Generating high resolution of daily mean temperature using statistical models

Yoon, Sanghoo

doi:10.7465/jkdi.2016.27.5.1215

Cited by 4 publications

(1 citation statement)

References 20 publications

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“…또한 산림재적에 대한 현장조사 시 그 지점에 위치하는 산림의 수고와 흉고직경을 측정하여 재적값을 구하는 데, 이러한 방법이 상당한 관측 오차를 유발한다는 점 또한 문제가 될 수 있다. 따라서 본 논문에서는 산 림의 공간효과를 고려한 계층적 베이지안 분석을 통해 관측되지 않은 전체 산림재적을 추정하고자 한다 (Lee와 Kim, 2016;Yoon, 2016). Matérn, 1986).…”

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Hierarchical Bayesian analysis for a forest stand volume

Song¹,

Park²,

Kim³

2017

Journal of the Korean Data and Information Science Society

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It has gradually become important to estimate a forest stand volume utilizing Li-DAR data. Recently, various statistical models including a linear regression model has been introduced to estimate a forest stand volume using LiDAR data. One of limitations of the current approaches is in that the accuracy of observed forest stand volume data, which is used as a response variable, is questionable unstable. To overcome this limitation, we consider a spatial structure for a forest stand volume. In this research, we propose a hierarchical model for applying a spatial structure to a forest stand volume. The proposed model is applied to the LiDAR data and the forest stand volume for Bonghwa, Gyeongsangbuk-do.

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Hierarchical Bayesian analysis for a forest stand volume

Song¹,

Park²,

Kim³

2017

Journal of the Korean Data and Information Science Society

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Correlation Analysis of Meteorological Factors for Wooden Building in Beopjusa and Seonamsa Temples by Statistical Model

Kim¹,

Kim²,

Lim³

et al. 2018

Journal of Conservation Science

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Exposure to the natural environment can cause damage to domestic wooden cultural assets, such as temples. Deterioration is accelerated by biological damage and various environmental factors. In this study, meteorological factors were monitored by equipment installed at Beopjusa temple of Boeun province and Seonamsa temple of Suncheon province. A statistical model was applied to these data to predict the meteorological factors and to compare the predictive performance of each meteorological factor. The resulting correlation coefficient between air and dew point temperatures was highest, at 0.95, while the correlation coefficient for relative humidity had a moderate value(0.65) at both the Beopjusa and Seonamsa temples. Thus, a general linear model was found to be suitable for predicting air and dew point temperatures. An analysis of correlation between meteorological factors showed that there was strong positive correlation between air temperature and dew point temperature, and between solar radiation and evaporation at both sites. There was a weak positive correlation

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