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Open AccessArticle

Comparison of Aqua/Terra MODIS and Himawari-8 Satellite Data on Cloud Mask and Cloud Type Classification Using Split Window Algorithm

1
Center for Environmental Remote Sensing, Chiba University, Chiba 2638522, Japan
2
Remote Sensing Technology and Data Center, Indonesian Institute of Aeronautics and Space (LAPAN), Jakarta 13710, Indonesia
3
Department of Physics, Faculty of Mathematics and Natural Science, Universitas Jenderal Soedirman, Central Java 53123, Indonesia
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(24), 2944; https://doi.org/10.3390/rs11242944
Received: 5 October 2019 / Revised: 29 November 2019 / Accepted: 2 December 2019 / Published: 9 December 2019
(This article belongs to the Special Issue Active and Passive Remote Sensing of Aerosols and Clouds)
Cloud classification is not only important for weather forecasts, but also for radiation budget studies. Although cloud mask and classification procedures have been proposed for Himawari-8 Advanced Himawari Imager (AHI), their applicability is still limited to daytime imagery. The split window algorithm (SWA), which is a mature algorithm that has long been exploited in the cloud analysis of satellite images, is based on the scatter diagram between the brightness temperature (BT) and BT difference (BTD). The purpose of this research is to examine the usefulness of the SWA for the cloud classification of both daytime and nighttime images from AHI. We apply SWA also to the image data from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra to highlight the capability of AHI. We implement the cloud analysis around Japan by employing band 3 (0.469 μm) of MODIS and band 1 (0.47 μm) of AHI for extracting the cloud-covered regions in daytime. In the nighttime case, the bands that are centered at 3.9, 11, 12, and 13 µm are utilized for both MODIS and Himawari-8, with somewhat different combinations for land and sea areas. Thus, different thresholds are used for analyzing summer and winter images. Optimum values for BT and BTD thresholds are determined for the band pairs of band 31 (11.03 µm) and 32 (12.02 µm) of MODIS (SWA31-32) and band 13 (10.4 µm) and 15 (12.4 µm) of AHI (SWA13-15) in the implementation of SWA. The resulting cloud mask and classification are verified while using MODIS standard product (MYD35) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data. It is found that MODIS and AHI results both capture the essential characteristics of clouds reasonably well in spite of the relatively simple scheme of SWA based on four threshold values, although a broader spread of BTD obtained with Himawari-8 AHI (SWA13-15) could possibly lead to more consistent results for cloud-type classification than SWA31-32 based on the MODIS sensors. View Full-Text
Keywords: Himawari-8 AHI; Aqua MODIS; Terra MODIS; cloud mask; cloud type classification; split window algorithm; brightness temperature Himawari-8 AHI; Aqua MODIS; Terra MODIS; cloud mask; cloud type classification; split window algorithm; brightness temperature
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MDPI and ACS Style

Purbantoro, B.; Aminuddin, J.; Manago, N.; Toyoshima, K.; Lagrosas, N.; Sumantyo, J.T.S.; Kuze, H. Comparison of Aqua/Terra MODIS and Himawari-8 Satellite Data on Cloud Mask and Cloud Type Classification Using Split Window Algorithm. Remote Sens. 2019, 11, 2944.

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