• Journal of Korean Society for Atmospheric Environment
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• v.20 no.4
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• pp.523-537
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• 2004

In order to raise the accuracy of meteorological data, several numerical experiments about the usefulness of data assimilation to prediction of air pollution was carried out. Used data for data assimilation are surface meteorological components observed by Automatical Weather System with high spatial density. The usage of surface data assimilation gives changes of temperature and wind fields and the change caused by the influence of land-use on meterological simulation is more sensitive at night than noon. The data quality in assimilation it also one of the important factors to predict the meteorological field precisely and through the static IOA (Index of Agreement), simulated meteorological components with selected limited surface data assimilation are agree well with observations.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.470-470
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• 2015

본 연구의 목적은 위성영상 기반의 SEBAL(Surface Energy Balance Algorithm for Land) 모형과 SWAT(Soil and Water Assessment Tool) 수문모형을 용담댐 유역($922.3km^2$)에 적용하여 증발산량을 산정하고 모형 간 공간 증발산량의 비교를 통해 각 모형의 적용성을 평가하는데 있다. 이를 위해 SEBAL모형의 입력자료로 Terra MODIS(Moderate Resolution Imaging Spectrometer) Product 중 Normalized Distribution Vegetation Index(NDVI), Albedo 영상을 2012년부터 2013년까지 월단위로 구축하고, 일단위의 Land Surface Temperature(LST) 영상을 구축하였다. 지형자료로는 Digital Elevation Model(DEM)과 Land use를 구축하였으며 SEBAL 모형의 구동을 위한 위성영상 및 지형자료는 500 m의 공간해상도로 재구축하였다. SWAT 모형의 모의를 위해 기상 및 유량 자료를 2000년부터 2013년까지 일단위로 구축하였고, DEM, Land use, 토양도의 지형자료를 30 m의 공간해상도로 구축하였다. SWAT 모형의 유출 검보정 후 수위관측소 지점에서 평균 $R^2$를 산정한 결과 도치(0.80), 동향(0.72), 석정(0.64), 주천(0.80), 천천(0.80), 용담댐(0.72)로 높은 상관성을 나타냈으며, 유출 검보정 후 SWAT 모형의 증발산량 모의 결과를 바탕으로 SEBAL 모형과의 공간 증발산량을 비교하였다. 두 모형의 증발산량은 SEBAL 모형의 경우 지형에 따라 SWAT 모형은 토양 특성에 따라 분포하는 경향이 다르게 나타났다. SEBAL 모형은 주로 저지대에서 증발산량이 높게 산정되며 고지대로 갈수록 감소하여 증발산량이 지형의 고저차에 따라 분포하는 모습을 보였다. SWAT 모형은 토양 특성에 따라 증발산량이 분포하며 유역 내에서 뚜렷한 차이를 나타내지는 않았다. 월별 총 증발산량은 SWAT 모형의 경우 7~8월에 약 90 mm/mon로 가장 높게 나타나고 1~2월은 0 mm/mon로 계절별 변화폭이 컸으나, SEBAL 모형의 경우 5~6월에 증발산량이 약 60 mm/mon로 가장 높게 나타났고 계절별 변화 폭이 SWAT 모형에 비해 적은 모습을 보였다. 이는 위성영상을 기반으로 하는 SEBAL 모형의 특성상 장마 기간에 해당하는 7~8월은 구름으로 인해 일사량이 적게 계산되고, 그 결과 5~6월에 비해 증발산량이 작게 산정되는 것으로 판단된다.

• Journal of Environmental Impact Assessment
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• v.19 no.4
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• pp.367-380
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• 2010

수산 해양환경적 측면에서 중요한 위치에 있는 황해(Yellow Sea)의 해양 생태계 변화과정에 대 한 체계적이고 심층적인 연구을 위하여 기후 변화와 관련된 생태 및 환경변화에 대한 황해 해역의 반응성 연구가 필요한 실정이다. 본 연구는 황해해역에서 수온 상승에 따른 클로로필의 변화를 살펴보고, 지구온난화가 해양환경과 생태계에 미칠 영향을 예측하고자 하였다. 황해해역에서 해수유동 모델의 결과를 기초 입력자료로 활용하여 클로로필과 상호작용을 하는 육상유입부하량, 저질 영양 염용출량 및 생물학적 파라메타 등을 입력하여 현재상태를 재현하였다. 우리나라 주변 해수의 온도가 지난 10년간 약 $0.75^{\circ}C$ 상승했다고 가정하였을 때, 본 실험에서는 수온이 선형적으로 연간 $0.075^{\circ}C$ 씩 상승한다고 가정하여 10년 후까지의 Chlorophyll-a 농도 변화를 예측하였다. 예측 결과, 연구해역의 중앙부에서는 전체적으로 농도가 높아지고, 우리나라 연안해역에서 Chlorophyll-a 의 농도가 낮아지는 것으로 예측되었다. 본 연구의 결과를 기초로 하여 10년 이상의 장기적인 예측실험을 한다면 기후변화가 황해해역의 생태계 변화에 미치는 영향을 파악할 수 있을 것으로 기대된다.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.46-56
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• 2018

This paper aimed to identify main factors of community characters, which have an effect on the land surface temperature(LST) change and estimate the impacting coefficient(ratio) of factors in a significant level of statistics. Chungcheongbuk-do province was selected and then partitioned into city and county areas for the sake of convenience of modeling. LST time series data and the community character data were developed based on Terra Satellite MODIS data and collected from the National Statistical Office, respectively. By the cause and effect relationship between community characters and LST, regression coefficients were estimated using a penal model. In a panel modeling, LST and community characters were used as a dependent variable and explanatory variables, respectively. Panel modeling analysis was carried out using statistical package STATA14 and one-way fixed effect model was selected as the most suitable model to evaluate the regression coefficients in the study area. The impacting ratio of LST change by any explanatory variable derived from the regression coefficients of the panel model fixed. Impacting ratios for industrial areas, elevation ${\times}$ building, energy usage, average window speed, non-urban management area, agricultural, nature and environmental conservation, average precipitation were 3.746, 2.856, 2.742, 0.553, 0.102, 0.071 and 0.003, respectively.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.10
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• pp.101-106
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• 2014

