Tainan, the earliest developed city in Taiwan, was the origin of Taiwan's culture. Nearly 400 years ago, the coastal zone in Tainan connected a large lagoon, called Tai-Jiang Inner Sea. However, the environment was changed during the 400 years. The inner sea became land gradually and then the land was extending to the west for a few kilometers. Such changes affected many human activities such as the social activities, economic activities and land use. To comprehend the relation between the changes and the human activities, temporal spatial data was considered as a favorable data source for studying. The temporal datasets used in this study were collected from 1904 to 2011, which include: (1) old topographic maps; (2) historical aerial images; (3) officially topographic map; (4) modern images. These precious temporal datasets provide us the possibility of building the temporal spatial information. However, in order to retrieve these spatial information from the historical images, image registration and rectification should be done. In this study, we present a methodology of processing multi-temporal datasets during 100 years employed by commercial software (SOCET GXP 4.0) and a coordinate transformation of six parameter method. The accuracy of the transformation results and the limitation of each dataset for doing transformation were also assessed and discussed respectively in this paper. In the past, maps were rarely produced because of the lack of efficient mapping technology. The landscape of the history usually described in the literature. Combining temporal spatial information and historical literatures is therefore considered great improvements on the changing analysis. Hence we built a web-based viewing system for the comparison of multi-temporal data. In this study, we additionally focused on land use changes in the coastal zone of old Tainan city. The land use are classified into 9 categories and the changes are evaluated based on the land use categories. A transition matrix is also utilized to conjecture and explain the land use changes. The results demonstrate that the long-term change analysis is benefited from the temporal spatial information retrieved from the temporal datasets by our methodology.
|出版狀態||Published - 2014|
|事件||35th Asian Conference on Remote Sensing 2014: Sensing for Reintegration of Societies, ACRS 2014 - Nay Pyi Taw, Myanmar|
持續時間: 2014 十月 27 → 2014 十月 31
|Other||35th Asian Conference on Remote Sensing 2014: Sensing for Reintegration of Societies, ACRS 2014|
|城市||Nay Pyi Taw|
|期間||14-10-27 → 14-10-31|
All Science Journal Classification (ASJC) codes