• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.34-45
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• 2021

Weather is one of the important factors in the agricultural industry as it affects the price, production, and quality of crops. Upland crops are directly exposed to the natural environment because they are mainly grown in mountainous areas. Therefore, it is necessary to provide accurate weather for upland crops. This study examined the effectiveness of 12 forest soil factors to interpolate the weather in mountainous areas. The daily temperature and precipitation were collected by the Korea Meteorological Administration between January 2009 and December 2018. The Generalized Additive Model (GAM), Kriging, and Random Forest (RF) were considered to interpolate. For evaluating the interpolation performance, automatic weather stations were used as training data and automated synoptic observing systems were used as test data for cross-validation. Unfortunately, the forest soil factors were not significant to interpolate the weather in the mountainous areas. GAM with only geography aspects showed that it can interpolate well in terms of root mean squared error and mean absolute error. The significance of the factors was tested at the 5% significance level in GAM, and the climate zone code (CLZN_CD) and soil water code B (SIBFLR_LAR) were identified as relatively important factors. It has shown that CLZN_CD could help to interpolate the daily average and minimum daily temperature for upland crops.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1119-1130
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• 2021

Urban flooding caused by localized heavy rainfall with unstable climate is constantly occurring, but a system that can predict spatial flood information with weather forecast has not been prepared yet. The worst flood situation in urban area can be occurred with difficulties of structural measures such as river levees, discharge capacity of urban sewage, storage basin of storm water, and pump facilities. However, identifying in advance the spatial flood information can have a decisive effect on minimizing flood damage. Therefore, this study presents a methodology that can predict the urban flood map in real-time by using rainfall data of the Korea Meteorological Administration (KMA), the results of two-dimensional flood analysis and random forest (RF) regression model. The Ujeong district in Ulsan metropolitan city, which the flood is frequently occurred, was selected for the study area. The RF regression model predicted the flood map corresponding to the 50 mm, 80 mm, and 110 mm rainfall events with 6-hours duration. And, the predicted results showed 63%, 80%, and 67% goodness of fit compared to the results of two-dimensional flood analysis model. It is judged that the suggested results of this study can be utilized as basic data for evacuation and response to urban flooding that occurs suddenly.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.267-279
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• 2023

This research assessed the feasibility of using high-resolution aerial images and deep learning algorithms for estimating the land-use and land-cover areas at the Approach 3 level, as outlined by the Intergovernmental Panel on Climate Change. The results from different sampling densities of high-resolution (51 cm) aerial images were compared with the land-cover map, provided by the Ministry of Environment, and analyzed to estimate the accuracy of the land-use and land-cover areas. Transfer learning was applied to the VGG16 architecture for the deep learning model, and sampling densities of 4 × 4 km, 2 × 4 km, 2 × 2 km, 1 × 2 km, 1 × 1 km, 500 × 500 m, and 250 × 250 m were used for estimating and evaluating the areas. The overall accuracy and kappa coefficient of the deep learning model were 91.1% and 88.8%, respectively. The F-scores, except for the pasture category, were >90% for all categories, indicating superior accuracy of the model. Chi-square tests of the sampling densities showed no significant difference in the area ratios of the land-cover map provided by the Ministry of Environment among all sampling densities except for 4 × 4 km at a significance level of p = 0.1. As the sampling density increased, the standard error and relative efficiency decreased. The relative standard error decreased to ≤15% for all land-cover categories at 1 × 1 km sampling density. These results indicated that a sampling density more detailed than 1 x 1 km is appropriate for estimating land-cover area at the local level.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.247-256
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• 2008

Recently, natural disasters like flooding damages have frequently occurred as to typhoons and local downpours affected by the climate changes. Many researches have actively been studied in analysing runoff models, the verification of their parameters, and the inflow on surfaces in order to lessen the damages. However, much time and effort needs in generating input files of the models in most current researches. Therefore, in this paper we develop a system for generating a simulation input data automatically. This system is connected to the EPA-SWMM based on the spatial data in the UIS systems and consists the simulation module for analysing urban flooding and the SWMM simulator module. Also, we construct a prototype using a range of regular inundation to generate a simulation input file. This system gives advantages showing inundation areas based on the map viewer as well as lessening errors of input data and simulation time.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.174-179
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• 2017

Soil parameters are required inputs to crop models, which estimate crop yield under a given environment condition. The Korean Soil Information System (KSIS), which provides detailed soil profile record of 390 soil series in the HTML (HyperText Markup Language) format, would be useful to prepare soil input files. Korean Soil Information System Processing Tool (KSISPT) was developed to aid generation of soil input data based on the KSIS database. Java was used to implement the tool that consists of a set of modules for parsing the HTML document of the KSIS, storing data required for preparing soil input file, calculating additional soil parameter, and writing soil input file to a local disk. Using the automated soil data preparation tool, about 940 soil input data were created for the DSSAT model and the ORYZA 2000 model, respectively. In combination with soil series distribution map at 30m resolution, spatial analysis of crop yield could be projected under climate change, which would help the development of adaptation strategies.

