• Asian Journal of Atmospheric Environment
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• 제6권2호
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• pp.127-135
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• 2012

Urbanization has led to a reduction in green spaces and thus transformed the spatial pattern of urban land use. An increase in air temperature directly affects forest vegetation, phenology, and biodiversity in urban areas. In this paper, we analyze the changing land use patterns and urban heat distribution (UHD) in Seoul on the basis of a spatial assessment. It is necessary to monitor and assess the functions of green spaces in order to understand the changes in the green space. In addition, we estimated the influence of green space on urban temperature using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery and climatic data. Results of the assessment showed that UHD differences cause differences in temperature variation and the spatial extent of temperature reducing effects due to urban green space. The ratio of urban heat area to green space cooling area increases rapidly with increasing distance from a green space boundary. This shows that urban green space plays an important role for mitigating urban heating in central areas. This study demonstrated the importance of green space by characterizing the spatiotemporal variations in temperature associated with urban green spaces.

• 대한원격탐사학회지
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• 제28권6호
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• pp.683-691
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• 2012

High resolution satellite images are now widely used for a variety of mapping applications including photogrammetry, GIS data acquisition and visualization. As the spectral and spatial data size of satellite images increases, a greater processing power is needed to process the images. The solution of these problems is parallel systems. Parallel processing techniques have been developed for improving the performance of image processing along with the development of the computational power. However, conventional CPU-based parallel computing is often not good enough for the demand for computational speed to process the images. The GPU is a good candidate to achieve this goal. Recently GPUs are used in the field of highly complex processing including many loop operations such as mathematical transforms, ray tracing. In this study we proposed a technique for parallel processing of high resolution satellite images using GPU. We implemented a spectral radiometric processing algorithm on Landsat-7 ETM+ imagery using CUDA, a parallel computing architecture developed by NVIDIA for GPU. Also performance of the algorithm on GPU and CPU is compared.