• Title/Summary/Keyword: 지역 대푯값

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Estimation of Representative Area-Level Concentrations of Particulate Matter(PM10) in Seoul, Korea (미세먼지(PM10)의 지역적 대푯값 산정 방법에 관한 연구 - 서울특별시를 대상으로)

  • SONG, In-Sang;KIM, Sun-Young
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.4
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    • pp.118-129
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    • 2016
  • Many epidemiological studies, relying on administrative air pollution monitoring data, have reported the association between particulate matter ($PM_{10}$) air pollution and human health. These monitoring data were collected at a limited number of fixed sites, whereas government-generated health data are aggregated at the area level. To link these two data types for assessing health effects, it is necessary to estimate area-level concentrations of $PM_{10}$. In this study, we estimated district (Gu)-level $PM_{10}$ concentrations using a previously developed pointwise exposure prediction model for $PM_{10}$ and three types of point locations in Seoul, Korea. These points included 16,230 centroids of the largest census output residential areas, 422 community service centers, and 610 centroids on the 1km grid. After creating three types of points, we predicted $PM_{10}$ annual average concentrations at all locations and calculated Gu averages of predicted $PM_{10}$ concentrations as representative Gu-estimates. Then, we compared estimates to each other and to measurements. Prediction-based Gu-level estimates showed higher correlations with measurement-based estimates as prediction locations became more population representative ($R^2=0.06-0.59$). Among the three estimates, grid-based estimates gave lowest correlations compared to the other two(0.35-0.47). This study provides an approach for estimating area-level air pollution concentrations and assesses air pollution health effects using national-scale administrative health data.

Optimal Design of Friction Dampers based on the Story Shear Force Distribution of a Building Structure (경주지역에서 발생한 3개 지진의 지진원 및 지진파전파 매질특성에 관한 연구)

  • Jung, Je-Won;Kim, Jun-Kyoung
    • Journal of the Earthquake Engineering Society of Korea
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    • v.10 no.1 s.47
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    • pp.33-39
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    • 2006
  • Parameters including the seismic sources and the elastic wave propagation characteristics were analysed using the observed ground motions from 3 Kyoungju region earthquakes. The Levenberg-Marquardt algorithm was applied to invert all the variables non-linearly and simultaneously with S wave energy In frequency domain. Average stress drop of 3 events and local attenuation parameter ${\kappa}$ were estimated to about 48-bar and 0.0312 respectively. Regional attenuation parameter, Qo and ${\eta}$, were also estimated to be about 417 and 0.83. ${\kappa}$ values are much higher than that of EUS, even though smaller than that of WUS. All these values resultant from this study show that there are differences in some parameters of other studios due to differences in the governing equation. of acceleration motions

The study of heavy rain warning in Gangwon State using threshold rainfall (침수유발 강우량을 이용한 강원특별자치도 호우특보 기준에 관한 연구)

  • Lee, Hyeonjia;Kang, Donghob;Lee, Iksangc;Kim, Byungsikd
    • Journal of Korea Water Resources Association
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    • v.56 no.11
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    • pp.751-764
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    • 2023
  • Gangwon State is centered on the Taebaek Mountains with very different climate characteristics depending on the region, and localized heavy rainfall is a frequent occurrence. Heavy rain disasters have a short duration and high spatial and temporal variability, causing many casualties and property damage. In the last 10 years (2012~2021), the number of heavy rain disasters in Gangwon State was 28, with an average cost of 45.6 billion won. To reduce heavy rain disasters, it is necessary to establish a disaster management plan at the local level. In particular, the current criteria for heavy rain warnings are uniform and do not consider local characteristics. Therefore, this study aims to propose a heavy rainfall warning criteria that considers the threshold rainfall for the advisory areas located in Gangwon State. As a result of analyzing the representative value of threshold rainfall by advisory area, the Mean value was similar to the criteria for issuing a heavy rain warning, and it was selected as the criteria for a heavy rain warning in this study. The rainfall events of Typhoon Mitag in 2019, Typhoons Maysak and Haishen in 2020, and Typhoon Khanun in 2023 were applied as rainfall events to review the criteria for heavy rainfall warnings, as a result of Hit Rate accuracy verification, this study reflects the actual warning well with 72% in Gangneung Plain and 98% in Wonju. The criteria for heavy rain warnings in this study are the same as the crisis warning stages (Attention, Caution, Alert, and Danger), which are considered to be possible for preemptive rain disaster response. The results of this study are expected to complement the uniform decision-making system for responding to heavy rain disasters in the future and can be used as a basis for heavy rain warnings that consider disaster risk by region.

Exploring Optimal Threshold of RGB Pixel Values to Extract Road Features from Google Earth (Google Earth에서 도로 추출을 위한 RGB 화소값 최적구간 추적)

  • Park, Jae-Young;Um, Jung-Sup
    • Journal of Korea Spatial Information System Society
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    • v.12 no.1
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    • pp.66-75
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    • 2010
  • The authors argues that the current road updating system based on traditional aerial photograph or multi-spectral satellite image appears to be non-user friendly due to lack of the frequent cartographic representation for the new construction sites. Google Earth are currently being emerged as one of important places to extract road features since the RGB satellite image with high multi-temporal resolution can be accessed freely over large areas. This paper is primarily intended to evaluate optimal threshold of RGB pixel values to extract road features from Google Earth. An empirical study for five experimental sites was conducted to confirm how a RGB picture provided Google Earth can be used to extact the road feature. The results indicate that optimal threshold of RGB pixel values to extract road features was identified as 126, 125, 127 for manual operation which corresponds to 25%, 30%, 19%. Also, it was found that display scale difference of Google Earth was not very influential in tracking required RGB pixel value. As a result the 61cm resolution of Quickbird RGB data has shown the potential to realistically identified the major type of road feature by large scale spatial precision while the typical algorithm revealed successfully the area-wide optimal threshold of RGB pixel for road appeared in the study area.