• The Journal of Engineering Geology
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• v.28 no.1
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• pp.35-45
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• 2018

Imaging technologies are applied at various geological scales including pore scale, core scale and intermediate scale in order to characterize pore space of rocks as well as to map the fluid distribution in porous media. This technical report presents experimental results using core-flooding apparatus suited with imaging technology. Three different core samples, that are homogeneous, fractured and heterogeneous cores, were used to assess the two-phase fluid migration behavior as $CO_2$ displaces resident brine. We show that imaging technology can be effective in characterizing salt-precipitation, capillary pressure and spatio-temporal variation of trapping mechanisms.

• Fashion & Textile Research Journal
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• v.15 no.6
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• pp.993-999
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• 2013

This study aimed to measure the amount of sweating on 12 parts of the upper body using absorption fabric and analyze subjective sensations. The study was conducted with 9 male subjects in climate chamber controled at $30{\pm}0.5^{\circ}C$, and $55{\pm}5%$ RH. The result was that sweating amount of the upper back part was significantly more than upper front part. We assumed that forced convection flow cased by exercise decreased the sweating rate in the front. The skin temperature of upper front body rapidly decreased as soon as exercise starts and gradually increased with cessation of exercise. On the other hand, the skin temperature of palm increased with exercise and showed continuous increasing even exercise stopping all the experimental period. This is caused by thermoregulatory responses through vasodilatation on the peripheral area. Subjective sensations, such as thermal sensation, wet sensation, and thermal comfort showed the highest score at the time of exercise stop. This means the subjects felt more hot, wet, and uncomfortable after exercise stopped. Bur after wiping of sweat, subjective sensation scores were recovered rapidly. The present study has provided more detailed information on the upper body sweat distribution than previously available, which can be used in clothing design, thermo-physiological modeling, and thermal manikin design. We also think that results of the present study will play an important role in making the sweat distribution map.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.121-131
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• 2018

Climate change has caused changes in environmental factors that have a direct impact on agriculture such as temperature and precipitation. The meteorological disaster that has the greatest impact on agriculture is drought, and its forecasts are closely related to agricultural production and water supply. In the case of terrestrial data, the accuracy of the spatial map obtained by interpolating the each point data is lowered because it is based on the point observation. Therefore, acquisition of various meteorological data through satellite imagery can complement this terrestrial based drought monitoring. In this study, Evaporative Stress Index (ESI) was used as satellite data for drought determination. The ESI was developed by NASA and USDA, and is calculated through thermal observations of GOES satellites, MODIS, Landsat 5, 7 and 8. We will identify the difference between ESI and other satellite-based drought assessment indices (Vegetation Health Index, VHI, Leaf Area Index, LAI, Enhanced Vegetation Index, EVI), and use it to analyze the drought in South Korea, and examines the applicability of ESI as a new indicator of agricultural drought monitoring.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.6
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• pp.838-848
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• 2013

The Community Multiscale Air Quality (CMAQ) model is capable of providing high quality atmospheric chemistry profiles through the utilization of high-resolution meteorology and emissions data. However, it cannot simulate air quality accurately if input data are not appropriate and reliable. One of the most important inputs required by CMAQ is the air pollutants emissions, which determines air pollutants concentrations during the simulation. For the CMAQ simulation of Korean peninsula, we, in general, use the Korean National Emission Inventory data which are estimated by Clean Air Policy Support System (CAPSS). However, since they are not provided by model-ready emission data, we should convert CAPSS emissions into model-ready data. The SMOKE is the emission model we used in this study to generate CMAQ-ready emissions. Because processing the emissions data is very monotonous and tedious work, we have developed CAPSS2SMOKE program to convert CAPSS emissions into SMOKE-ready data with ease and effective. CAPSS2SMOKE program consists of many codes and routines such as source classification code, $PM_{10}$ to $PM_{2.5}$ ratio code, map projection conversion routine, spatial allocation routine, and so on. To verify the CAPSS2SMOKE program, we have run SMOKE using the CAPSS 2009 emissions and found that the SMOKE results inherits CAPSS emissions quite well.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.1
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• pp.9-14
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• 2010

Recent increase in the strength and frequency of typoons due to climate change claims reconsideration of the design wind load in existing design codes for civil engineering structures in which the basic wind speed is estimated based on meteorological data by mid 1990s. In this paper, based on wind speed data at 76 observatories in Korea from 1961 through 2008, the basic wind speeds which can be utilized in designing civil engineering structures including buildings and bridges are estimated using the statistical process. The return period of the wind speed for each location is determined using the Gumbel distribution. The results for considered locations are compared to the existing design codes. Also, for design applications, the wind speed map, which classifies the country into four basic wind speed zones, is proposed using the resulting basic wind speeds.