38 research outputs found

    Macular thickness variations with sex, age, and axial length in healthy subjects: a spectral domain-optical coherence tomography study

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    PURPOSE: To assess the relationship between macular retinal thickness and volume and age, sex, and refractive error/axial length with spectral domain-optical coherence tomography (SD-OCT). METHODS: One randomly selected eye of 198 consecutive ophthalmically normal subjects (104 men, 94 women) between July 2008 and January 2009, with corrected visual acuities better than 20/30 were included in this cross-sectional study. Complete ophthalmic examination, axial length measurement with a laser interferometer, and macular cube 512 x 128 scan by SD-OCT were performed. RESULTS: The mean age was 55.6 +/- 16.4 years (range, 17-83), average refractive error was -2.17 +/- 4.82 (range, -23.50-3.75), and average axial length was 24.73 +/- 1.98 mm (range, 21.52-32.51). The central subfield thickness, average inner macular thickness, and overall macular volume were significantly lower in the female subjects (partial correlation: P = 0.009, P = 0.027, and P = 0.042, respectively). As age increased, average inner macular thickness, average outer macular thickness, overall average macular thickness, and macular volume decreased significantly (partial correlation: P = 0.002, P = 0.002, P = 0.002, and P = 0.000, respectively). Refractive error had no significant influence in partial correlation analysis. Axial length correlated negatively with average outer macular thickness, overall average macular thickness, and macular volume (partial correlation: P = 0.006, P = 0.044, and P = 0.003, respectively). CONCLUSIONS: In normal subjects, SD-OCT showed that retinal thickness is related to age, sex, and axial length, with regional variationsope

    Structure-function relationship and diagnostic value of macular ganglion cell complex measurement using Fourier-domain OCT in glaucoma.

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    PURPOSE: To assess the relationship between visual function and macular ganglion cell complex (GCC) thickness measured by Fourier-domain optical coherence tomography (OCT) and to evaluate the diagnostic value of GCC thickness for detecting early, moderate, and severe glaucoma. METHODS: Participants underwent reliable standard automated perimetry testing and OCT imaging with optic nerve head (ONH) mode and GCC mode within a single day. The relationship between structure and function was evaluated by comparing GCC thickness with mean deviation (MD) and visual field index (VFI), by regression analysis. The results were compared with those obtained for retinal nerve fiber layer (RNFL) thickness. The area under the receiver operating characteristic curve (AUC) was used to determine the relationship between disease severity and glaucomatous changes in RNFL and GCC parameters. RESULTS: One hundred three normal control subjects and 138 patients with glaucoma were included in the present study. Compared with linear models, second-order polynomial models better described the relationships between GCC thickness and MD (P<0.001), and between GCC thickness and VFI (P<0.001). A GCC pattern parameter, global loss volume (GLV), had the highest AUC for detecting early glaucoma. The AUC of mean GCC thickness for early glaucoma was higher than that of mean RNFL; however, the difference was not significant (P=0.330). CONCLUSIONS: A curvilinear function best described the relationship between VF sensitivity and GCC thickness. Macular GCC thickness and RNFL thickness showed similar diagnostic performance for detecting early, moderate, and severe glaucoma.ope

    Determinants of perimacular inner retinal layer thickness in normal eyes measured by Fourier-domain optical coherence tomography.

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    PURPOSE: To determine the effects of age, sex, spherical equivalent, axial length, anterior chamber depth, optic disc area, and central corneal thickness on perimacular inner retinal layer thickness in the normal human eye as measured by Fourier-domain optical coherence tomography (FD-OCT). METHODS: In this cross-sectional observational study, 182 Korean healthy subjects aged from 22 to 84 years were included. To obtain the inner retinal layer thickness, perimacular ganglion cell complex thickness, which extends from the internal limiting membrane to the inner nuclear layer, was measured by FD-OCT on one randomly selected eye of each subject. Linear regression analyses of the effects of demographic and clinical variables, including age, sex, spherical equivalent, axial length, anterior chamber depth, optic disc area, and central corneal thickness, on perimacular inner retinal layer thickness were performed. RESULTS: The mean inner retinal layer thickness for the entire population was 93.87 ฮผm. Thinner inner retinal layer measurements were associated with older age (P = 0.010) and greater axial length (P = 0.021). Mean inner retinal layer thickness decreased by approximately 1.59 ฮผm for every decade of age and by approximately 1.56 ฮผm for every 1-mm greater axial length. There was no relationship between inner retinal layer thickness and sex, anterior chamber depth, optic disc area, or central corneal thickness. CONCLUSIONS: Inner retinal layer thickness, as measured by FD-OCT, varies significantly with age and axial length. The effect is small but clinically relevant in the interpretation of inner retinal layer thickness measurements.ope

    [๊ธ€์“ฐ๊ธฐ ์ƒ๋‹ด์‹ค์—์„œ]์ด๊ณต๊ณ„ ํ•™์ƒ๋“ค์˜ ๊ธ€์“ฐ๊ธฐ

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    ๊ธ€์“ฐ๊ธฐ๊ต์‹ค์—์„œ ์ด๊ณต๊ณ„ ํ•™์ƒ์˜ ๋ฆฌํฌํŠธ๋ฅผ ์ƒ๋‹ดํ•˜๋Š” ๊ฒฝ์šฐ๋Š” ๊ทธ๋ฆฌ ๋งŽ์ง€ ์•Š๋‹ค. ๊ทธ๋‚˜๋งˆ ์ด๊ณต๊ณ„ ํ•™์ƒ๋“ค์ด ๋ฆฌํฌํŠธ ์ƒ๋‹ด์„ ์œ„ํ•ด ๊ธ€์“ฐ๊ธฐ๊ต์‹ค์„ ์ฐพ์„ ๋•Œ๋Š” ๊ทธ ๋ฆฌํฌํŠธ์˜ ์ˆ˜์—…์ด ํ•ต์‹ฌ๊ต์–‘ ์ˆ˜์—…์ธ ๊ฒฝ์šฐ๊ฐ€ ๋Œ€๋ถ€๋ถ„์ด๊ณ , ์ž์‹ ์˜ ์ „๊ณต ์ˆ˜์—… ๋ฆฌํฌํŠธ ๋•Œ๋ฌธ์— ์ƒ๋‹ด์„ ์ฒญํ•˜๋Š” ๊ฒฝ์šฐ๋Š” ๊ทนํžˆ ๋“œ๋ฌผ๋‹ค. 2003๋…„ 2ํ•™๊ธฐ ์ด๋ฃจ์–ด์ง„ ๋ชจ๋“  ๋ฆฌํฌํŠธ ์ƒ๋‹ด ์ค‘ ์ž์—ฐ ๊ณ„์—ด ์ˆ˜์—…์˜ ๋ฆฌํฌํŠธ๊ฐ€ ์‹ ์ฒญ๋œ ๊ฒฝ์šฐ๋Š” ์ „์ณฌ 265๊ฑด ์ค‘ 9๊ฑด์— ๋ถˆ๊ณผํ–ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ถˆ๊ท ํ˜•์ด ์–ด๋””์„œ๋ถ€ํ„ฐ ์‹œ์ž‘๋˜๋Š” ๊ฒƒ์ผ๊นŒ. ์ด๊ณต๊ณ„ ํ•™์ƒ๋“ค์ด ๊ธ€์“ฐ๊ธฐ๋ฅผ ์‹ซ์–ดํ•œ๋‹ค๊ฑฐ๋‚˜ ๊ทธ ๋™์•ˆ์˜ ๊ธ€์“ฐ๊ธฐ ์—ฐ์Šต์ด ๋ถ€์กฑํ–ˆ๋‹ค๊ณ  ์ƒ๊ฐํ•  ์ˆ˜๋„ ์žˆ๊ฒ ์ง€๋งŒ, ์ด๋Ÿญ ์‹์˜ ํ•ด์„์€ ์‚ฌ์‹ค ๋ชจ๋“  ํ•™์ƒ์—๊ฒŒ ์ ์šฉ๋  ์ˆ˜ ์žˆ๋Š” ์ธก๋ฉด์ด ์žˆ๋‹ค. ๊ธ€์„ ์“ฐ๋Š” ๊ฒƒ์„ ๋ถ€๋‹ด์Šค๋Ÿฌ์›Œํ•˜๊ณ  ์ž์‹ ์˜ ๋ฆฌํฌํŠธ๋ฅผ ์ƒ๋‹ด ๋ฐ›๋Š” ๊ฒƒ์„ ๋ถ€๋‹ด์Šค๋Ÿฌ์›Œํ•˜๋Š” ๊ฒƒ์€ ๋‹ค ๋งˆ์ฐฌ๊ฐ€์ง€๋ผ๋Š” ์–˜๊ธฐ๋‹ค. ๋ฆฌํฌํŠธ ์ƒ๋‹ด์„ ๊ธฐํ”ผํ•˜๋Š” ์ด์œ ๋ฅผ ํ•™์ƒ๋“ค์—๊ฒŒ์„œ ์ฐพ์„ ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ํ•™์ƒ๋“ค์„ ๋Œ๋Ÿฌ์‹ผ ๊ตฌ์ €์  ์ธก๋ฉด์—์„œ ๋ฐ”๋ผ๋ณด์•„์•ผ ํ•˜๋Š” ๊นŒ๋‹ญ์ด ์—ฌ๊ธฐ์— ์žˆ๋‹ค

