• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.1-16
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• 2017

This study was conducted to analyze the urban heat island(UHI) intensity of South Korea by using Moderate Resolution Imaging Spectroradiometer(MODIS) satellite imagery. For this purpose, the metropolitan area was spatially divided according to land cover classification into urban and non-urban land. From the analysis of land surface temperature(LST) in South Korea in the summer of 2009 which was calculated from MODIS satellite imagery it was determined that the highest temperature recorded nationwide was $36.0^{\circ}C$, lowest $16.2^{\circ}C$, and that the mean was $24.3^{\circ}C$, with a standard deviation of $2.4^{\circ}C$. In order to analyze UHI by cities and counties, UHI intensity was defined as the difference in average temperature between urban and non-urban land, and was calculated through RST1 and RST2. The RST1 calculation showed scattered distribution in areas of high UHI intensity, whereas the RST2 calculation showed that areas of high UHI intensity were concentrated around major cities. In order to find an effective method for analyzing UHI by cities and counties, analysis was conducted of the correlation between the urbanization ratio, number of tropical heat nights, and number of heat-wave days. Although UHI intensity derived through RST1 showed barely any correlation, that derived through RST2 showed significant correlation. The RST2 method is deemed as a more suitable analytical method for measuring the UHI of urban land in cities and counties across the country. In cities and counties with an urbanization ratio of < 20%, the rate of increase for UHI intensity in proportion to increases in urbanization ratio, was very high; whereas this rate gradually declined when the urbanization ratio was > 20%. With an increase of $1^{\circ}C$ in RST2 UHI intensity, the number of tropical heat nights and heat wave days was predicted to increase by approximately five and 0.5, respectively. These results can be used for reference when predicting the effects of increased urbanization on UHI intensity.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.119-119
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• 2023

본 연구에서는 Terra MODIS(MODerate resolution Imaging Spectroradiometer) 위성영상과 토양수분 부족지수(Soil Water Deficit Index, SWDI)를 이용하여 2012년부터 2022년까지 한반도 전국의 1km 공간 증발산량을 산정하였다. 공간 증발산량을 산정하기 위한 과정은 크게 두 가지로 구분된다. 첫 번째로 MODIS의 LST(Land Surface Temperature), NDVI(Normalized Difference Vegetation Index), 선행강우 및 무강우 누적일수를 이용해 1 km 공간 토양수분을 산정하였다. 농촌진흥청 토양수분관측망 자료 중 토지피복, 토양 속성을 고려하여 선정된 70개소 토양수분 실측데이터와 비교한 결과 지점별 평균 R² 0.63~0.90으로 유의미한 상관성을 나타내었다. 산정된 공간 토양수분은 생장저해수분점과 초기위조점의 관계를 이용한 SWDI로 변환하였다. 두 번째로 순 복사량, 기온 및 NDVI의 적은 수문인자를 통해 증발산량 산정이 가능한 MS-PT(Modified Satellite-based Priestley-Taylor) 모형을 기반으로 계절별 식생과 토양수분 상태를 고려하여 1 km 공간 증발산량을 산정하였다. MS-PT 모형에서 가정한 대기 증발 변수 Diurnal temperature (DT)와 지표 수분의 상관성 문제를 해결하기 위해 DT를 SWDI로 적용하였다. 모형 결과의 검증을 위해 국내 플럭스 타워 (설마천, 청미천, 덕유산) 증발산량 관측자료와의 결정계수(Coefficient of determination, R²), RMSE(Root Mean Square Error) 및 IOA(Index of Agreement)를 산정하였다. 본 연구의 결과로 생산되는 국내 증발산량의 시, 공간적 변동성은 증발산량을 통한 수문학적 가뭄지수 및 급성 가뭄을 파악하는데 활용될 수 있을 것으로 판단된다.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.126-137
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• 2021

Recently, the number of damages on social infrastructure has increased due to natural disasters and the frequency of earthquake events that are higher than magnitude 3 has increased in South Korea. Liquefaction was found near the epicenter of a 5.4 magnitude earthquake that occurred in Pohang, South Korea, in 2017. To explore increases in soil moisture index due to soil liquefaction, changes in the remote exploration index by the land cover before and post-earthquake occurrence were analyzed using liquefaction feasibility index and multi-cyclical Landsat-8 satellite images. We found that the soil moisture index(SMI) in the liquefaction region immediately after the earthquake event increased significantly using the Normal Vegetation Index(NDVI) and Surface Temperature(LST).

