• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.123-123
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• 2020

The present study is aimed to correcting radar-based mean areal precipitation forecasts to improve urban flood predictions and uncertainty analysis of water levels contributed at each stage in the process. For this reason, a long short-term memory (LSTM) network is used to reproduce three-hour mean areal precipitation (MAP) forecasts from the quantitative precipitation forecasts (QPFs) of the McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation (MAPLE). The Gangnam urban catchment located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 24 heavy rainfall events, 22 grid points from the MAPLE system and the observed MAP values estimated from five ground rain gauges of KMA Automatic Weather System. The corrected MAP forecasts were input into the developed coupled 1D/2D model to predict water levels and relevant inundation areas. The results indicate the viability of the proposed framework for generating three-hour MAP forecasts and urban flooding predictions. For the analysis uncertainty contributions of the source related to the process, the Bayesian Markov Chain Monte Carlo (MCMC) using delayed rejection and adaptive metropolis algorithm is applied. For this purpose, the uncertainty contributions of the stages such as QPE input, QPF MAP source LSTM-corrected source, and MAP input and the coupled model is discussed.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1635-1640
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• 2017

In this paper, a hierarchical image tree model for weather classification is defined in a single outdoor image, and a weather classification algorithm using image intensity and k-mean segmentation image is proposed. In the first level of the hierarchical image tree model, the indoor and outdoor images are distinguished. Whether the outdoor image is daytime, night, or sunrise/sunset image is judged using the intensity and the k-means segmentation image at the second level. In the last level, if it is classified as daytime image at the second level, it is finally estimated whether it is sunny or foggy image based on edge map and fog rate. Some experiments are conducted so as to verify the weather classification, and as a result, the proposed method shows that weather features are effectively detected in a given image.

• 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.

• KIEAE Journal
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• v.3 no.1
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• pp.5-12
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• 2003

Using the wind, we can get a thermal comfort in summer. In winter we must shut out the wind. To achieve sustainable environmental building design, especially wind data is very important. The wind direction and wind velocity of 32 cities were analyzed to suggest the wind map of Korea. The weather data which was used in this paper was from National Weather Service(19711.1~2000.12.31). The results of this study are 1) The monthly wind velocity of Seoul is 1.1m/s-3.8m/s. 2) The maximum wind velocity could be estimated from the annual average wind velocity. The regression curve is Y(The maximum wind velocity)=6.369732 X(annual average wind velocity) + 6.391668 (P< 9.66E-12). 3) The wind velocity at the inland area which is far from 25km sea side is smaller than coastal area. The distance from the sea is major index of wind velocity. 4) The monthly wind direction was compared inland area with coastal area. 5) The uniform-velocity line on the Korean map was obtained.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1017-1026
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• 2015

Infrared (IR) target detection is one of the key technologies in Automatic Target Detection/Recognition (ATD/R) for military applications. However, IR sensors have limitations due to the weather sensitivity and atmospheric effects. In recent years, sensor information fusion study is an active research topic to overcome these limitations. SAR sensor is adopted to sensor fusion, because SAR is robust to various weather conditions. In this paper, a Boolean Map Visual Theory-Morphology (BMVT-M) method is proposed to detect targets in SAR and IR images. Moreover, we suggest the IR and SAR image registration and decision level fusion algorithm. The experimental results using OKTAL-SE synthetic images validate the feasibility of sensor fusion-based target detection.

• The Korean Journal of Ecology
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• v.19 no.5
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• pp.403-416
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• 1996

Global natural vegetation mapping (GNVM) system was developed for estimating potential forest area of the globe. With input of monthly mean temperature and monthly precipitation observed at weather stations, the system spherically interpolates them into 1°×1°grid points on a blobe, converts them into vegetation types, and produces a potential vegetation map and a potenital vegetation area. The spherical interpolation was based on negative exponential function fed from the constant radius stations with oval weighing method which is latitudinally elongated weighing in temperature and longitudinally elongated weighing in precipitation. The temperature values were corrected for altitude by applying a linear lapse-rate (0.65℃ / 100m) with reference to a built-in digital terrain map of the globe. The vegetation classification was based upon Koppen’s sKDICe. The potential forest area is estimated for 6.96 Gha (46.24％) of the global land area (15.05 Gha).