    ๋ฌผ ๋ฏผ๊ฐ์„ฑ ๊ทธ๋ฆฐ์ธํ”„๋ผ์ŠคํŠธ๋Ÿญ์ฒ˜ ๊ณ„ํš์„ ์œ„ํ•œ ์ ์ง€๋ชจํ˜• ๊ฐœ๋ฐœ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ํ™˜๊ฒฝ๋Œ€ํ•™์› : ํ˜‘๋™๊ณผ์ • ์กฐ๊ฒฝํ•™์ „๊ณต, 2015. 8. ์„ฑ์ข…์ƒ.์ง€์†๊ฐ€๋Šฅ์„ฑ์„ ๊ณ ๋ คํ•˜์ง€ ์•Š์€ ์ฑ„ ๊ฐœ๋ฐœ์ด ์™„๋ฃŒ๋œ ๋„์‹œ์˜ ํ™˜๊ฒฝ์  ๋ฌธ์ œ๋Š” ์˜ค๋ž˜๋œ ์ด์Šˆ์ด๋‹ค. ๋„์‹œ์˜ ์ƒํƒœ์  ๊ธฐ๋ŠฅํšŒ๋ณต๊ณผ ์ƒํƒœ์„ฑ ํ™•๋ณด๊ฐ€ ๋ฌธ์ œ ํ•ด๊ฒฐ์˜ ๋Œ€์•ˆ์ž„์„ ๋งŽ์€ ์—ฐ๊ตฌ์—์„œ ์ œ์‹œํ•˜๊ณ  ์žˆ๊ณ , ์‹ค์ฒœ์— ์˜ฎ๊ธฐ๋Š” ๋„์‹œ ๋˜ํ•œ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฐ ๋งฅ๋ฝ์—์„œ ๋„์‹œ ์ƒํƒœ์„ฑ์— ๊ด€ํ•œ ๋‹ค์–‘ํ•œ ๊ธฐ์ˆ ์  ์šฉ์–ด๋“ค์ด ์ œ์‹œ๋˜๊ณ  ์žˆ๋‹ค. ๊ทธ ์ค‘ ๊ทธ๋ฆฐ์ธํ”„๋ผ์ŠคํŠธ๋Ÿญ์ฒ˜(GI)๋Š” ์‹ค์ฒœ์„ฑ๊ณผ ์„ ์–ธ์  ๊ฐœ๋…์„ ๋ชจ๋‘ ํฌ๊ด„ํ•˜๋Š” ์šฉ์–ด๋กœ์„œ ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋„์‹œ์˜ ํ™˜๊ฒฝ์  ๋ฌธ์ œ ์ค‘ ๋ฌผ ์ˆœํ™˜๋ฌธ์ œ์— ์ดˆ์ ์„ ๋‘์—ˆ์œผ๋ฉฐ, ํ•ด๊ฒฐ ๋Œ€์•ˆ์œผ๋กœ์„œ ๋„์‹œ ๋ฌผ ๋ฏผ๊ฐ์„ฑ์˜ ํšŒ๋ณต๊ณผ ๊ธฐ์ˆ ์  ์ ‘๊ทผ์œผ๋กœ์„œ GI์— ์ฃผ๋ชฉํ–ˆ๋‹ค. ๋ฌผ ๋ฏผ๊ฐ์„ฑ์ด ๋‚ฎ์„์ˆ˜๋ก ๋„์‹œ์˜ ์ž์—ฐ์  ๋ฌผ ์ˆœํ™˜ ๋Šฅ๋ ฅ์€ ๋–จ์–ด์ง€๊ณ , ๋…น์ง€์˜ ์งˆ๊ณผ ์ง‘์ค‘ํ˜ธ์šฐ์— ์˜ํ•œ ์นจ์ˆ˜ํ”ผํ•ด์˜ ์œ„ํ—˜์„ฑ ๋˜ํ•œ ๋†’์•„์ง„๋‹ค. ์ด๋Š” ํ† ์–‘์„ ํ†ตํ•ด ์ง€ํ•˜์ˆ˜์™€ ์‹๋ฌผ์„ ๊ฑฐ์ณ ์ฆ๋ฐœ์‚ฐ ๋˜๋Š” ๊ณผ์ •์ด ์ฝ˜ํฌ๋ฆฌํŠธ์™€ ์•„์ŠคํŒ”ํŠธ ๋“ฑ ๋ถˆํˆฌ์ˆ˜ ํฌ์žฅ๋ฉด์— ์˜ํ•ด ์ฐจ๋‹จ๋œ ๊ฒƒ์ด ์ฃผ์š”ํ•œ ์›์ธ์ด๋‹ค. ์ด ๋ฌธ์ œ๋ฅผ ๊ธฐ์ˆ ์ ์œผ๋กœ ํ•ด๊ฒฐํ•˜๋ฉด ๋„์‹œ์—์„œ ๋ฌผ ์ˆœํ™˜์ด ์›ํ™œํžˆ ์ด๋ฃจ์–ด์ง€๋Š” ๋ฌผ ๋ฏผ๊ฐ์„ฑ์„ ํšŒ๋ณต์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ๊ธฐ์ˆ ์ ์œผ๋กœ GI๋Š” ๋„์‹œ ๋ฌผ ์ˆœํ™˜์„ฑ ํšŒ๋ณต์„ ์œ„ํ•œ ๊ธฐ๋Šฅ์„ ๋‹ด๊ณ  ์žˆ๋‹ค. GI๋Š” ํ˜•ํƒœ์ ์œผ๋กœ ๋„์‹œ์˜ ์ง€์†๊ฐ€๋Šฅ์„ฑ์„ ์œ„ํ•ด ๋…น์ง€์˜ ์—ฐ๊ฒฐ๋ง์„ ๊ฐ–์ถ”๋„๋ก ํ•˜๋ฉฐ, ๋…น์ง€์˜ ๊ธฐ๋Šฅ์  ์—ฐ๊ฒฐ์„ฑ์„ ํฌํ•จํ•œ๋‹ค. ์ด๋ฏธ ์„ ์ง„๊ตญ์€ ๊ธฐ์ƒ์ด๋ณ€ ๋˜๋Š” ๊ธฐํ›„๋ณ€ํ™”์— ๊ด€ํ•œ ์ „๋žต์œผ๋กœ ๊ฐ์ข… ๊ณต๊ฐ„๊ณ„ํš์— GI๋ฅผ ์ ์šฉ, ์ œ๋„์ , ๊ธฐ์ˆ ์ ์œผ๋กœ ๊ตฌํ˜„ํ•˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ, ๋ฌผ ๋ฏผ๊ฐ์„ฑ ํšŒ๋ณต๊ณผ ๋ฌผ ์ˆœํ™˜ ํ™˜๊ฒฝ๊ฐœ์„ ์„ ์œ„ํ•œ ๊ณต๊ฐ„์  ๋Œ€์ƒ์— ๋Œ€ํ•œ ํŒ๋ณ„๋ฐฉ๋ฒ•๋ก ์ด ์ฒด๊ณ„ํ™” ๋˜์–ด ์žˆ์ง€ ๋ชปํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋ฅผ ๊ณ ๋ คํ•˜์—ฌ, ๊ธฐ์„ฑ์‹œ๊ฐ€์ง€์—์„œ ๋†’์€ ๋ฌผ ์ˆœํ™˜์„ฑ์„ ๊ฐ€์ ธ์˜ฌ ์ˆ˜ ์žˆ๋Š” ์ตœ์ ์˜ GI ์ ์šฉ ์žฅ์†Œ๋ฅผ ํŒ๋ณ„ํ•˜๋Š”๋ฐ ์ฃผ๋ชฉํ–ˆ๋‹ค. ํŠนํžˆ ๋ฌผ ์ˆœํ™˜์„ฑ ๋‹จ์ ˆ์ด ์›์ธ์œผ๋กœ ์ง€๋ชฉ๋˜๊ณ  ์žˆ์œผ๋ฉฐ, ๋„์‹ฌ์—์„œ ์ฆ๊ฐ€ ์ถ”์„ธ์ธ ์ง€ํ‘œ์ˆ˜ ์นจ์ˆ˜ํ˜„์ƒ์„ ์—ฐ๊ตฌ๋Œ€์ƒ์œผ๋กœ ์ •ํ–ˆ๋‹ค. ์ง€ํ‘œ์ˆ˜ ์นจ์ˆ˜์˜ ์›์ธ์€ ์ง‘์ค‘ํ˜ธ์šฐ์— ๋”ฐ๋ฅธ ๊ฐ•์šฐ์œ ์ถœ์ˆ˜์˜ ๊ณผ๋‹คํ•œ ์ง€ํ‘œ๋ฉด ๋ˆ„์ ์ด๋‹ค. ์ด ์นจ์ˆ˜ ์œ„ํ—˜์„ฑ์„ ์ €๊ฐ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ์šฐ์„ ์ ์œผ๋กœ ๊ฐ•์šฐ์œ ์ถœ์ˆ˜ ๋ฐœ์ƒ์„ ์ง€ํ‘œ๋ฉด์—์„œ ์ œ์–ดํ•˜๊ธฐ ์œ„ํ•œ ๊ณต๊ฐ„ํ™•๋ณด๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด ๊ณต๊ฐ„์— ๋Œ€ํ•œ ๊ณต๊ฐ„์  ํŠน์„ฑ์„ ์ „์‚ฐํ™”ํ•˜์—ฌ ์ ์ง€๋ฅผ ํŒ๋ณ„ ํ•  ์ˆ˜ ์žˆ๋Š” GIS ๊ธฐ๋ฐ˜ ๋ชจํ˜•์„ ๊ฐœ๋ฐœํ–ˆ๋‹ค. ์ด ๋ชจํ˜•์€ ๊ณต๊ฐ„๋ณ€์ˆ˜๋ฅผ ์ •๋Ÿ‰์ ์œผ๋กœ ํ™œ์šฉํ•ด ๋„๋ฉดํ™” ๋œ ์ž๋ฃŒ๋ฅผ ์ž‘์„ฑํ•˜๋„๋ก ์„ค๊ณ„๋๋‹ค. ๋ชจํ˜•์— ์‚ฌ์šฉ๋œ ๊ณต๊ฐ„๋ณ€์ˆ˜๋Š” ๊ฐ•์šฐ์œ ์ถœ์ˆ˜์˜ ํ๋ฆ„๊ณผ ํ† ์–‘์˜ ์ˆ˜๋ฌธํ•™์  ํŠน์„ฑ, ํ† ์ง€ํ”ผ๋ณต์ƒํƒœ๋‹ค. ์ด ์ค‘ ๊ฐ•์šฐ์œ ์ถœ์ˆ˜์˜ ํ๋ฆ„์€ GI ์ ์šฉ์ง€์ ์„ ์ฐพ๋Š”๋ฐ ์ค‘์ถ”์  ์—ญํ• ์„ ํ•œ๋‹ค. ํŠนํžˆ ๊ฐ•์šฐ์œ ์ถœ์ˆ˜์˜ ํ๋ฆ„์€ ์ง€ํ˜•์— ์˜ํ–ฅ์„ ๋ฐ›๊ธฐ ๋•Œ๋ฌธ์— ์ •๋ฐ€ํ•œ ๋„์‹œ์ง€ํ˜•์„ ๊ตฌ์„ฑํ•  ์ˆ˜ ์žˆ๋Š” ๊ณผ์ •์ด ๋ชจํ˜•์— ํฌํ•จ๋ผ ์žˆ๋‹ค. ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์„ธ ๊ฐ€์ง€ ์ด๋ฉฐ, ๊ฐ ์—ฐ๊ตฌ๋ชฉ์ ์— ๋”ฐ๋ฅธ ๊ฒฐ๊ณผ๋Š” ์•„๋ž˜์™€ ๊ฐ™๋‹ค. ์ฒซ์งธ ๋ชฉ์ ์€ ๊ฐ•์šฐ์œ ์ถœ์ˆ˜์˜ ๊ณต๊ฐ„์  ๋ถ„ํฌ๋ฅผ ์‹ค์ œ์— ๊ฐ€๊น๊ฒŒ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•œ ๊ฐ€์ƒ์ง€ํ˜• ๊ตฌ์ถ•๋ชจํ˜•์„ ๊ฐœ๋ฐœํ•˜๋Š” ๊ฒƒ์ด์—ˆ๋‹ค. ๋ชจํ˜•์„ ์œ„ํ•ด ArcGIS ๋ช…๋ น์–ด๋ฅผ ์ƒˆ๋กœ ์กฐํ•ฉํ•˜๊ณ  ๋ฐ์ดํ„ฐ ์ž…๋ ฅ๊ณผ์ •์„ ์ถ”๊ฐ€ํ•œ ํ”„๋กœ์„ธ์Šค๋ฅผ ๊ตฌ์„ฑํ–ˆ๋‹ค. ์ด ํ”„๋กœ์„ธ์Šค๋Š” ๊ฑด์ถ•๋ฌผ๊ณผ ๋„๋กœ์˜ ์œ„์น˜์ •๋ณด์™€ ๋“ฑ๊ณ ์„ ์— ์˜ํ•œ ๋†’์ด์ •๋ณด๋ฅผ ๊ฒฐํ•ฉํ•œ ๊ฒƒ์ด ํ•ต์‹ฌ์œผ๋กœ, ๊ฒฐ๊ณผ๋กœ ๋„์‹œ์— ํŠนํ™”๋œ ์ง€ํ˜•(SUDEM)์„ ๊ตฌํ˜„ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ๋ชฉ์ ์€ ๋„์‹œ ํŠนํ™” ์ง€ํ˜•์ •๋ณด์™€ ์ˆ˜๋ฌธ๋ถ„์„์„ ๊ฒฐํ•ฉํ•œ ๋ชจํ˜•์„ ํ†ตํ•ด ๋†’์€ ์ •๋ฐ€๋„์˜ ๊ฐ•์šฐ์œ ์ถœ์ˆ˜ ๊ด€๋ จ ์ˆ˜๋ฌธ์ •๋ณด๋ฅผ ๋„์ถœํ•˜๋Š” ๊ฒƒ์ด์—ˆ๋‹ค. SUDEM์„ ๊ณต๊ฐ„์ž…๋ ฅ๋ณ€์ˆ˜๋กœ ์‚ฌ์šฉํ•œ ArcGIS ์™€ ArcHydro์˜ ์ˆ˜๋ฌธ๋ถ„์„ ๊ณผ์ •์„ ์กฐํ•ฉํ–ˆ๊ณ , ๋„์‹œ์ง€ํ˜•์— ํŠนํ™”๋œ ์œ ์—ญ, ๊ฐ•์šฐ์œ ์ถœ์ˆ˜์˜ ํ๋ฆ„๋ถ„ํฌ, ์ตœ์žฅํ๋ฆ„์˜ ์œ„์น˜, ๋ฐฐ์ˆ˜์ง€์ ์„ ๊ฒฐ๊ณผ๊ฐ’์œผ๋กœ ์–ป์„ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ฐ๊ฐ์˜ ๊ฒฐ๊ณผ๋Š” ์ผ๋ฐ˜ DEM์„ ์‚ฌ์šฉํ•œ ๊ฒฐ๊ณผ ๋Œ€๋น„ ์ •๋ฐ€๋„๊ฐ€ ๋†’์•˜๊ณ  ๊ฒฐ๊ณผ๋„๋ฉด์˜ ๊ณต๊ฐ„์  