Artificial light sources make our daily life convenient, but cause a severe problem called light pollution. We propose a novel system for efficient visualization of light pollution in the night sky. Numerous methods have been proposed for rendering the sky, but most of these focus on rendering of the daytime or the sunset sky where the sun is the only, or dominant light source. For the visualization of the light pollution, however, we must consider many city light sources on the ground, resulting in excessive computational cost. We address this problem by precomputing a set of intensity distributions for the sky illuminated by city light at various locations and with different atmospheric conditions. We apply a principal component analysis and fast Fourier transform to the precomputed distributions, allowing us to efficiently visualize the extent of the light pollution. Using this method, we can achieve one to two orders of magnitudes faster computation compared to a naive approach that simply accumulates the scattered intensity for each viewing ray. Furthermore, the fast computation allows us to interactively solve the inverse problem that determines the city light intensity needed to reduce light pollution. Our system provides the user with both a forward and inverse investigation tool for the study and minimization of light pollution.

We propose an efficient, specific method for estimating camera parameters from a single starry night image. Such an image consists of a collection of disks representing stars, so traditional estimation methods for common pictures do not work. Our method uses a database, a star catalog, that stores the positions of stars on the celestial sphere. Our method computes magnitudes (i.e., brightnesses) of stars in the input image and uses them to find the corresponding stars in the star catalog. Camera parameters can then be estimated by a simple geometric calculation. Our method is over ten times faster and more accurate than a previous method.

The mid-Pleistocene climate transition (MPT) is a complex global change leading to late pleistocene ice ages with increased mean ice volume and dominant 100-ka cycle. However, the timing and structure of the MPT is still an open question both in marine and land sediments. In order to identify and explore the existence of MPT in terrestrial aeolian sediments, we carried out high-resolution rock magnetic analyses on aeolian loess sediments in the central Loess Plateau, North China. The results show that the MPT occurred at 0.93 Ma and ended at 0.62 Ma. This transition event maybe related to the aggravation of dry, the forming and expanding of desert in Asian interior triggered by the uplift of the Tibetan plateau besides global ice volume and solar insolation.