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.663-671
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• 2020

Recently, there have been many natural disasters in Korea, not only in forest areas but also in urban areas, and the national requirements for them are increasing. In particular, there is no pre-disaster information system that can systematically manage the collapse of the slope of the national highway. In this study, big data analysis was conducted on the factors causing slope collapse based on the detailed investigation report on the slope collapse of national roads in Gangwon-do and Gyeongsang-do areas managed by the Cut Slope Management System (CSMS) and the basic survey of slope failures. Based on the analysis results, a slope collapse risk prediction model was established through Adaboost, a classification-based machine learning model, reflecting the collapse slope location and weather information. It also developed a visualization map for the risk of slope collapse, which is a visualization program, to show that it can be used for preemptive disaster prevention measures by identifying the risk of slope due to changes in weather conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2292-2298
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• 2010

A mashup is a web page or application that uses and combines information, contents or Open APIs available on the web to create a new service. The mashup developed by the need not combination of simple information can contribute to new added-values with practicality and convenience. Thus, in this paper, we want to develop a RIA-based dynamic mashup service for the users considering weather forecast and marine information importantly. We design and implement the system that it can register a number of information about a domain dynamically through registration process based on the map and present a mark of domain location on the map and the information including internal environment, external environment and weather of related to the domain within a webpage. Implemented service need not require a tedious process visiting other web sites every time to confirm the relevant information because we can see simultaneously related information with a map within a page.

• Atmosphere
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• v.21 no.4
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• pp.405-414
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• 2011

In this study, the influence of a change in land use on the local weather fields is investigated around the Lake Shihwa area using synthetic land cover data and a high-resolution mesoscale model - the Weather Research and Forecasting (WRF). The default land cover data generally used in the WRF is based on the land use category of the United States Geological Survey (USGS), which erroneously presents most land areas of the Korean Peninsula as savannas. To revise such a fault, a multi-temporal land cover data, provided by the Ministry of Environment of Korea, was employed to generate a land cover map of 2005 subject to the land use in Korea at that time. A new land cover map of 1989, before the construction of the Lake Shihwa, was made based on the 2005 map and the Landsat 4-5 TM satellite images of two years. Over the areas where the land use had been changed (e.g., from sea to wetlands, towns, etc.) due to the Lake Shihwa development project, the skin temperature decreased by up to $8^{\circ}C$ in the winter case while increased by as much as $14^{\circ}C$ in the summer case. Changes in the water vapor mixing ratio were mostly affected by advection and topography in both seasons, with considerable increase in the summer case due to continuous sea breeze. Local decrease in water vapor occurred over high land use change areas and/or over downstream of such areas where alteration in wind fields were induced by changes in skin temperature and surface roughness at the areas of land use changes. The albedo increased by about 0.1% in the regions where sea was converted into wetland. In the regions where urban areas were developed, such as Songdo New Town and Incheon International Airport, the albedo increased by up to 0.16%.

• Spatial Information Research
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• v.20 no.6
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• pp.13-21
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• 2012

In this study, homogeneous regions for regional frequency analysis were identified using rainfall data from 61 observation points in Korea. The used data were gathered from 1980 to 2010. Self organizing map and K-means clustering based on Davies-Bouldin Index were used to make clusters showing similar rainfall patterns and to decide the optimum number of the homogeneous regions. The results from this analysis showed that the 61 observation points can be optimally grouped into 6 geographical clusters. Finally, the 61 observations points grouped into 6 clusters were mapped regionally using Thiessen polygon method.