• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.275-278
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• 2006

Google Earth enables people to easily find information linked to geographical locations. Google Earth consists of a collection of zoomable satellite images laid over a 3-D Earth model and any geographically referenced information can be uploaded to the Web and then downloaded directly into Google Earth. This can be achieved by encoding in Google's open file format, KML (Keyhole Markup Language), where it is visible as a new layer superimposed on the satellite images. We used KML to create and share fine resolution gridded temperature data projected to 3 climatological normal years between 2011-2100 to visualize the site-specific warming and the resultant earlier blooming of spring flowers over the Korean Peninsula. Gridded temperature and phonology data were initially prepared in ArcGIS GRID format and converted to image files (.png), which can be loaded as new layers on Google Earth. We used a high resolution LCD monitor with a 2,560 by 1,600 resolution driven by a dual link DVI card to facilitate visual effects during the demonstration.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.687-701
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• 2014

Sea ice is generally accepted as an important factor to understand the process of earth climate changes and is the basis of earth system models for analysis and prediction of the climate changes. To continuously monitor sea ice changes at kilometer scale, it is demanded to create more accurate grid data from the current, limited sea ice data. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Sea Ice Concentration (SIC) from 10 km to 1 km resolution using a weighting scheme of sea ice days ratio derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sea ice cover product that has a high correlation with the SIC. In a case study for Okhotsk Sea, the sea ice areas of both data (before and after downscaling) were identical, and the monthly means and standard deviations of SIC exhibited almost the same values. Also, Empirical Orthogonal Function (EOF) analyses showed that three kinds of SIC data (ERA-Interim, original AMSR2, and downscaled AMSR2) had very similar principal components for spatial and temporal variations. Our method can apply to downscaling of other continuous variables in the form of ratio such as percentage and can contribute to monitoring small-scale changes of sea ice by providing finer SIC data.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.307-321
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• 2016

Planetary Boundary Layer Height (PBLH) is a major input parameter for weather forecasting and atmosphere diffusion models. In order to estimate the sub-grid scale variability of PBLH, we need to monitor PBLH data with high spatio-temporal resolution. Accordingly, we introduce a LIdar observation VEhicle (LIVE), and analyze PBLH derived from the lidar loaded in LIVE. PBLH estimated from LIVE shows high correlations with those estimated from both WRF model ($R^2=0.68$) and radiosonde ($R^2=0.72$). However, PBLH from lidar tend to be overestimated in comparison with those from both WRF and radiosonde because lidar appears to detect height of Residual Layer (RL) as PBLH which is overall below near the overlap height (< 300 m). PBLH from lidar with 10 min time resolution shows typical diurnal variation since it grows up after sunrise and reaches the maximum after 2 hours of sun culmination. The average growth rate of PBLH during the analysis period (2014/06/26 ~ 30) is 1.79 (-2.9 ~ 5.7) m $min^{-1}$. In addition, the lidar signal measured from moving LIVE shows that there is very low noise in comparison with that from the stationary observation. The PBLH from LIVE is 1065 m, similar to the value (1150 m) derived from the radiosonde launched at Sokcho. This study suggests that LIVE can observe continuous and reliable PBLH with high resolution in both stationary and mobile systems.

• Atmosphere
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• v.17 no.1
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• pp.87-99
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• 2007

Simulation results of Asian Dust Aerosol Model (ADAM) for the period of April 7-9, 2006 were analyzed, comparing with observed PM10 data. ADAM simulated around ten times lower than on-site PM10 concentration in the source regions: Zhurihe, Tongliao, Yushe, Dalian and Huimin. As the result of this low concentration, transported amounts of Asian Dust were under-estimated as well. In order to quantify a forecasting accuracy, Bias and RMSE were calculated. Even though remarkably negative Biases and high RMSEs were observed, ADAM simulation had followed well up the time of dust outbreak and a transported path. However, the emission process to generate dust from source regions requires a great enhancement. The PM10 concentration at the surface reached up to $2,300{\mu}gm^{-3}$ at Baeknyoungdo and Seoul (Mt. Gwanak), up to $1,750{\mu}gm^{-3}$ at KGAWO about 18:00 LST in April 8, respectively; however, ADAM did not simulate the same result on its second peak. It is considered that traveling Asian dust might have been lagged over the Korean peninsula by the blocking of surface high pressure. Moreover, the current RDAPS's 30 km grid resolution (which ADAM adopts as the meteorological input data) might not adequately represent small-scale atmospheric motions below planetary boundary layer.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.6
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• pp.1179-1194
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• 1992

QUICKER scheme has several attractive properties. However, under highly convective conditions, it produces overshoots and possibly some oscillations on each side of steps in the dependent variable when the flow is convected at an angle oblique to the grid line. Fortunately, it is possible to modify the QUICKER scheme using non-linear and linear functional relationship. Details of the development of polynomial upwinding scheme are given in this paper, where it is seen that this non-linear scheme has also third order accuracy. This polynomial upwinding scheme is used as the basis for the SHARPER and SMARTER schemes. Another revised scheme was developed by partial modification of QUICKER scheme using CDS and UPWIND schemes(QUICKUP). These revised schemes are tested at the well known bench mark flows, Two-Dimensional Pure Convection Flows in Oblique-Step, Lid Driven Cavity Flows and Buoyancy Driven Cavity Flows. For pure convection oblique step flow test problem, QUICKUP, SMARTER and SHARPER schemes remain absolutely monotonic without overshoot and oscillation. QUICKUP scheme is more accurate than any other scheme in their relative accuracy. In high Reynolds number Lid Driven Cavity Flow, SMARTER and SHARPER schemes retain lower computational cost than QUICKER and QUICKUP schemes, but computed velocity values in the revised schemes produced less predicted values than QUICKER scheme which is strongly effected by overshoot and undershoot values. Also, in Buoyancy Driven Cavity Flow, SMARTER, SHARPER and QUICKUP schemes give acceptable results.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1567-1577
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• 2020