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.61-77
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• 2024

The purpose of this study was to develop a method for rapidly diagnosing urban thermal comfort using Unmanned Aerial Vehicle (UAV) based data. The research was conducted at Changwon National University's College of Engineering site and Yongji Park, both located in Changwon, Gyeongsangnam-do. Baseline data were collected using field measurements and UAVs. Specifically, the study calculated field measurement-based thermal comfort indices PET and UTCI, and used UAVs to create and analyze vegetation index (NDVI), sky view factor (SVF), and land surface temperature (LST) images. The results showed that UAV-predicted PET and UTCI had high correlations of 0.662 and 0.721, respectively, within a 1% significance level. The explanatory power of the prediction model was 43.8% for PET and 52.6% for UTCI, with RMSE values of 6.32℃ for PET and 3.16℃ for UTCI, indicating that UTCI is more suitable for UAV-based thermal comfort evaluation. The developed method offers significant time-saving advantages over traditional approaches and can be utilized for real-time urban thermal comfort assessment and mitigation planning

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.3
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• pp.51-61
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• 2020

Drought events are not clear when those start and end compared with other natural disasters. Because drought events have different timing and severity of damage depending on the region, various studies are being conducted using satellite images to identify regional drought occurrence differences. In this study, we investigated the applicability of drought assessment using the Evaporative Stress Index (ESI) based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. The ESI is an indicator of agricultural drought that describes anomalies in actual and reference evapotranspiration (ET) ratios that are retrieved using remotely sensed inputs of Land Surface Temperature (LST) and Leaf Area Index (LAI). However, these approaches have a limited spatial resolution when mapping detailed vegetation stress caused by drought, and drought hazard in the actual crop cultivation areas due to the small crop cultivation in South Korea. For these reasons, the development of a drought index that provides detailed higher resolution ESI, a 500 m resolution image is essential to improve the country's drought monitoring capabilities. The newly calculated ESI was verified through the existing 5 km resolution ESI and historical records for drought impacts. This study evaluates the performance of the recently developed 500 m resolution ESI for severe and extreme drought events that occurred in South Korea in 2001, 2009, 2014, and 2017. As a result, the two ES Is showed high correlation and tendency using Receiver Operating Characteristics (ROC) analysis. In addition, it will provide the necessary information on the spatial resolution to evaluate regional drought hazard assessment and and the small-scale cultivation area across South Korea.

• Journal of Wetlands Research
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• v.8 no.1
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• pp.49-58
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• 2006

Drought is an natural phenomenon which effects greatly on our society. It has various time scale and it is difficult to define the beginning and the end. So we can't aware it quickly and the damage of drought become severe. To cope with these problems, it needs to construct drought monitoring system. And it is required that the definition of drought which is objective and can be applied widely and proper drought index for drought monitoring. Meteorology and hydrology have developed drought index for drought monitoring. There are many attempt to interpret the drought using NDVI(Normalized Difference Vegetation Index) or LST(Land Surface Temperature) in remote sensing. In this study, drought index and precipitation is used to find drought severity of last ten years in South Korea. NDVI and VCI is applied to perceive the state of drought. Finally, the possibility of drought monitoring and evaluating drought depth is estimated by analyzing the correlation between vegetation Index and drought index.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.605-605
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• 2016

최근 기후변화로 인한 국지적 또는 대규모 극한 가뭄과 홍수가 빈발함에 따라 수자원 관리 여건은 점점 더 어려워지고 있다. 이런 물 관련 재해에 보다 효과적으로 대응하기 위해서는 수자원인자에 대한 시공간적 모니터링이 필수적인데, 이러한 관점에서 시공간적 광역관측이 가능한 위성자료의 활용가치는 매우 높게 평가되고 있으며, 최근에는 국내외적으로 위성자료를 이용하여 수문 인자 산출, 가뭄 홍수 등의 모니터링 기술 등에 대한 연구가 활발히 진행되고 있다. K-water는 위성정보 활용기술력 축적을 통한 보다 효율적인 수자원 관리를 하기 위하여 수자원 분야에 활용 가능한 해외의 주요 위성자료를 실시간 직수신 처리하여 표출하는 K-water 위성영상관리시스템(K-SIMS, K-water Satellite Image Management System)을 2015년에 구축하였다. 현재 K-SIMS를 통해 관리되는 위성은 AQUA, TERRA, NPP, GCOM-W, GPM로서 총 5개이다. AQUA, TERRA, NPP 위성은 각 궤도운영 스케쥴에 따라 한반도 상공을 통과하는 시각에 안테나가 위성의 궤도를 따라가며 수신하고, GCOM-W, GPM 위성자료는 FTP 접속를 통해 준실시간으로 수신하고 있다. 산출물은 AQUA, TERRA, NPP가 각각 23종, GCOM-W 9종, GPM 2종 등 총 80여종으로 위성원시자료 수신즉시 처리 표출까지 실시간 자동 수행되고 있으나 식생지수, 강수, 구름, 대기온도, 수증기 등 대부분 수문기상학적 변수들로 구성되어 있어 수자원 관리 현업 업무에는 직접 사용하기에는 다소 한계가 있다. 따라서, 위성자료의 활용성을 높이기 위하여 수문해석에 중요한 변수인 토양수분에 대해서 AQUA, TERRA의 MODIS LST(Land Surface Temperature)와 식생지수(Vegetation Index)를 이용하여 SMI(Soil Moisture Index)를 산출하고 이를 K-SIMS에 표출하는 체계를 추가로 구축하여 현업 활용도가 높은 자료를 생산하고 있으며, 향후 위성자료를 활용한 가뭄지수를 추가로 산출하여 표출할 계획이다. 이와 함께 K-water는 차세대 중형위성 개발 사업에 따른 수자원 위성 확보에 대비해 수자원 분야 위성활용 중장기 계획을 마련하였다. 향후에 광학위성, SAR위성 등 다양한 위성자료의 융복합적 활용을 통하여 위성산출물 알고리즘을 지속적으로 개발함으로써 홍수, 가뭄, 수질 등 물 재해 대응 및 수자원 관리 전 분야에 위성자료의 활용을 확대해 나갈 계획이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.365-365
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• 2019

