• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.1
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• pp.99-108
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• 1998

In order to represent the surface characteristics in local meteorological model, soil type, vegetation index, surface roughness length, surface albedo and leaf area index should be prescribed on the surface process parameterization. In this study, the $1^{\circ}/1^{\circ}leaf$ area index, surface roughness length, and snow free surface albedo and fine mesh NDVI with seasonal variation derived from the satellite observation were applied to the land surface process parameterization. From comparison between with and without satellite data in the interactions between biosphere and atmosphere, land and atmosphere, the sensitivity of the simulated heat, energy and water vapor fluxes, ground temperature, wind, canopy water content, specific humidity, and precipitation fields were investigated.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1383-1398
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• 2018

Sea surface wind is one of the most fundamental variables for understanding diverse marine phenomena. Although scatterometers have produced global wind field data since the early 1990's, the data has been used limitedly in oceanic applications due to it slow spatial resolution, especially at coastal regions. Synthetic Aperture Radar (SAR) is capable to produce high resolution wind field data. KOMPSAT-5 is the first Korean satellite equipped with X-band SAR instrument and is able to retrieve the sea surface wind. This study presents the validation results of sea surface wind derived from the KOMPSAT-5 backscattering coefficient data for the first time. We collected 18 KOMPSAT-5 ES mode data to produce a matchup database collocated with buoy stations. In order to calculate the accurate wind speed, we preprocessed the SAR data, including land masking, speckle noise reduction, and ship detection, and converted the in-situ wind to 10-m neutral wind as reference wind data using Liu-Katsaros-Businger (LKB) model. The sea surface winds based on XMOD2 show root-mean-square errors of about $2.41-2.74m\;s^{-1}$ depending on backscattering coefficient conversion equations. In-depth analyses on the wind speed errors derived from KOMPSAT-5 backscattering coefficient data reveal the existence of diverse potential error factors such as image quality related to range ambiguity, discrete and discontinuous distribution of incidence angle, change in marine atmospheric environment, impacts on atmospheric gravity waves, ocean wave spectrum, and internal wave.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2022.09a
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• pp.38-38
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• 2022

동해안 지역에서 발생되는 대형 산불의 원인은 건조주의보, 영동지역에서 불어오는 강한 바람, 소나무의 단순림, 임도 유무와 상태 등을 들고 있다. 조사 대상지인 삼척 검봉산 일대는 기존 소나무가 우점하는 곳으로 2001년 복원을 위해 소나무, 곰솔, 굴참나무 등을 조림하였고, 일부는 자연복원을 하였다. 복원 이후 21년 지난 현재 삼척 검봉산 일대 산불피해 복원지역의 식생은 크게 굴참나무-소나무군락, 소나무신갈나무군락, 곰솔-소나무군락으로 나누어지는 것으로 나타났다. 산불피해지 식생 회복은 굴참나무, 소나무, 곰솔 등 조림으로 현재 식생은 산불 발생 이전의 임상으로 회복되고 있다. 특히, 산불의 유형 중 지표화 피해지역은 하층 식생의 피해가 크다. 기존의 소나무는 결실된 종자를 비산하여 치수를 발생시켜 자연복원의 속도를 높이고 굴참나무를 활용한 인공복원은 맹아를 발달시켜 본인의 영역을 확장하는 전략을 지니고 있다. 단, 입지적 환경이 동일하다는 전제 조건에서 숲에서 재생 기작이 진행되는 자연복원보다는 인공복원이 회복시간과 종다양성이 높은 측면에서는 효과적인 것으로 결론을 지을 수 있다. 식생군락을 분류한 결과 굴참나무-소나무군락, 소나무-신갈나무군락, 곰솔소나무군락으로 3개 군락으로 나누어졌다. 인공복원지에 식재한 굴참나무, 소나무, 곰솔은 복원 이후 지속적으로 해당지역의 식생이 우점종으로 자생하고 있는 것으로 나타났으나, 소나무-신갈나무군락의 경우 참나무과 식물인 신갈나무와 굴참나무, 졸참나무가 교목층과 아교목층에 자연유입되고 있어 향후 신갈나무가 우점하는 활엽수림으로 천이 될 것으로 예상된다. 군락의 종다양도지수는 낙엽활엽수가 우점하는 굴참나무-소나무군락이 가장 높게 나타났으며, 침엽수림인 곰솔소나무군락이 가장 낮게 나타났다. 산불피해지 식생은 조림수종에 영향을 크게 받으며, 21년이 지난 현재 산불 이전 임상으로 회복되는 경향을 나타내었다. 향후, 효과적인 복원을 위한 DB구축 및 모니터링자료 마련을 위해 산불피해지에 대한 지속적인 식생조사를 통한 자료구축이 필요하다.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.477-487
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• 2012

Sea surface winds in the sea off the east coast of Korea were derived from L-band ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) data and their characteristics of errors were analyzed. We could retrieve high-resolution wind vectors off the east coast of Korea including the coastal region, which has been substantially unavailable from satellite scatterometers. Retrieved SAR-wind speeds showed a good agreement with in-situ buoy measurement by showing relatively small an root-mean-square (RMS) error of 0.67 m/s. Comparisons of the wind vectors from SAR and scatterometer presented RMS errors of 2.16 m/s and $19.24^{\circ}$, 3.62 m/s and $28.02^{\circ}$ for L-band GMF (Geophysical Model Function) algorithm 2009 and 2007, respectively, which tended to be somewhat higher than the expected limit of satellite scatterometer winds errors. L-band SAR-derived wind field exhibited the characteristic dependence on wind direction and incidence angle. The previous version (L-band GMF 2007) revealed large errors at small incidence angles of less than $21^{\circ}$. By contrast, the L-band GMF 2009, which improved the effect of incidence angle on the model function by considering a quadratic function instead of a linear relationship, greatly enhanced the quality of wind speed from 6.80 m/s to 1.14 m/s at small incident angles. This study addressed that the causes of wind retrieval errors should be intensively studied for diverse applications of L-band SAR-derived winds, especially in terms of the effects of wind direction and incidence angle, and other potential error sources.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.287-298
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• 1997