ํŠน์„ฑ์ด ๋„์‹œ์˜ ๋ฌผ๋ฆฌ์  ๊ตฌ์กฐ๋ฅผ ๋ฐ˜์˜ํ•˜๊ณ  ์žˆ์—ˆ๋‹ค. ์„ธ ๋ฒˆ์งธ ๋ชฉ์ ์€ ๊ฐ•์šฐ์œ ์ถœ์ˆ˜ ์ˆ˜๋ฌธ์ •๋ณด, ์ˆ˜๋ฌธํ•™์  ํ† ์–‘ํŠน์„ฑ, ํ† ์ง€ํ”ผ๋ณต์ƒํƒœ๋ฅผ ํ™œ์šฉํ•ด GI ์ ์šฉ๋Œ€์ƒ์ง€์—ญ๊ณผ ์œ ํ˜• ํŒ๋ณ„ ๋ฐฉ๋ฒ•๋ก ์„ ์ œ์‹œํ•˜๋Š” ๊ฒƒ์ด์—ˆ๋‹ค. ์„ธ ์ข…๋ฅ˜์˜ ๊ณต๊ฐ„๋ณ€์ˆ˜๋ฅผ ๋ฌผ ๋ฏผ๊ฐ์„ฑ๊ณผ์˜ ํŠน์„ฑ๊ณผ ๊ด€๋ จ์‹œ์ผœ ์ฝ”๋“œํ™”ํ•˜๊ณ  ์ค‘์ฒฉํ•œ ๊ฒฐ๊ณผ๊ฐ€ ๋†’์„์ˆ˜๋ก ๋ฌผ ๋ฏผ๊ฐ์„ฑ์ด ๋–จ์–ด์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋ชจํ˜•์„ ์„ค๊ณ„ํ–ˆ๋‹ค. ๋ชจํ˜• ์ ์šฉ ๊ฒฐ๊ณผ 5๊ฐ€์ง€ ์œ ํ˜•์ด ๋„์ถœ๋๋Š”๋ฐ ๋ฌผ ๋ฏผ๊ฐ์„ฑ์ด ๊ฐ€์žฅ ๋†’์€ ์ง€์ ๊ณผ ๊ฐ€์žฅ ๋‚ฎ์€ ์ง€์ ์€ GI ์ ์ง€์—์„œ ์ œ์™ธํ•˜์˜€๋‹ค. ๊ทธ ์ด์œ ๋กœ์„œ ๋ฌผ ๋ฏผ๊ฐ์„ฑ์ด ๊ฐ€์žฅ ๋†’์€ ์ง€์ ์€ ์ง‘์ค‘ ํ˜ธ์šฐ์‹œ ์ง€ํ‘œ์ˆ˜ ์ˆ˜์šฉ๋Šฅ๋ ฅ์ด ํฐ ์ง€์—ญ์œผ๋กœ ํ˜„์žฌ ์ž์—ฐ์ƒํƒœ์ด๊ฑฐ๋‚˜ ์ž์—ฐ์ƒํƒœ์— ๊ฐ€๊นŒ์šด ๊ธฐ๋Šฅ์„ ํ•˜๊ณ  ์žˆ๋Š” ์ง€์—ญ์œผ๋กœ ๋„์ถœ๋˜์—ˆ์œผ๋ฉฐ, ๊ฐ€์žฅ ๋‚ฎ์€ ๋ฌผ ๋ฏผ๊ฐ์„ฑ์„ ๊ฐ–๋Š” ์ง€์—ญ์€ ๊ฐ•์šฐ์œ ์ถœ์ˆ˜ ๋ฐœ์ƒ์‹œ ์ง€ํ‘œ์ˆ˜ ์ˆ˜์šฉ๋Šฅ๋ ฅ์ด ๋ถ€์กฑํ•˜์—ฌ ๋ฐฐ์ˆ˜์‹œ์„ค์ด ํ•„์š”ํ•œ ๊ฐœ๋ฐœ์ง€์—ญ์œผ๋กœ ๋„์ถœ๋˜์—ˆ๋‹ค. ์ด ๋‘ ์œ ํ˜•์€ ํ˜„์žฌ์ƒํƒœ ์œ ์ง€ ๋˜๋Š” ๋ฐฐ์ˆ˜์‹œ์„ค์ด ํ•„์š”ํ•œ ์ง€์—ญ์œผ๋กœ์„œ GI์ ์šฉ ๋ฒ”์œ„๋ฅผ ๋ฒ—์–ด๋‚˜ ์žˆ์œผ๋ฏ€๋กœ ์ œ์™ธ GI ์ ์ง€์—์„œ ์ œ์™ธํ•˜์˜€๋‹ค. ๋‚˜๋จธ์ง€ 3๊ฐ€์ง€ ์œ ํ˜•์ด ์œ„์น˜ํ•œ ์ง€์ ์€ GI ์ ์ง€๋กœ ํŒ๋ณ„๋˜์—ˆ๋‹ค. ๋‚˜๋จธ์ง€ 3๊ฐ€์ง€ ์œ ํ˜•์€ GI์˜ ๊ธฐ๋Šฅ๋ณ„ ํŠน์„ฑ๊ณผ ๊ณต๊ฐ„ํŠน์„ฑ ๊ฐ„ ์ƒ๊ด€์„ฑ์— ๋”ฐ๋ผ ์นจํˆฌํ˜•, ์นจํˆฌ+์ €๋ฅ˜ํ˜•, ์นจํˆฌ+์ €๋ฅ˜+์›”๋ฅ˜ํ˜• ์œผ๋กœ ๊ตฌ๋ถ„๋ผ ๋„๋ฉด์ƒ์— ๊ทธ ๋ถ„ํฌ๊ฐ€ ํ‘œํ˜„๋˜์—ˆ๋‹ค. ๊ฐœ๋ฐœ๋œ GI ์ ์ง€ํŒ๋ณ„ ๋ชจํ˜•์„ ์‹ค์ œ ๋„์‹œ๊ณ„ํš์— ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ์•ˆ์„ ๊ณ ์ฐฐํ•˜์˜€๋‹ค. ์นจ์ˆ˜์ทจ์•ฝ์ง€์—ญ๊ณผ ์นจ์ˆ˜์ทจ์•ฝ์ง€์—ญ์ด ํฌํ•จ๋œ ์†Œ์œ ์—ญ์„ ์ง€๊ตฌ๋‹จ์œ„๊ณ„ํš ๋Œ€์ƒ์œผ๋กœ GI ํŒ๋ณ„๋ชจํ˜•์˜ ํ™œ์šฉ์„ฑ์„ ๊ฒ€์ฆํ–ˆ๋‹ค. ํ˜„์žฌ์˜ ์ง€๊ตฌ๋‹จ์œ„๊ณ„ํš ์ œ๋„์ƒ ํ˜„์‹ค์ ์šฉ์ด ๊ฐ€๋Šฅํ•˜๋‚˜, ํ˜„์žฌ ๋ฌผ ์ˆœํ™˜ ๊ด€๋ จ ํ•ญ๋ชฉ์ด ํ™˜๊ฒฝ์˜ค์—ผ๋ฐฉ์ง€ ํ•ญ๋ชฉ์— ํ•œ์ •๋˜์–ด ์žˆ๋Š” ์ œ๋„์  ํ•œ๊ณ„์ ์ด ์กด์žฌํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ, ํ˜„์žฌ ์ง€๊ตฌ๋‹จ์œ„๊ณ„ํš์ œ๋„๋Š” GI๋ฅผ ์ง์ ‘์  ๊ณ„ํš๋Œ€์ƒ์— ๊ณ ๋ คํ•˜๊ณ  ์žˆ์ง€ ์•Š์œผ๋ฏ€๋กœ GI๋ฅผ ํ™œ์šฉํ•œ ์นจ์ˆ˜์ทจ์•ฝ์ง€์—ญ ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•ด์„œ๋Š” ํ–ฅํ›„ ์ œ๋„์  ๊ฐœ์„ ์ด ํ•„์š”ํ•จ์„ ํ™•์ธํ–ˆ๋‹ค. ์นจ์ˆ˜์ทจ์•ฝ์ง€์—ญ์˜ ์ทจ์•ฝ์„ฑ์„ ์ €๊ฐํ•˜๊ธฐ ์œ„ํ•œ ๋ฐฉ๋ฒ•์œผ๋กœ ํ†ตํ•ฉ์œ ์—ญ๊ด€๋ฆฌ์˜ ๊ฐœ๋…๊ณผ GI ์ ์ง€ํŒ๋ณ„๋ชจํ˜•์„ ๊ฒฐํ•ฉํ•œ ๋ฐฉ๋ฒ•๋ก ์˜ ํ™œ์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ๊ฒ€ํ† ํ–ˆ๋‹ค. ๊ฒฐ๊ณผ์ ์œผ๋กœ ์นจ์ˆ˜์˜ ์›์ธ์„ ์ œ๊ณตํ•˜๋Š” ์ƒ๋ฅ˜์ง€์—ญ์˜ ๋ช…ํ™•ํ•œ ๊ณต๊ฐ„์  ๊ฒฝ๊ณ„๋ฅผ ํŒ๋ณ„ํ•  ์ˆ˜ ์žˆ๊ณ , ์นจ์ˆ˜ ์›์ธ์ œ๊ณต ์ง€์—ญ์„ ๋Œ€์ƒ์œผ๋กœ GI ์ ์ง€๋ฅผ ๊ตฌ๋ถ„ํ•  ์ˆ˜ ์žˆ์œผ๋ฏ€๋กœ ๋†’์€ ํšจ์œจ์„ฑ์„ ๊ฐ–์ถ˜ ๊ณ„ํš์„ ์ˆ˜๋ฆฝํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์‚ฌ๋ฃŒ๋๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” GI๋ฅผ ๊ธฐ์ˆ ์ ์œผ๋กœ ๋‹ค๋ฃฌ ์‹œ๋„์˜ ์ดˆ๊ธฐ ๊ฒฐ๊ณผ๋ผ ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฐ ์ธก๋ฉด์—์„œ ๋ณธ ์—ฐ๊ตฌ์˜ ์˜์˜๋Š” ๋„์‹œ์˜ ๋ฌผ๋ฆฌ์  ์ •๋ณด๋งŒ์„ ํ™œ์šฉํ•ด ํ˜„ํ™ฉ์— ๊ฐ€๊นŒ์šด ์ง€ํ‘œ์ˆ˜ ํ๋ฆ„์„ ๊ตฌํ˜„ํ•œ ๊ฒƒ๊ณผ ์ด๋ฅผ ๊ณต๊ฐ„ ์ •๋ณดํ™”ํ•˜์—ฌ ์ˆ˜๋ฌธํ•™์  ํ† ์–‘ํŠน์„ฑ, ์ง€ํ‘œ๋ฉด ํฌ์žฅํŠน์„ฑ์„ ๋ฐ˜์˜ํ•œ ๊ณต๊ฐ„์ •๋ณด์™€ ๊ฒฐํ•ฉํ•ด GI์˜ ์ ์ง€ ๋ฐ ์ ์šฉ์œ ํ˜•์— ๊ด€ํ•œ ๊ณต๊ฐ„์  ํŒ๋ณ„์ด ๊ฐ€๋Šฅํ•จ์„ ๋ฐํžŒ ๊ฒƒ์ด๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ ๋ชจํ˜•๊ฒฐ๊ณผ์˜ ํ™œ์šฉ์„ ์ค‘์‹ฌ์œผ๋กœ ๋ณธ ์—ฐ๊ตฌ์˜ ์˜์˜๋Š” 1) ํ†ตํ•ฉ์œ ์—ญ๊ด€๋ฆฌ์˜ ๊ฐœ๋…๊ณผ GI ์ ์ง€ํŒ๋ณ„ ๋ชจํ˜•์„ ๊ฒฐํ•ฉํ•˜๋ฉด ์นจ์ˆ˜์ทจ์•ฝ์ง€์—ญ์— ์ง์ ‘์  ์˜ํ–ฅ์„ ์ฃผ๋Š” ๊ณต๊ฐ„์  ๋ฒ”์œ„์™€ ํŠน์„ฑ์„ ๋™์‹œ์— ์ฐพ์„ ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ–ˆ๋‹ค. 2) ๋ชจํ˜•์„ ํ†ตํ•ด GI๊ฐ€ ํšจ๊ณผ์ ์œผ๋กœ ๊ธฐ๋Šฅํ•  ์ˆ˜ ์žˆ๋Š” ๊ณต๊ฐ„์  ๋ฒ”์œ„์™€ ์œ„์น˜๋ฅผ ํŒ์ •ํ•  ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ–ˆ๋‹ค. 3) ๋„์‹œ๊ณ„ํš์„ ํ†ตํ•œ ์ œ๋„์  ์‹คํ˜„๊ฐ€๋Šฅ์„ฑ ์ค‘ ํ˜„์žฌ ์ง€๊ตฌ๋‹จ์œ„๊ณ„ํš์— ์ ์šฉ ๊ฐ€๋Šฅํ•˜๋‹ค. ๋‹ค๋งŒ, ๊ณ„ํš์  ์ง€ํ‘œ๊ฐ€ GI์— ์ดˆ์ ์„ ๋‘๊ณ  ์žˆ์ง€ ์•Š๋Š” ํ•œ๊ณ„์ ์ด ์กด์žฌํ•จ์„ ํ™•์ธํ–ˆ๋‹ค๋Š” ์ ์ด๋‹ค. ๋ณธ ๋ชจํ˜•์€ ๋ฌผ๋ฆฌ์  ๊ณต๊ฐ„์ •๋ณด ๋งŒ์„ ์ž…๋ ฅ๋ณ€์ˆ˜๋กœ ์‚ฌ์šฉํ•˜์—ฌ ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœํ•˜๊ฒŒ ๋˜๋ฏ€๋กœ GI ์ ์šฉ์— ๋”ฐ๋ฅธ ๋„์‹œ์‚ฌํšŒํ•™์  ๋ณ€ํ™”์— ๋Œ€ํ•ด ๋Œ€์‘ํ•˜๊ธฐ ์–ด๋ ต๋‹ค. ๋˜ ๊ฐ•์šฐ์œ ์ถœ์ˆ˜์˜ ์ •ํ™•ํ•œ ๋ณ€ํ™”๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ์„ ํ–‰์—ฐ๊ตฌ์˜ ์‹คํ—˜๊ฒฐ๊ณผ๋ฅผ ์‚ฌ์šฉํ–ˆ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์กด์žฌํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ํ–ฅํ›„์—ฐ๊ตฌ๋กœ์„œ GI ๋„์ž…์— ๋”ฐ๋ฅธ ํšจ๊ณผ๊ฒ€์ฆ์„ ์ฃผ์ œ๋กœ GI์˜ ์ธ๋ฌธ-์‚ฌํšŒ์  ๋ฐ์ดํ„ฐ๋ฅผ GI ์ ์ง€ํŒ๋ณ„๋ชจํ˜•์˜ ํŒ๋‹จ๊ธฐ์ค€์œผ๋กœ ์ถ”๊ฐ€ํ•œ๋‹ค๋ฉด, ์ด์šฉ์ž์˜ GI์˜ ์นจ์ˆ˜์ €๊ฐ ํšจ๊ณผ์— ๊ด€ํ•œ ์ธ์‹๋ณ€ํ™” ๋“ฑ์˜ ์ถ”๊ฐ€์ ์ธ ์—ฐ๊ตฌ๊ฐ€ ๊ฐ€๋Šฅํ•  ๊ฒƒ์ด๋‹ค. ๋˜ํ•œ GI ์ ์ง€ํŒ๋ณ„ ๋ชจํ˜•๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ง€๊ตฌ๋‹จ์œ„๊ณ„ํš ๋ฐ ๋„์‹œ๊ธฐ๋ณธ๊ณ„ํš์—์„œ ์นจ์ˆ˜์ทจ์•ฝ์ง€์—ญ์— ๊ด€ํ•œ ์ธ์„ผํ‹ฐ๋ธŒ, ๊ทœ์ œ ๋“ฑ์˜ ๊ธฐ์ค€๊ณผ GI์— ๊ด€ํ•œ ์ฃผ๋ฏผ์ธ์‹์„ ํ™œ์šฉ ๊ฐ€๋Šฅํ•œ ๊ณ„ํš ์ž๋ฃŒ๋กœ ๋งˆ๋ จํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ๋ณด๋‹ค ๊ตฌ์ฒด์ ์ธ ๊ธฐ์ค€ ๋งˆ๋ จ์„ ์œ„ํ•ด ํ•ด๋‹น ์ง€์—ญ์„ ๋Œ€์ƒ์œผ๋กœ ๊ฐ•์šฐ์œ ์ถœ๋Ÿ‰ ์ €๊ฐํšจ๊ณผ๋ฅผ ๊ฒ€์ฆํ•˜๋Š” ์—ฐ๊ตฌ๊ฐ€ ์ถ”๊ฐ€์ ์œผ๋กœ ํ•„์š”ํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” GI ์‹คํ˜„์„ ์œ„ํ•œ ์ดˆ๊ธฐ ์—ฐ๊ตฌ๋‹ค. ์ดˆ๊ธฐ ์—ฐ๊ตฌ๋กœ์„œ ๋ณธ ์—ฐ๊ตฌ์˜ ํ•ต์‹ฌ์€ ๋„์‹œ์˜ ๋ฌผ ๋ฏผ๊ฐ์„ฑ์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ๊ณต๊ฐ„๋ณ€์ˆ˜ ๋งŒ์„ ํ™œ์šฉํ•˜์—ฌ GIS๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ GI์˜ ์œ ํ˜•๋ณ„ ์ ํ•ฉ์ง€๋ฅผ ํŒ๋ณ„ํ•˜๋Š” ๋…ผ๋ฆฌ์ฒด๊ณ„๋ฅผ ๊ตฌ์ถ•ํ•œ ๊ฒƒ์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ชจํ˜•์ด ์‘์šฉ ๊ฐ€๋Šฅํ•œ ํ”Œ๋žซํผ์œผ๋กœ์„œ ์ž‘๋™๊ฐ€๋Šฅํ•œ๊ฐ€์— ๋Œ€ํ•ด ์šด์šฉ๋Šฅ๋ ฅ์„ ๊ฒ€์ฆํ•˜๋Š” ์—ฐ๊ตฌ๋‹จ๊ณ„๋ผ ํ•  ์ˆ˜ ์žˆ๋‹ค. ์šด์šฉ์„ฑ์„ ์‚ดํŽด๋ณด๊ณ  ๊ฒฐ๊ณผ์˜ ์œ ์˜์„ฑ์„ ๊ตฌ์ฒด์ ์œผ๋กœ ๊ณ ์ฐฐํ•˜๊ธฐ ์œ„ํ•ด GI ์ ์ง€ํŒ๋ณ„์„ ์œ„ํ•œ ๋ณ€์ˆ˜๋ฅผ 3๊ฐ€์ง€๋กœ ์ œํ•œํ–ˆ๊ณ , ๊ณต๊ฐ„์  ํ•ด์ƒ๋„๋ฅผ 5mร—5m๋กœ ๊ทœ์ •ํ–ˆ๋‹ค. ๋ณธ ๋ชจํ˜•์˜ ๋…ผ๋ฆฌ์ฒด๊ณ„๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ž…๋ ฅ๋ณ€์ˆ˜๋Š” ํ–ฅํ›„ ์—ฐ๊ตฌ์— ์˜ํ•ด ์ถฉ๋ถ„ํžˆ ๋ณด์™„ ๋˜๋Š” ๋Œ€์ฒด๋˜์–ด ์‚ฌ์šฉ๊ฐ€๋Šฅํ•˜๋‹ค. ํ˜„์žฌ ์‚ฌ์šฉํ•œ ์„ธ ๊ฐ€์ง€ ๊ณต๊ฐ„ ๋ณ€์ˆ˜๊ตฐ์€ ๊ธฐ๋ณธ์  ํ‹€ ์ฐจ์›์—์„œ ์œ ์ง€ํ•˜๋˜, ์„ธ๋ถ€๋ณ€์ˆ˜์˜ ๊ฐœ์ˆ˜ ๋ฐ ์ฝ”๋“œํ™”์— ๊ด€ํ•œ ์ž์œ ๋„๋Š” ์—ด๋ ค์žˆ๋‹ค. ํ•ด์ƒ๋„ ๋˜ํ•œ ๋ถ„์„ ๋Œ€์ƒ์ง€์—ญ์˜ ๊ณต๊ฐ„์  ๋ฒ”์œ„์— ๋”ฐ๋ผ ์—ฐ๊ตฌ์ž์˜ ์˜๋„์— ๋”ฐ๋ผ ์ถฉ๋ถ„ํžˆ ์กฐ์ ˆ ๊ฐ€๋Šฅํ•˜๋‹ค. ๋”ฐ๋ผ์„œ ํ–ฅํ›„ ๊ธฐ์ˆ ์  ๋ณด์™„์„ ํ†ตํ•ด ์ •๋ฐ€์„ฑ์„ ๋†’์ผ ์ˆ˜ ์žˆ๋Š” ๋ณ€์ˆ˜๋กœ ํ˜„์žฌ์˜ ๋ณ€์ˆ˜๋ฅผ ๋ณด์™„ ๋˜๋Š” ๋Œ€์ฒดํ•  ์ˆ˜ ์žˆ๊ณ , ๊ณต๊ฐ„์ ํ•ด์ƒ๋„๋„ ๋”์šฑ ์„ธ๋ฐ€ํ•˜๊ฒŒ ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์ „๋งํ•œ๋‹ค. ์•ž์œผ๋กœ ํ•œ๊ตญ์€ ๊ธฐํ›„๋ณ€ํ™” ๊ด€๋ จ ํ˜„์ƒ์„ ๋‹ค๋ฃจ๊ธฐ ์œ„ํ•œ ๊ณ„ํš์  ์ ‘๊ทผ์ด ํ•„์š”ํ•  ๊ฒƒ์ด๋‹ค. ๊ด€๋ จํ˜„์ƒ์œผ๋กœ ์ง‘์ค‘ํ˜ธ์šฐ์— ์˜ํ•œ ์นจ์ˆ˜๋Š” ์›์ธ์ง€์—ญ๊ณผ ํ”ผํ•ด์ง€์—ญ์„ ํ†ตํ•ฉ์ ์œผ๋กœ ๊ณ ๋ คํ•ด์•ผ ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๋„์‹œ๊ณ„ํš ์ฐจ์›์˜ ๊ณต๊ณต์  ๊ด€๋ฆฌ์™€ ์ด๋ฅผ ์œ„ํ•œ ๊ณผํ•™์ ์ธ ๊ทผ๊ฑฐ๊ฐ€ ํ•„์š”ํ•  ๊ฒƒ์ด๋‹ค. ๋‹จ์ง€๊ทœ๋ชจ์—์„œ๋ถ€ํ„ฐ ๊ด‘์—ญ์ ์ธ ๊ทœ๋ชจ๋ฅผ ํ•œ ๋ฒˆ์— ๋‹ค๋ฃฐ ์ˆ˜ ์žˆ๋Š” ๋ณธ ๋ชจํ˜•์€ ์•ž์œผ๋กœ ๋„์‹œ๊ณ„ํš ์ˆ˜๋ฆฝ์— ์œ ์šฉ ํ•œ ์ž๋ฃŒ๋ฅผ ์ œ๊ณตํ•  ๊ฒƒ์ด๋‹ค.The environmental problem of urban areas where the development process has completed without considering their sustainability has long been an issue. Many research and studies suggested that restoring ecological functions and securing ecological values of cities is an alternative solution. A growing number of cities are trying to adopt the suggestion in practice. In this context, many technical terms about urban ecology have been presented. Among them, green infrastructure(GI) has attracted attention as a terminology which includes both practical and proclamatory values. This research focused on urban water sensitivity. A city with lower water sensitivity has a poorer capacity of natural water cycle, with a higher risk of flooding due to poor quality green areas and intensive rainfall. The water cycle where water comes from rain, infiltrates into the soil, flows underground and evaporates through plants is disrupted by impervious covers such as concrete and asphalt, which are the main key figures of lower water sensitivity. GI has functions to restore urban water cycle. GI has a network form connecting green areas, including areas which provide the functions of green areas, for urban sustainability. Advanced countries have already been applying GI to their spatial planning strategically to be prepared for abnormal weather patterns and climate change. They have achieved GI technically and institutionally. Considering this, this research has focused on identifying optimal spaces for GI application which can enhance water cycle in existing cities. Importantly, surface water flooding was chosen as the main subject, which occurs more frequently in urban areas. Since surface water flooding is caused by excessive