We used Structure from Motion with Multi-View Stereo Photogrammetry (SfM–MVS) to produce a high-resolution Digital Surface Model (DSM) based on archived aerial photographs taken during the 34th Japanese Antarctic Research Expedition in 1993. We applied this technique to aerial photos of Skarvsnes, Soya Coast, East Antarctica, and succeeded in creating a DSM with 1.4 m spatial resolution, which is sufficient for the identification of streamlined bedforms. Although a col-shaped distortion was identified in the SfM–DSM image, this was reduced by correcting the 3D surface trend estimation of the distortion. A comparison between the SfM–DSM constructed from images acquired in 1993 and the Geospatial Information Authority of Japan DSM (GSI–DSM) constructed from images acquired in 2009 revealed that a lake (Kaminotani Ike) underwent a significant rise in water level of >20 m, which exceeds the vertical root mean square error of each DSM. DSM generated using SfM–MVS can therefore be used for geomorphological studies. It can also be applied as basic data for research on global environmental changes such as ice-sheet mass balance and ice-sheet monitoring.

As a result of analyzing the collection rate of local taxes and the financial situation in the basic municipalities in a metropolitan area, it is clear that the finances of local governments in the metropolitan area are susceptible to economic fluctuations and the impact of the delinquency of local taxes. Therefore, this paper quantitatively analyzes the collection rate of local taxes and the index related to the issues of poverty, and examines the determinant factors and spatial patterns. The study area was the Tokyo metropolitan area, which includes Tokyo Metropolis and three prefectures, Saitama, Chiba, and Kanagawa (excluding special wards in Tokyo). The findings are summarized as follows.

1) Local governments with low local tax collection rates have a significant relationship with indicators related to the issue of poverty such as average annual income and unemployment rate, which have an explanatory power of about 60%. Therefore, areas with low collection rates have appeared in a sectoral form corresponding to the knowledge of social status in urban spatial structure.

2) Through analysis of local Moran statistics, cool spot areas with significantly low collection rates were detected in spatial continuity. In addition, geographically weighted regression analysis suggested that there are regional differences in the factors that determine the collection rate.