The main object of this study was to prove the effectiveness of satellite image data for extraction of the Matsucoccus Thenbergianae Miller ビt Park damaged area. The effectiveness of extraction of damaged area was improved by using the BRCT(Backwards radiance correction transformation) with DEM for normalization of topographic effects. The surface analysis of the extracted damaged area was revealed that the damage was started at south-west slope with the aspect of 7 to 18 degrees, and 50% to 70% of the highest altitude mountains. The direction of damage attached by the Matsucoccus Thunbergianae Miller et Park was able to predict through the analysis of periodical of years' images

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.4
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• pp.206-211
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• 2011

Low water temperature during the summer associated with the occurrence of cold water zone off Haeundae was studied using the data from CTD observations and a monitoring buoy deployed in Suyeong Bay. Shortterm variability of current was dominant and was not related to the wind. The NE-SW components of wind parallel to the coast contained more than 96% of total variance and could account for major fluctuations of water temperature. Upwelling-response of water temperature was very sensitive so that the temperature began to decrease immediately after the onset of the southwesterly wind. In particular, there were three cases in which SW winds for only two days caused considerable temperature drops. In 2009, four upwelling events shorter than 5 days took place while seven events with periods of 2~18 days were recorded in 2010. During a very intense upwelling for seven days in mid-August 2010, temperature decreased by more than $10^{\circ}C$ in spite of the variable winds. Temperature variability at Gampo, Ulsan, Gijang and Haeundae had similar patterns. CTD observation and satellite imagery showed that the upwelling zone could be extended to the Haeundae-Busan area. According to the wavelet analysis, coherent periods were 2~8 days during the frequent upwelling/downwelling events.

• Journal of Conservation Science
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• v.37 no.3
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• pp.209-219
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• 2021

In this study, the wind environment in an urban area near Sungneymun gate was numerically investigated in the cases of inflow directions. The wind fields for the target area were simulated using Geographic Information System data and Computational Fluid Dynamics model. Results, including vector fields, three-dimensional wind velocity components, and wind speeds, were analyzed to examine flow characteristics. Wind direction variability affected by buildings was shown in the target area. The complex flows around Sungneymun did not depend on the inflow direction as a boundary condition. The wind speed around Sungneymun was generally 3 times stronger at 14 m above ground level (AGL) compared to the surface wind at 2 m AGL and relatively high in the case of easterly inflow. The effect of wind was also analyzed to be relatively significant at the southeast side of Sungneymun. Thus, it was suggested that the assessment of wind environment affected by high-rise and high-density buildings should be necessary for the architectural heritage in urban areas.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.81-94
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• 2010

Input variable selection is one of the various techniques for improving the performance of artificial neural network. In this study, mutual information is applied for input variable selection technique instead of correlation coefficient that is widely used. Among 152 variables of RDAPS (Regional Data Assimilation and Prediction System) output results, input variables for artificial neural network are chosen by computing mutual information between rainfall records and RDAPS' variables. At first the rainfall forecast variable of RDAPS result, namely APCP, is included as input variable and the other input variables are selected according to the rank of mutual information and correlation coefficient. The input variables using mutual information are usually those variables about wind velocity such as D300, U925, etc. Several statistical error estimates show that the result from mutual information is generally more accurate than those from the previous research and correlation coefficient. In addition, the artificial neural network using input variables computed by mutual information can effectively reduce the relative errors corresponding to the high rainfall events.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.237-240
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• 2017

지구온난화로 인해 세계 곳곳에서 기온상승이 관측되고 있으며, 이는 전지구적 기후시스템의 변화를 보여주는 대표적인 예이다. 온도를 비롯한 강수량, 풍속, 증발량 등의 기상학적, 수문학적 인자들이 각각 서로에게 영향을 주고 받으며 복잡하게 변화할 것이고, 그 변화폭도 점점 커질 것이다. 증발에 영향을 미치는 인자들은 크게 세 가지로 나뉘는데, 태양복사에너지, 온도, 바람, 기압, 습도와 같은 기상학적인자, 증발표면의 특성인자 그리고 수질인자로 분류할 수 있다. 증발에 영향을 주는 인자들은 예전부터 알려져 있지만 이들 간의 복잡한 상호작용에 대해 정확히 이해하기는 쉽지 않다. 본 연구에서는 댐유역의 증발량에 영향을 미치는 기상인자 파악을 위해 2008부터 2016년까지 관측된 낙동강수계 내 안동댐과 남강댐의 기상자료(기온, 강수량, 풍속, 상대습도, 기압, 일사량, 일조시간, 전운량)를 이용한 변화를 분석하였으며, 다변량 통계기법인요인분석을 통해 증발량과 상관성이 높은 인자들을 분류하였다. 안동댐과 남강댐 공통적으로 증발량과 기온, 기압이 같은 요인으로 분류되고 높은 상관성을 보였으며, 강수량, 일조시간, 일사량, 전운량이 같은 요인으로 분류되었다. 국내의 증발량 측정지점에 대한 추가적인 분석과 영향인자를 이용한 다변량회귀식과 인공신경망 통해 증발량 미측정 지점의 증발량 산정이 가능할 것으로 판단된다.