• Title/Summary/Keyword: Spatiotemporal GIS

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Analysis of Future Demand and Utilization of the Urban Meteorological Data for the Smart City (스마트시티를 위한 도시기상자료의 미래수요 및 활용가치 분석)

  • Kim, Seong-Gon;Kim, Seung Hee;Lim, Chul-Hee;Na, Seong-Kyun;Park, Sang Seo;Kim, Jaemin;Lee, Yun Gon
    • Atmosphere
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    • v.31 no.2
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    • pp.241-249
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    • 2021
  • A smart city utilizes data collected from various sensors through the internet of things (IoT) and improves city operations across the urban area. Recently substantial research is underway to examine all aspects of data that requires for the smart city operation. Atmospheric data are an essential component for successful smart city implementation, including Urban Air Mobility (UAM), infrastructure planning, safety and convenience, and traffic management. Unfortunately, the current level of conventional atmospheric data does not meet the needs of the new city concept. New and innovative approaches to developing high spatiotemporal resolution of observational and modeling data, resolving the complex urban structure, are expected to support the future needs. The geographic information system (GIS) integrates the atmospheric data with the urban structure and offers information system enhancement. In this study we proposed the necessity and applicability of the high resolution urban meteorological dataset based on heavy fog cases in the smart city region (e.g., Sejong and Pusan) in Korea.

Analysis on Spatiotemporal Variability of Erosion and Deposition Using a Distributed Hydrologic Model (분포형 수문모형을 이용한 침식 및 퇴적의 시.공간 변동성 분석)

  • Lee, Gi-Ha;Yu, Wan-Sik;Jang, Chang-Lae;Jung, Kwan-Sue
    • Journal of Korea Water Resources Association
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    • v.43 no.11
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    • pp.995-1009
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    • 2010
  • Accelerated soil erosion due to extreme climate change, such as increased rainfall intensity, and human-induced environmental changes, is a widely recognized problem. Existing soil erosion models are generally based on the gross erosion concept to compute annual upland soil loss in tons per acre per year. However, such models are not suitable for event-based simulations of erosion and deposition in time and space. Recent advances in computer geographic information system (GIS) technologies have allowed hydrologists to develop physically based models, and the trend in erosion prediction is towards process-based models, instead of conceptually lumped models. This study aims to propose an effective and robust distributed rainfall-sediment yield-runoff model consisting of basic element modules: a rainfall-runoff module based on the kinematic wave method for subsurface and surface flow, and a runoff-sediment yield-runoff model based on the unit stream power method. The model was tested on the Cheoncheon catchment, upstream of the Yongdam dam using hydrological data for three extreme flood events due to typhoons. The model provided acceptable simulation results with respect to both discharge and sediment discharge even though the simulated sedigraphs were underestimated, compared to observations. The spatial distribution of erosion and deposition demonstrated that eroded sediment loads were deposited in the cells along the channel network, which have a short overland flow length and a gentle local slope while the erosion rate increased as rainfall became larger. Additionally, spatially heterogeneous rainfall intensity, dependant on Thiessen polygons, led to spatially-distinct erosion and deposition patterns.