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.

Silica is one of the mineral needs of industry, especially in base materials for the primary or auxiliary raw materials. Silica sand on Rupat Island was identified on the northern coastline. Selected samples were measured to get the percentage of minerals/elements using X-ray fluorescence. Two adjacent scenes of ALOS PALSAR full-polarimetry data were used. The dielectric constant of samples was measured using a dielectric probe kit in the frequency range from 0.3 to 3.0 GHz and also used for calculating the backscattering coefficient. Freeman-Durdeen and Yamaguchi techniques were used to obtain the scattering decomposition of physical scattering from the incoherent object model base. Surface scattering is a very clear decomposition used to show the silica sand identification compared with other decompositions. From surface scattering, the backscattering coefficient value of silica sand resulted from −59 dB to −52 dB. Thickness estimation from satellite and field measurements show the minimum is 59 cm and the maximum is 74 cm, with the average differentiation between these measurements being 4.88 cm. The condition supported by the grain size of silica sand particles that have almost the same size and shape were conducted by using microscopic photograph testing. These values were caused by a slightly rough surface.

Research on climate change was conducted in Bali, Indonesia, using the Conformal Cubic Atmospheric Model (CCAM), which works with the Representative Concentration Pathway (RCP) 4.5. The history data means average data from 1971 to 2000, climate projections with RCP4.5 scenario means average data from 2040 to 2069, and anomaly (climate change) is RCP4.5 minus history. The results represent the history of temperature between 22.5-27.5 ⁰C and the projection between 25.5-29.5 ⁰C. Temperature anomalies can be observed in much of northern Bali, which has increased from about 1.6 to 2.9 ⁰C. There is a trend towards reduced (drier) humidity in most parts of Bali, particularly in the northern part of Bali. In contrast, a small amount in the south increases the (wetter) humidity. The comfort index of the Bali region in history is still relatively comfortable (20-26 ⁰C). The projection condition RCP 4.5, there is no comfortable area with an index of more than 26 ⁰C (hot and dry).