Urban land cover classification is role in urban planning and management. So, it's important to improve classification accuracy on urban location. In this paper, machine learning model, Support Vector Machine (SVM) and Artificial Neural Network (ANN) are proposed for urban land cover classification based on high resolution satellite imagery (KOMPSAT-3A). Satellite image was trained based on 25 m rectangle grid to create training data, and training models used for classifying test area. During the validation process, we presented confusion matrix for each result with 250 Ground Truth Points (GTP). Of the four SVM kernels and the two activation functions ANN, the SVM Polynomial kernel model had the highest accuracy of 86%. In the process of comparing the SVM and ANN using GTP, the SVM model was more effective than the ANN model for KOMPSAT-3A classification. Among the four classes (building, road, vegetation, and bare-soil), building class showed the lowest classification accuracy due to the shadow caused by the high rise building.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.1-15
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• 2015

Urban flooding threatens human beings and facilities with chemical and physical hazards since the beginning of human civilization. Recent studies have emphasized the integration of data and models for effective urban flood inundation modeling. However, the model set-up process is tend to be time consuming and to require a high level of data processing skill. Furthermore, in spite of the use of high resolution grid data, inundation depth and velocity are varied with building treatment methods in 2-D inundation model, because undesirable grids are generated and resulted in the reliability decline of the simulation results. Thus, it requires building generalization process or enhancing building orthogonality to minimize the distortion of building before converting building footprint into grid data. This study aims to develop building generalization method for 2-dimensional inundation analysis to enhance the model reliability, and to investigate the effect of building generalization method on urban inundation in terms of geographical engineering and hydraulic engineering. As a result to improve the reliability of 2-dimensional inundation analysis, the building generalization method developed in this study should be adapted using Digital Building Model(DBM) before model implementation in urban area. The proposed building generalization sequence was aggregation-simplification, and the threshold of the each method should be determined by considering spatial characteristics, which should not exceed the summation of building gap average and standard deviation.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.142-154
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• 2010

The purpose of this study is to analyze the effects of various spatial characteristics on the land surface temperature and to grasp the characteristics of thermal environment by types of urban area in Changwon, Gyeongsangnam-do. The spatial data were consisted LST, normalized difference built-up index(NDBI) and normalized difference vegetation index(NDVI) obtained from Landsat 5 TM and land use and land cover map classified from high resolution digital aerial photograph($10cm{\times}10cm$). The unit space for spatial analysis was built by $500m{\times}500m$ Vector GRID. According to the results of estimation of relationship between thermal environment and spatial characteristics, LST had the highest positive correlation with NDBI by 0.929 and had high positive correlation with impervious area ratio by 0.857. In order to analysis of thermal environment on land use, types of urban area were classified by 4 of residential focus area, industrial focus area, green focus area and mixed area. According to the results of analysis, mean LST of industrial focus area was showed the highest by $21.10^{\circ}C$. But mean LST of green focus area was analyzed the lowest by $18.85^{\circ}C$. In conclusion, the results of this study investigated the effects of spatial characteristics on urban thermal environment and can provide methods and basic informations about land use planning and development density restriction for reduction of urban heat.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.28-35
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• 2006

An accurate prediction of budburst in grapevines is indispensable for vineyard frost warning system operations in spring because cold tolerance depends heavily on phonology. However, existing frost warning systems utilize only daily minimum temperature forecasts since there is no way to estimate the site-specific phonology of grapevines. A budburst estimation model based on thermal time was used to project budburst dates of two grapevine cultivars (Kyoho and Campbell Early), and advisories were issued depending on phonology as well as temperature. A 'warning' is issued if two conditions are met: the forecasted daily minimum temperature falls below $-1.5^{\circ}C$ and the estimated phonology is within the budburst period. A 'watch' is issued for a temperature range of -1.5 to $+1.5^{\circ}C$ with the same phonology condition. Validation experiments were done at 8 vineyards in Anseong in spring 2005, and the results showed a good agreement with the observations. This method was applied to the climatological normal year (1971-2000) to determine sites with high frost risk at a 30 m grid cell resolution. Among 608,585 grid cells constituting Anseong, 1,059 cells were identified as high risk for growing Kyoho and 2,788 cells for Campbell Early.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.1
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• pp.20-25
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• 2020

Spatial simulation of crop growth often requires application of management conditions to each cell. In particular, it is of great importance to determine the temperature conditions during the nursery period for rice seedlings, which would affect heading date projections. The objective of this study was to determine the value of TMPSB, which is the parameter of ORYZA2000 model to represent temperature increase under a plastic tunnel during the rice seedling periods. Candidate values of TMPSB including 0℃, 2℃, 5℃, 7℃ and 9℃ were used to simulate rice growth and yield. Planting dates were set from mid-April to mid-June. The simulations were performed at four sites including Cheorwon, Suwon, Seosan, and Gwangju where climate conditions at rice fields common in Korea can be represented. It was found that the TMPSB values of 0℃ and 2℃ resulted in a large variation of heading date due to low temperature occurred in mid-April. When the TMPSB value was >7℃, the variation of heading date was relatively small. Still, the TMPSB value of 5℃ resulted in the least variation of heading date for all the planting dates. Our results suggested that the TMPSB value of 5℃ would help reasonable assessment of climate change impact on rice production when high resolution gridded weather data are used as inputs to ORYZA2000 model over South Korea.