stormwater runoff resulting from intensive heavy rain, the runoff needs to be controlled to mitigate the risk of flooding This research has developed a GIS-based model for identifying GI suitable areas, which has its focus on the issue above mentioned. The model was designed to use spatial data quantitatively and generate a map. The spatial variables used for the model are: stormwater runoff flows, hydrologic characteristics of the soil and land cover conditions, among which stormwater runoff flow plays a pivotal role in finding spots for GI application. In particular, it is affected by the terrain shape. Therefore, a process which can generate a precise urban topography was also included in the model. This research had three aims. The results for each aim are as follows: The first aim was to develop a model which generates a virtual terrain to understand the spatial distribution of stormwater runoff as close as possible to the real one. To make the model, Arc GIS commands were newly combined and a process where a data input phase was added was formed. The core of the process was combining location data of buildings and roads with height data of contour lines. As a result, specific urban DEM (SUDEM), was made. The second aim was to get precise hydrologic data on stormwater runoff by using a model which combines urban specific topographic data with hydrology analysis. Hydrologic analysis processes of ArcGIS and ArcHydro which uses SUDEM as spatial input variables were combined. Urban specific watersheds, rainfall runoff flow distribution, longest flow location, and drainage points were obtained as result values. All results show a higher precision degree compared to general DEM results. The spatial features of the results reflected the physical structure of cities. The third aim was to propose a methodology for identifying GI suitable area and GI types by using hydrologic data on rainfall runoff, hydrologic soil properties and land cover conditions. The three types of spatial variables were coded in relation with water sensitivity. The model was designed to show lower water sensitivity when the result value of overlaying variables was higher. Five types were created as a result of applying the model. The two types with highest or lowest water sensitivity were excluded from GI suitable areas. The area of the rest three types'Infiltration type', 'Infiltration + detention type' and 'Infiltration + detention + overflow type' were identified as GI suitable areas by maps. In addition, the research studied ways to use the model in practice. The usability of the GI suitable model for district-unit plans was verified, with flooding vulnerable areas being subject to district-unit plans. It was confirmed that GI can be applied to district areas under the current system of district-unit plan. Yet, it needs to be considered that GI was not directly subject to the plan. As a way of mitigating the vulnerability of the flooding areas, this research reviewed the concept that combines integrated watershed management with the GI suitable identification model. A clear spatial boundary of the upstream area where flooding originates from as well as GI suitable areas in the area could be identified. Therefore, it is expected that this concept will improve the effectiveness of urban plans. This research stands in the early stage of using GI in terms of technical level. In this regard, the meaning of this research is: it verified the fact that it is possible to build a virtual terrain by using only the physical data of a city through a modeland it also generated surface water flows closed to the urban situation. Moreover, this research verified it is possible to identify GI suitable areas and GI types by using variables which reflect the characteristics of surface water, soil and land cover. The meaning of this research in terms of using the model result is as follows: 1) the spatial scope which has direct influence on flooding-vulnerable areas was identified by combining the concept of integrated watershed management with the GI suitable area identification model. 2) The spatial scope for effective GI functions was defined through the model. 