가뭄은 전 세계적으로 농업을 비롯한 사회, 경제적으로 큰 피해를 주는 자연 재해이며, 향후 피해 저감을 위해 가뭄의 경향을 파악하고 지역별 가뭄 특성을 파악할 필요가 있다. 위성영상을 활용한 가뭄 판단은 광역적 범위를 대상으로 다양한 밴드를 활용한 데이터를 주기적이고 일정한 수준으로 취득 가능하다는 장점이 있다. 농업 가뭄 분야의 위성영상 활용은 미계측 지역에 대한 정확한 데이터 취득이 어려운 지점데이터의 단점을 보완할 수 있다. 위성영상을 활용한 가뭄 지수로는 Leaf Area Index (LAI), Vegetation Health Index (VHI), Enhanced Vegetation Index (EVI) 등 다양한 지수들이 있으며, 본 연구에서는 단기 가뭄 판단에 활용되고 있는 Evaporative Stress Index (ESI)를 활용하였다. 국내 행정구역 기반의 가뭄 판단을 위해 Moderate Resolution Imaging Spectramadiometer (MODIS)위성의 MOD16A2 영상을 사용하였다. MOD16A2는 land surface temperature (LST)과 LAI의 계산을 통한 실제 증발산량과 FAO-56 Penman-Monteith 공식을 사용한 잠재증발산량을 포함한 다양한 데이터를 8일 주기의 500m 해상도로 제공하고 있다. 2001년부터 2018년까지 500m 해상도의 ESI를 산정하였으며, 국내의 과거 가뭄 경향 분석과 지역별 특성 파악을 위한 표준화를 수행하였다. 그 결과 과거 극심한 가뭄이 있었던 해 (2000-2001년, 2015-2017년 등)에 대한 농업 가뭄 경향 분석이 가능하였으며, 지역별 특성을 파악한 결과 상습가뭄 지역에서 가뭄 경향을 확인하였다. 농업 가뭄 분야에서 ESI의 활용은 가뭄 조기 경보 시스템 개발 및 위성영상 기반 가뭄 모니터링 기술 개발 등에 활용 가능할 것으로 기대된다.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.6
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• pp.789-800
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• 2013

$N_2O$ and $CH_4$, Greenhouse gas emission, Forest soil, Closed chamber technique, Soil uptake $N_2O$ and $CH_4$ are important greenhouse gases (GHG) along with $CO_2$ influencing greatly on climate change. Their soil emission rates are highly affected by bio-geo-chemical processes in C and N through the land-atmosphere interface. The forest ecosystems are generally considered to be net emission for $N_2O$; however, net sinks for $CH_4$ by soil uptake. Soil $N_2O$ and $CH_4$ emissions were measured at Mt. Taewha in Gwangju, Kyeonggi, Korea. Closed chamber technique was used for surface gas emissions from forest soil during period from May to October 2012. Gas emission measurement was conducted mostly on daytime (from 09:00 to 18:00 LST) during field experiment period (total 25 days). The gas samples collected from chamber for $N_2O$ and $CH_4$ were analyzed by gas chromatography. Soil parameters were also measured at the sampling plot. GHG averages emissions during the experimental period were $3.11{\pm}16.26{\mu}g m^{-2}hr^{-1}$ for $N_2O$, $-1.36{\pm}11.3{\mu}gm^{-2}hr^{-1}$ for $CH_4$, respectively. The results indicated that forest soil acted as a source of $N_2O$, while it acted like a sink of $CH_4$ on average. On monthly base, means of $N_2O$ and $CH_4$ flux during May (spring) were $8.38{\pm}48.7{\mu}gm^{-2}hr^{-1}$, and $-3.21{\pm}31.39{\mu}gm^{-2}hr^{-1}$, respectively. During August (summer) both GHG emissions were found to be positive (averages of $2.45{\pm}20.11{\mu}gm^{-2}hr^{-1}$ for $N_2O$ and $1.36{\pm}9.09{\mu}gm^{-2}hr^{-1}$ for $CH_4$); which they were generally released from soil. During September (fall) $N_2O$ and $CH_4$ soil uptakes were observed and their means were $-1.35{\pm}12.78{\mu}gm^{-2}hr^{-1}$ and $-2.56{\pm}11.73{\mu}gm^{-2}hr^{-1}$, respectively. $N_2O$ emission was relatively higher in spring rather than other seasons. This could be due to dry soil condition during spring experimental period. It seems that soil moisture and temperature mostly influence gas production and consumption, and then emission rate in subsoil environment. Other soil parameters like soil pH and chemical composition were also discussed with respect to GHG emissions.