• Title/Summary/Keyword: Spatial autocorrelation

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Theory of efficient array observations of microtremors with special reference to the SPAC method (SPAC 방법에 근거한 상시진동의 효과적 배열 관측 이론)

  • Okada, Hiroshi
    • Geophysics and Geophysical Exploration
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    • v.9 no.1
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    • pp.73-85
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    • 2006
  • Array observations of the vertical component of microtremors are frequently conducted to estimate a subsurface layered-earth structure on the assumption that microtremors consist predominantly of the fundamental mode Rayleigh waves. As a useful tool in the data collection, processing and analysis, the spatial autocorrelation (SPAC) method is widely used, which in practice requires a circle array consisting of M circumferential stations and one centre station (called "M-station circle array", where M is the number of stations). The present paper considers the minimum number of stations required for a circle array for efficient data collection in terms of analytical efficacy and field effort. This study first rearranges the theoretical background of the SPAC algorithm, in which the SPAC coefficient for a circle array with M infinite is solely expressed as the Bessel function, $J_0(rk)$ (r is the radius and k the wavenumber). Secondly, the SPAC coefficient including error terms independent of the microtremor energy field for an M-station circle array is analytically derived within a constraint for the wave direction across the array, and is numerically evaluated in respect of these error terms. The main results of the evaluation are: 1) that the 3-station circle array when compared with other 4-, 5-, and 9-station arrays is the most efficient and favourable for observation of microtremors if the SPAC coefficients are used up to a frequency at which the coefficient takes the first minimum value, and 2) that the Nyquist wavenumber is the most influential factor that determines the upper limit of the frequency range up to which the valid SPAC coefficient can be estimated.

Application of Environmental Planning Considering the Trend of PM10 in Ambient Air (미세먼지(PM10) 추세를 고려한 환경계획 적용 방향 제안)

  • Yoon, Eun Joo
    • Journal of Environmental Impact Assessment
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    • v.29 no.3
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    • pp.210-218
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    • 2020
  • Even though PM10 in ambient air has been steadily reduced, the perception of it has been deteriorated. Forthatreason, first, it can still be mentioned the annual average concentration of PM10 exceeding WHO standards, second, an increase in the number of high concentration days of PM10, and third, lack of consideration for differences in causes and phenomena of PM10 by regions. Therefore, this study was aimed to suggest management types for PM10 in ambient air by clustering 69 cities based on the trends and current levels of PM10. In addition, we proposed complementary measures such as the green infrastructure, ventilation corridors and adaptation measures (limit of exposure) for type III (distribution in the central inner region) and IV (metropolitan city, south-east coast region) where improvement of PM10 was insufficient. Although this study did not consider the cause of PM10 together, there is a significance that the scientific basis for responding to the near future is conducted based on past trends of PM10.

Application of Hot Spot Analysis for Interpreting Soil Heavy-Metal Concentration Data in Abandoned Mines (폐금속 광산의 토양 중금속 오염 조사 자료 해석을 위한 핫스팟 분석의 적용)

  • LEE, Chae-Young;KIM, Sung-Min;CHOI, Yo-Soon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.2
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    • pp.24-35
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    • 2019
  • In this study, a hotspot analysis was conducted to suggest a new method for interpreting soil heavy-metal contamination data of abandoned metal mines according to statistical significance level. The spatial autocorrelation of the data was analyzed using the Getis-Ord $Gi{\ast}$ statistic in order to check whether soil heavy metal contamination data showing abnormal values appeared concentrated or dispersed in a specific space. As a result, the statistically significant data showing abnormal values in the mine area could be classified as follows: (1) the contamination degree and the hotspot value (z-score) were both high, (2) the contamination degree was high but the z-score was low, (3) the contamination degree was low but the z-score was high and (4) the contamination degree and the z-score were both low. The proposed method can be used to interpret the soil heavy metal contamination data according to the statistical significance level and to support a rational decision for soil contamination management in abandoned mines.