3) As a result of studying the feasibility of GI application in urban planning under the current institution, it was found that it is possible to apply GI to district unit planning. Yet, it was also confirmed that there is a limit in this research as the district plan which was case-studied was not focusing on GI. Meanwhile, as the result was produced by using physical spatial data only, the effect of GI on urban-sociologic changes cannot be verified. In addition, the research used the result of previous studies in order to accurately estimate the changes in rainfall runoff. Therefore, if further studies are conducted under the theme of verifying the effect of introducing GI, it will be possible to study changes in users awareness of GIs flooding mitigation effect by using the data of social science of GI. On top of that, urban plans can be implemented in a flood vulnerable area based on the result of the GI suitable area identification model, and then, it would be possible to conduct a study to verify rainfall runoff mitigation effect in the area This research stands at the initial stage of introducing GI. Accordingly, it limited the number of variables used for identifying GI suitable areas to three and defined the spatial resolution as 5mร—5m. The main point of this research is to make a logical system of GI suitable areas using the spatial variables to relate water sensitivity of cities only. Maintaining the logical system of this research, new variables can be added or replace the variables used in this research, which can enhance the precision of analysis, by advancing related technologies. The spatial resolution and the identifying code of GI are also expected to be further improved. In Korea, the planned approach will be required to cope with the climate change phenomenon. For example, to manage the flooding by heavy rain related to climate change, the integrated consideration for the cause and influence is needed on the flooding areas. Especially the necessity of the scientific evidences is arisen for urban planning. In this point of view, the model of this research would provide the benefit based on providing useful GIS platform for urban planning through efficient analyzing function of this model.1. Introduction 1 1.1. Research Background 1 1.2. Research purpose 4 1.3. The scope of research 7 1.3.1. Content scope of research 7 1.3.2. Spatial scope of research 8 1.3.3. Research process 14 2. Literature review 16 2.1. Water Sensitive City and Green Infrastructure 16 2.1.1. Definitions of Urban Drainage Terminologies 16 2.1.2. Water Sensitive City 19 2.1.3. Green Infrastructure 22 2.1.4. Integrated Watershed Management 26 2.1.5. Sub-conclusion 29 2.2. Methodology for stormwater runoff and flood management 31 2.2.1. Prediction model for surface water flooding 31 2.2.2. Methodology of stormwater analysis 37 2.3. Variable definition through previous study 40 2.3.1. Urban topography 41 2.3.2. Distribution of stormwater runoff flow 41 2.3.3. Characteristics of soil 42 2.3.4. Characteristics of land cover 44 3. Development of a model to identify suitable areas for green infrastructure for water sensitive city 46 3.1. Overview 46 3.1.1. Purpose of model 46 3.1.2. Structure of model 47 3.1.3. Differentiation 49 3.2. Specific Urban DEM generation model 52 3.2.1. Purpose of model 52 3.2.2. Model composition methodology 52 3.2.3. Stormwater runoff flow pattern analysis using SUDEM 58 3.3. A model to identify suitable areas for green infrastructure for water sensitivity 61 3.3.1. Overview 61 3.3.2. Composition and methodology of model 62 3.3.3. Sub-conclusion 65 4. Conclusion and discussion 67 4.1. Result of input variable generation process 67 4.1.1. Unban specific hydrologic data 67 4.1.2. Hydrologic soil properties 77 4.1.3. Land cover condition 78 4.2. Result of GI suitable area identification model 80 4.2.1. Types of GI suitable areas 80 4.2.2. Stormwater runoff control effect 85 4.3. Application and discussion 88 4.3.1. Application to flooding-vulnerable areas 88 4.3.2. Approach to urban planning 92 5. Conclusion 99 5.1. Summary of research result 99 5.2. Meaning and limits of research 102 โ–  Bibliography : English 105 โ–  Bibliography : Korean 114 โ–  Web sites 115 Appendix A 117 1. Guidelines for District Unit Planning 117 2. Guideline for Urban Management Plan 118 Appendix B 119 Abbreviations 119Docto

