• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.1
• /
• pp.45.2-46
• /
• 2021

The Hayabusa 2 mission target asteroid (162173) Ryugu is a near-Earth, carbonaceous (C-type) asteroid. Before the arrival, this asteroid is expected to be covered with mm- to cm- sized grains through the thermal infrared observations [1]. These grains are widely understood to be formed by past impacts with other celestial bodies and fractures induced by thermal fatigue [2]. However, the close-up images by the MASCOT lander showed lumpy boulders but no abundant fine grains [3]. Morota et al. suggested that there would be submillimeter particles on the top of these boulders but not resolved by Hayabusa 2's onboard instruments [4]. Hence, we conducted polarimetry of Ryugu to investigate microscopic grain sizes on its surface. Polarimetry is a powerful tool to estimate physical properties such as albedo and grain size. Especially, it is known that the maximum polarization degree (Pmax) and the geometric albedo (pV) show an empirical relationship depending on surface grain sizes [5]. We observed Ryugu from UT 2020 November 30 to December 10 at large phase angles (ranging from 78.5 to 89.7 degrees) to derive Pmax. We modified TRIPOL (Triple Range Imager and POLarimeter, [6]) to attach to the 1.8-m telescope at the Bohyunsan Optical Astronomy Observatory (BOAO). With this instrument, we observed the asteroid and determined linear polarization degrees at the Rc-band filter. We obtained sufficient data sets from 7 nights at this observatory to determine the Pmax value, and collaborated with other observatories in Japan (i.e., Hokkaido University, Higashi-Hiroshima, and Nishi-Harima) to acquire linear polarization degrees of the asteroid from total 24 nights observations with large phase angle coverage (From 28 to 104 degrees). The observational results have been published in Kuroda et al. (2021) [7]. We thus found the dominance of submillimeter particles on the surface of Ryugu from the comparison with other meteorite samples from the campaign observation. In this presentation, we report our activity to modify the TRIPOL for the 1.8-m telescope and the polarimetric performance. We also examine the rotational variability of the polarization degree using the TRIPOL data.

• Korean Journal of Remote Sensing
• /
• v.30 no.4
• /
• pp.481-491
• /
• 2014

Blue-ice area is a glacial ice field in ice sheet, ice shelf and glaciers where snow ablation and sublimation is larger than snowfall. As the blue-ice area has large influences on the meteorite concentration mechanism and ice mass balance, it is required to quantify the concentration of blue-ice. We analyzed spectral reflectance characteristics of blue-ice, snow and cloud by using MODIS images obtained over blue-ice areas in McMurdo Dry Valleys, East Antarctica, from 2007 to 2012. We then developed Normalized Difference Blue-ice Index (NDBI) algorithm which quantifies the concentration of blue-ice. Snow and cloud have a high reflectance in visible and near-infrared (NIR) bands. Reflectance of blue-ice is high in blue band, while that lowers in the NIR band. NDBI is calculated by dividing the difference of reflectance in the blue and NIR bands by the sum of reflectances in the two bands so that NDBI = (Blue-NIR)/(Blue + NIR). NDBI calculated from the MODIS images showed that the blue-ice areas have values ranging from 0.2 to 0.5, depending on the exposure and concentration of blue-ice. It is obviously different from that of snow and cloud that has values less than 0.2 or rocks with negative values. The change of NDBI values in the blue-ice area has higher correlation with snow depth ($R^2=0.699$) than wind speed ($R^2=0.012$) or air temperature ($R^2=0.278$), all measured at a meteorological station installed in McMurdo Dry Valleys. As the snow depth increased, the NDBI value decreased, which suggests that snow depth can be estimated from NDBI values over blue-ice areas. The NDBI algorithm developed in this study will be useful for various polar research fields such as meteorite exploration, analysis of ice mass balance as well as the snow depth estimation.