Yang | 7 | 10 | 8.17 |