시계열 원격탐사 기법을 활용한 도시 식별 연구

Abstract

This paper introduces an exploratory approach that is based on time-series remote sensing techniques when identifying urban areas that are undergoing urbanization. By nature, urban sprawl is temporally and spatially dynamic; however, in the literature, the phenomenon has been typically identified with the remote sensing approaches that focus more on the spatial dimension of change than its temporal dimension. In this research, a seasonal trend analysis that focuses more on the time dimension is employed to identify urban areas in Northeast Asia between 1982 and 2002 with the support of the Geographic Information Systems/Remote Sensing (GIS/RS) computer software Idrisi. The seasonal trend analysis combines time-series Fourier analysis and time-series regression. It turns out that this exploratory approach is effective in analyzing and mapping spatiotemporal change of urban land-cover at the pixel level but is limited in delineating urban extents because of the discordance between urban land-cover and land-use. Therefore, when analyzing urban areas through time-series remote sensing as future research diverse map compositions are suggested to be explored along with the indices that quantify distinct temporal trends.