    Development of CAD Solid model to FE model converter algorithm by smart pattern recognition

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€,2007.Maste

    Effect of signal strength on reproducibility of peripapillary retinal nerve fiber layer thickness measurement and its classification by time-domain optical coherence tomography

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    PURPOSE: To assess the effect of signal strength (SS) on reproducibility of peripapillary retinal nerve fiber layer (RNFL) thickness measurement (measurement agreement) and its color-coded classification (classification agreement) by time-domain optical coherence tomography (OCT). METHODS: Two consecutive Stratus OCT scans with the Fast RNFL protocol were performed in 658 participants. Intraclass correlations and the linear-weighted kappa coefficient were calculated as indicators of RNFL measurement and classification agreement in participants grouped according to the difference in SS between consecutive OCT scans (interscan SS difference). RESULTS: Groups with a larger interscan SS difference (= 2) had lower measurement agreement than those with a smaller interscan SS difference (0 or 1) for the temporal quadrant and total average RNFL. Classification agreement for the nasal quadrant was lower in the groups with a larger interscan SS difference (= 2) than in those with a smaller interscan SS difference. The tendency of SS to affect classification and measurement agreement remained similar in the group with thinner RNFL thickness (โ‰ค85 ฮผm), but not in the group with thicker RNFL. CONCLUSIONS: Careful attention should be paid when comparing two or more OCT scans for RNFL thickness measurement or its color-coded classification as the agreement may be sensitive to SS differences.ope

    Short-term change in corneal epithelium after iris fixed phakic intraocular lens insertion