Although anti-freezing heating cable has been widely installed in most residential boiler pipe, there were excessive energy consumption and fire risk due to inadequate temperature control. In this paper, a new energy saving fire risk-free controller was developed by using microprocessing operation which include detection of not only boiler room temperature but also pipe surface one. Its actual effect has been verified to save more than a half of the energy consumption comparing to conventional controller through temperature and humidity chamber experiment.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.2
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• pp.34-43
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• 2009

Based on previous research on ways of reducing an urban heat island phenomenon via an introduction of wind corridors, I conducted this study to see what influence a change in land cover arising of or going through urbanization has on wind corridors of urban space. As a target place, I chose Daegu city where is a representative extreme heat place in Korea and has been also largely expanded in size by incorporating its neighboring areas since the 1980s, expecially Dalseo District whose surface temperature gap is large. The population of Dalseo District has been sharply increased since its creation as a new administrative district in 1988. I studied on the urban microclimate change for a 20-year period by using satellite images on summer months in 1987, 1997 and 2007 in time frames. The finding of this study found that a reduction of natural land cover and an increase of artificial land cover serves as a disadvantageous factor for cold air creation and flowing and strikingly lowers the amount and height of cold air in the downtown area. It seemed that the cold air creation and flowing functions are influenced by land cover. In order to steadily create cold air and secure its flowing, it is thought that urban development or urban regeneration should be implemented by analysing the characteristics of the space surrounding the city. By doing so, a pleasant and healthy city could be formed.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.20-29
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• 2006

Modeling urban climate caused by land use conversion is critical for human welfare and sustainable development, but has hampered because detailed information on urban characteristics is hard to obtain. With the advantage of satellite observations and the new statistical boundary system, this paper measures the economic and environmental effects of green area loss due to land use conversion in urban areas. To perform this purpose, data were collected from the various sources basic statistical unit data from the National Statistical Office, digital maps from the National Geographic Information Institute, satellite images, and field surveys when necessary. All data (maps and attributes) are built into the geographic information system (GIS). This paper also utilizes Landsat TM 5 imagery of Daegu city to derive vegetation index and to measure average surface temperature. The satellite data were examined using standard image processing software, ERDAS IMAGINE, and the results of the digital processing were presented with ARCVIEW(v.3.3). SAS package was used to perform statistical analyses. This study presents that there exists a strong relationship between land use change and climatic change as well as land price change. Based on results of the analysis, this paper suggests that planners should implement effective tools and policies of urban growth management to detect environmental quality and to make right decisions on policies concerning smart urban growth.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1101-1118
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• 2017

Temperatures in urban areas are steadily rising due to rapid urbanization and on-going climate change. Since the spatial distribution of heat in a city varies by region, it is crucial to investigate detailed thermal characteristics of urban areas. Recently, many studies have been conducted to identify thermal characteristics of urban areas using satellite data. However,satellite data are not sufficient for precise analysis due to the trade-off of temporal and spatial resolutions.In this study, in order to examine the thermal characteristics of Daegu Metropolitan City during the summers between 2012 and 2016, Moderate Resolution Imaging Spectroradiometer (MODIS) daytime and nighttime land surface temperature (LST) data at 1 km spatial resolution were downscaled to a spatial resolution of 250 m using a machine learning method called random forest. Compared to the original 1 km LST, the downscaled 250 m LST showed a higher correlation between the proportion of impervious areas and mean land surface temperatures in Daegu by the administrative neighborhood unit. Hot spot analysis was then conducted using downscaled daytime and nighttime 250 m LST. The clustered hot spot areas for daytime and nighttime were compared and examined based on the land cover data provided by the Ministry of Environment. The high-value hot spots were relatively more clustered in industrial and commercial areas during the daytime and in residential areas at night. The thermal characterization of urban areas using the method proposed in this study is expected to contribute to the establishment of city and national security policies.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.65-77
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• 2012

This study examined changes in land cover for the past 25 years in Busan and subsequently evaluated heat island potential by using land surface temperature and observation temperature data. The results were as below. The urban area of Busan increased by more than 2.5 times for the past 25 years from 1975 to 2000. It was believed that an increase in the pavement area of city within such a short period of time was an unprecedented phenomenon unique to our country. It could be assumed that urban heat island would be worsened through this process. After analyzing the land temperature according to the land cover, it was shown that there were noticeable changes in the temperature of urban & built-up and mountain & forest areas. In particular, the temperature rose to $36{\sim}39^{\circ}C$ in industrial areas during the summer, whereas it went down to $22{\sim}24^{\circ}C$ in the urban areas at whose center there were mountains. It was found that heat island potential according to the level of land cover had various values depending on the conditions of land cover. Among the areas of urbanization, the industrial area's heat island potential is 6 to $8^{\circ}C$, and the residential and commercial area's is $0{\sim}5^{\circ}C$, so it has been found that there is high possibility to induce urban heat islands. Meanwhile, in the forest or agricultural area or the waterside, the heat island potential is $-6{\sim}-3^{\circ}C$. With this study result, it is possible to evaluate the effects of temperature increase according to the urban land use, and it can be used as foundational data to improve urban thermal environment and plan eco-friendly urban development.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.931-946
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• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.