• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.257-266
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• 2017

In this study, the dust/smoke detection algorithm was developed with a multi-spectral satellite remote sensing method using Moderate resolution Imaging Spectroradiometer (MODIS) Level 1B (L1B) data and the results were validated as RGB composite images of red(R; band 1), green(G; band 4), blue(B; band 3) channels using MODIS L1B data and Cloud-Aerosol Lidar with Orthogonal Polarization Satellite Observations(CALIPSO) Vertical Feature Mask (VFM) product. In the daytime on March 30, 2007 and April 27, 2012, the consistencies between the dust/smoke detected by this algorithm and verification data were approximately 56.4 %, 72.0 %, respectively. During the nighttime, the similar consistency was 40.5 % on April 27, 2012. Although these results were analyzed for limited cases due to the spatiotemporal matching for the MODIS and CALIPSO satellites, they could be used to utilize the aerosol detection of geostationary satellites for the next generations in Korea through further research.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.3
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• pp.493-507
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• 2018

Due to high spatio-temporal variability of amount and optical/microphysical properties of atmospheric aerosols, satellite-based observations have been demanded for spatiotemporal monitoring the major aerosols. Observations of the heavy aerosol episodes and determination on the dominant aerosol types from a geostationary satellite can provide a chance to prepare in advance for harmful aerosol episodes as it can repeatedly monitor the temporal evolution. A new geostationary observation sensor, namely the Advanced Himawari Imager (AHI), onboard the Himawari-8 platform, has been observing high spatial and temporal images at sixteen wavelengths from 2016. Using observed spectral visible reflectance and infrared brightness temperature (BT), the algorithm to find major aerosol type such as volcanic ash (VA), desert dust (DD), polluted aerosol (PA), and clean aerosol (CA), was developed. RGB color composite image shows dusty, hazy, and cloudy area then it can be applied for comparing aerosol detection product (ADP). The CALIPSO level 2 vertical feature mask (VFM) data and MODIS level 2 aerosol product are used to be compared with the Himawari-8/AHI ADP. The VFM products can deliver nearly coincident dataset, but not many match-ups can be returned due to presence of clouds and very narrow swath. From the case study, the percent correct (PC) values acquired from this comparisons are 0.76 for DD, 0.99 for PA, 0.87 for CA, respectively. The MODIS L2 Aerosol products can deliver nearly coincident dataset with many collocated locations over ocean and land. Increased accuracy values were acquired in Asian region as POD=0.96 over land and 0.69 over ocean, which were comparable to full disc region as POD=0.93 over land and 0.48 over ocean. The Himawari-8/AHI ADP algorithm is going to be improved continuously as well as the validation efforts will be processed by comparing the larger number of collocation data with another satellite or ground based observation data.