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Abstract

Department of Urban and Environmental Engineering (Environmental Science and Engineering)Sea ice closely interacts with the atmosphere and ocean systems. Land fast sea ice (fast ice) is a kind of sea ice attached to the shore, ice shelves, or grounded icebergs. It is widely distributed along the Antarctic coast and acts as an interface between the atmosphere and the ocean, affecting heat balance feedback, thermal insulation effects, and deep water formation depending on the temporal and spatial effects of the environmental conditions. It also plays an important role in the biological aspects of Antarctica. Attached to the Antarctic glacier is strongly associated with calving events of ice shelf as it is physically coupled with glaciers at the terminus. The existing Antarctic fast ice has been mainly focused on the East Antarctic, especially for the research on long-term fast ice. Several case studies for West Antarctic fast ice with satellite images were performed in local areas. Various types of satellite data and detection techniques were utilized to successfully detect fast ice. In addition, long-term fast ice maps specifically focused on the Amundsen sea of West Antarctica were generated to investigate the distribution and variability of fast ice. This thesis reports the results of fast ice detection algorithms that have been developed using various satellite images that can be used for fast ice detection. Along with the use of multiple satellite data, the proposed fast ice detection algorithms can more effectively detect fast ice, which then allows to obtain more accurate fast ice detection and produce long-term fast ice with high accuracy. Especially, the distribution and variability of time-series fast ice in West Antarctica, which is more concentrated in the Amundsen Sea, were analyzed together with bathymetry data and the distribution of glacier icebergs. In order to detect fast ice, machine learning techniques were basically used in this thesis. Two classes (i.e. fast ice and non-fast ice) were classified. Using MODIS images, there was a problem that fast ice was not produced in cloud cover areas and the polar night season, which is winter season in Antarctica. MODIS and AMSR-E satellite data were selectively used to solve the cloud contamination problem. Correlation-related variables were finally added based on the fact that fast ice is motionless for a certain period of time, and fast ice detection was performed at 15-day intervals using the improved input variables. Active microwave sensor data, ALOS PALSAR, was also used to detect fast ice and to validate fast ice detection results. Its high-spatial resolution allows to extract fast ice boundary more accurately. Fast ice detections showed good agreement with available ALOS PALSAR SAR images and MODIS reflectance images. Nearly decade-long fast ice extents were produced in the Amundsen Sea of West Antarctica and analyzed in terms of spatiotemporal variations with bathymetry and icebergs calved from ice shelves in study area. In addition, anomalous fast ice breakup events were examined, which suggests the importance of fast ice on the stability of ice shelves.clos

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