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    ์˜ํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€] ํ™์ฑ„๊ณ ์ • ์œ ์ˆ˜์ •์ฒด์šฉ ์ธ๊ณต์ˆ˜์ •์ฒด ์‚ฝ์ž…์ˆ ์€ ์—‘์‹œ๋จธ๋ ˆ์ด์ €์— ์˜ํ•œ ๊ตด์ ˆ๊ต์ •๋ ˆ์ด์ €๊ฐ๋ง‰์ ˆ์ œ์ˆ ์ด๋‚˜ ๋ ˆ์ด์ € ๊ฐ๋ง‰์ ˆ์‚ญ๊ฐ€๊ณต์„ฑํ˜•์ˆ ๊ณผ ๊ฐ™์€ ์ •๋„์˜ ๊ทผ์‹œ๊ต์ • ํšจ๊ณผ๋ฅผ ๋ณด์ด๋ฉด์„œ๋„ ์ด๋“ค์— ๋น„ํ•ด ๊ต์ • ๊ฐ€๋Šฅํ•œ ๊ทผ์‹œ์˜ ์ •๋„์— ๋น„๊ต์  ์ œํ•œ์ด ์—†๊ณ , ๋Œ€๋น„๊ฐ๋„์˜ ์ €ํ•˜๊ฐ€ ์ ์œผ๋ฉฐ, PRK์—์„œ ๋ณด๋‹ค ๊ตด์ ˆ๋ฅ ์˜ ์•ˆ์ •ํ™”๊ฐ€ ๋น ๋ฅด๋‹ค๋Š” ์ , ๊ทธ๋ฆฌ๊ณ  ํˆฌ๋ช… ์ˆ˜์ •์ฒด ์ ์ถœ์ˆ ๊ณผ ๋‹ฌ๋ฆฌ ์ˆ˜์ˆ  ํ›„ ์กฐ์ ˆ๋ ฅ์„ ๋ณด์กดํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์žฅ์ ๋“ค์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๊ฐ๋ง‰๋‚ดํ”ผ์„ธํฌ ์†์ƒ์˜ ๊ฐ€๋Šฅ์„ฑ ๋•Œ๋ฌธ์— ๊ตด์ ˆ๊ต์ •์˜ ๋ฐฉ๋ฒ•์œผ๋กœ ๋„๋ฆฌ ๋ณด๊ธ‰๋˜์ง€ ์•Š๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ „๋ฐฉ ์œ ์ˆ˜์ •์ฒด์šฉ ์ธ๊ณต์ˆ˜์ •์ฒด์ธ ํ™์ฑ„๊ณ ์ • ์œ ์ˆ˜์ •์ฒด์šฉ ์ธ๊ณต์ˆ˜์ •์ฒด ์‚ฝ์ž…์ˆ˜์ˆ  ํ›„ ๋‚ดํ”ผ์„ธํฌ์˜ ์†์ƒ ์—ฌ๋ถ€์™€ ๊ทธ ์ •๋„๋ฅผ ํ™•์ธํ•˜๊ณ  ์ด์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ์ธ์ž๋“ค์„ ์•Œ์•„๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. 10๋ช… 11์•ˆ์„ ๋Œ€์ƒ์œผ๋กœ ์ „ํ–ฅ์ ์œผ๋กœ ํ™์ฑ„๊ณ ์ • ์œ ์ˆ˜์ •์ฒด์šฉ ์ธ๊ณต์ˆ˜์ •์ฒด ์‚ฝ์ž…์ˆ˜์ˆ  ํ›„ ๊ฐ๋ง‰ ๋‚ดํ”ผ์„ธํฌ์˜ ๋ณ€ํ™”๋ฅผ 1๋‹ฌ ๊ฐ„ ์กฐ์‚ฌํ•˜์—ฌ ์ˆ˜์ˆ  ํ›„ ๊ทธ ๋ฐ€๋„๊ฐ€ ๊ฐ์†Œํ•˜๊ณ (p=0.020; ๊ฐ์†Œ์œจ์€ ์ˆ˜์ˆ  ํ›„ 1์ฃผ์— 3.57%, ์ˆ˜์ˆ  ํ›„ 1๋‹ฌ์— 4.69%), ๋‹ค๋ฅธ ์†์ƒ์ง€ํ‘œ์ธ ๋‚ดํ”ผ์„ธํฌ ํฌ๊ธฐ์™€ ๋ชจ์–‘์˜ ๋‹ค๋ณ€์„ฑ์ด ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์„ ๊ด€์ฐฐํ•˜์˜€์œผ๋‚˜(p0.05). ๋‚ดํ”ผ์„ธํฌ์˜ ๊ฐ์†Œ๋Š” ์ˆ˜์ˆ  ์ „ ์ธก์ •๋œ ๊ฐ๋ง‰๊ณก๋ฅ ๋„๋‚˜ ์‚ฝ์ž…๋œ ์ธ๊ณต์ˆ˜์ •์ฒด์˜ ๋—์ˆ˜, ํฌ๊ธฐ, ๊ด‘ํ•™๋ถ€์™€ ๋‚ดํ”ผ์„ธํฌ๊ฐ„์˜ ๊ฑฐ๋ฆฌ, ๊ทธ๋ฆฌ๊ณ  ์ˆ˜์ˆ  ์ˆœ์„œ ๋“ฑ์— ์˜ํ–ฅ์„ ๋ฐ›์ง€ ์•Š์•˜์œผ๋ฉฐ(p>0.05), ์ „๋ฐฉ ๊นŠ์ด๊ฐ€ ์ ์„ ์ˆ˜๋ก ๊ฐ์†Œ๊ฐ€ ๋งŽ์ด ์ผ์–ด๋‚ฌ๋‹ค(์ƒ๊ด€๊ณ„์ˆ˜=-7.600;p>0.05). ํ™์ฑ„๊ณ ์ • ์œ ์ˆ˜์ •์ฒด์šฉ ์ธ๊ณต์ˆ˜์ •์ฒด ์‚ฝ์ž…์ˆ  ํ›„ ๊ฐ๋ง‰๋‚ดํ”ผ์„ธํฌ ๋ณ€ํ™”๋Š” ๋Œ€๋ถ€๋ถ„ ์ˆ˜์ˆ  ์ค‘ ์†์ƒ์— ์˜ํ•œ ๊ฒƒ์œผ๋กœ ์ˆ˜์ˆ  ํ›„ 1์ฃผ ์ด๋‚ด์— ์ผ์–ด๋‚˜๋ฉฐ, ์•ˆ๊ตฌ ์ „๋ฐฉ์˜ ๊นŠ์ด๊ฐ€ ์–•์„์ˆ˜๋ก ๋งŽ์ด ์ผ์–ด๋‚˜๋ฏ€๋กœ ๊ทธ๋Ÿฌํ•œ ํ™˜์ž์˜ ๊ฒฝ์šฐ ํ™์ฑ„๊ณ ์ • ์œ ์ˆ˜์ •์ฒด์šฉ ์ธ๊ณต์ˆ˜์ •์ฒด ์‚ฝ์ž…์ˆ ์— ์˜ํ•œ ๊ฐ๋ง‰ ๋‚ดํ”ผ์„ธํฌ ์†์ƒ์— ์œ ์˜ํ•˜์—ฌ์•ผ ํ•œ๋‹ค. [์˜๋ฌธ]Many refractive surgeons remain reluctant to implant iris fixed phakic intraocular lens(IOL) because of fear of damaging corneal endothelium even though it is known as relatively accurate method for the correction of refractive error with less limitation in correcting high myopia than conventional excimer laser refractive surgery, faster refractive stabilization than PRK, and less reduction of contrast sensitivity without losing accommodative power. In this study, we prospectively examined endothelial change in 11 phakic eyes implanted with Artisan phakic IOL insertion. Noncontact specular microscopy was performed preoperatively and 1 week and 1 months postoperatively. The mean endothelial cell loss was 3.57% at 1 weak, and 4.69% at 1 month. There were statistically significant decrease in endothelial cell density and increase in pleomorphism and polymegathism of the cell after the surgery which indicate cellular damage (p0.05). No correlation was observed between cell loss and corneal curvature, critical distance, IOL optic size, IOL diopter, and serial order of the operation. However, there was significant negative correlation (R=-7.600; p>0.05) between cell loss and anterior chamber depth. The results suggests that endothelial damage occurred primarily during the surgical procedure and special attention should be given in patients with shallow anterior chamber depth for iris fixed phakic IOL insertion to avoid unintended endothelial damage.ope

    DNAgram : Anagram ๋ฌธ์ œ ํ•ด๊ฒฐ์— ๊ด€ํ•œ ๋ถ„์ž ์ปดํ“จํŒ… ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ˜‘๋™๊ณผ์ • ์ธ์ง€๊ณผํ•™์ „๊ณต,2003.Maste

    Comparison of higher-order aberrations after LASEK with a 6.0 mm ablation zone and a 6.5 mm ablation zone with blend zone

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    PURPOSE: To compare the higher-order aberrations (HOAs) after laser-assisted subepithelial keratectomy (LASEK) using a conventional optical zone and a larger zone with a blend zone. SETTING: Department of Ophthalmology, Yonsei University College of Medicine, Seoul, Korea. METHODS: In this prospective study, 19 patients with a manifest refraction of -3.00 to -8.25 diopters (D) were treated with LASEK using a conventional (6.0 mm) optical zone in 1 eye and a larger (6.5 mm) zone with 8.0 mm blend zone in the other eye. The patients were followed for 3 months. Pupil size, best corrected visual acuity (BCVA), uncorrected visual acuity (UCVA), manifest refraction, corneal topography, pachymetry, and wavefront aberration were examined preoperatively; BCVA, UCVA, manifest refraction, and wavefront aberration were measured 1 and 3 months postoperatively. The Hartmann-Shack aberrometer (WaveScan(R), Visx) was used to measure the overall wavefront aberrations in scotopic pupils. RESULTS: There were no significant differences in preoperative pupil size, BCVA, UCVA, and manifest refraction between the 2 groups or in postoperative BCVA, UCVA, and refraction. Higher-order aberrations increased at 1 and 3 months in both eyes compared with preoperatively. At 3 months, in a scotopic pupil, the mean root-mean-square wavefront error of the HOAs was 0.41 +/- 0.14 in the eyes treated with the larger optical zone and 0.61 +/- 0.28 in those treated with the conventional optical zone. There was a significant difference between optical zones (P =.006). The difference was more pronounced in the treatment of myopia greater than -5.0 D (P =.001). CONCLUSIONS: In the scotopic condition, HOAs after LASEK using a large optical zone with blend zone ablation were smaller than those associated with conventional ablation zone treatment. The larger zone with blend zone treatment may be a good surgical alternative for better visual outcomes in scotopic conditions.ope
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