• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.36-44
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• 2006

In this study, we constructed a forest fire danger map in the Yeongdong area of Gangwon-do and Northeastern area of Gyeongsangbuk-do using a forest fire rating model and geographical information system (GIS). We investigated the appropriate positions of the automatic weather station (AWS) and a comprehensive network solution (a system including measurement, communication and data processing) for the establishment of an optimum mountain meteorological observation network system (MMONS). Also, we suggested a possible plan for combining the MMONS with unmanned monitoring camera systems and wireless relay towers operated by local governments and the Korea Forest Service for prevention of forest fire.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.3
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• pp.148-156
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• 2011

The purpose of this study is to analyze the patterns of forest fire possibly related with Asian dust event and carry out a correlation analysis between forest fire occurrence and existence or not of the Asian dust event during dry seasons i.e. February to May in 2000 to 2008. To study the correlation of forest fire and Asian dust, we surveyed information of Asian dust observations, forest fire statistics, fire danger rating index, weather data such as temperature, relative humidity and wind speed of the day occurring the forest fire. As a consequence of analysis, the regional frequency of Asian dust was the highest in Gyeonggi and Chungbuk divisions. Frequencies of forest fire occurrence by the Asian dust events were the highest in the day before three days of the Asian dust event. The highest frequent regions of forest fire occurrence were district of boundary line between Gyeonggi and Western of Gangwon, Chungbuk and Gyeonbuk inland. The correlation between forest fire and fire danger rating index showed the high correlation with the day before three days and after three days of the Asian dust event. These correlation coefficients were 0.50038 and 0.53978 to 1% significance level. The result of analysis between the frequency of forest fire occurrence and wind speed had a highly negative relationship at all the Asian dust days, the day before and after three days. The correlation coefficients had been -0.58623 to -0.61245 to 1% significance level. Relative humidity showed a little of negative relationship with forest fire occurrence in -0.2568(p ${\leq}$ 0.01) for the Asian dust day and -0.35309(p ${\leq}$ 0.01) for next three days. Moreover, at the day before three days of Asian dust events, it was -0.23701 to 1% significance level. However, the mean temperature did not correlate with frequency of forest fire occurrence by Asian dust events at all.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.3
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• pp.1-12
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• 2016

This study aimed to interpret the fundamental cause of road-kill occurrences and analyzed spatial characteristics of the road-kill locations from Route 44 in Seorak National Park, Korea. Logistic regression analysis was utilized for backward elimination on variables. Seorak National Park Service has constructed GIS-data of 81 road-kill occurrences from 2008 to 2013 and these data were assigned as dependent variables in this study. Considered as independent variables from previous studies and field surveys, vegetation age-class, distance to streams, coverage of fences and retaining walls, and distance to building sites were assigned as road-kill impact factors. The coverage of fences and retaining walls(-1.0135) was shown as the most influential factor whereas vegetation age-class(0.0001) was the least influential among all of the significant factor estimates. Accordingly, the rate of road-kill occurrence can increase as the distance to building sites and stream becomes closer and vegetation age-class becomes higher. The predictive accuracy of road-kill occurrence was shown to be 72.2% as a result of analysis, assuming as partial causes of road-kill occurrences reflecting spatial characteristics. This study can be regarded as beneficial to provide objective basis for spatial decision making including road-kill occurrence mitigation policies and plans in the future.

• Land and Housing Review
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• v.2 no.4
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• pp.517-528
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• 2011

Indiscreet developments cause environmental problems in major cities of Seoul Metropolitan Area. Among the environmental problems, the air pollution leads the citizens' physical and economic damages. Therefore, it needs to predict how much air pollutant which is emitted from human activities can be carried by urban environment, then to examine the reasonable level of urban development This study assumed that the air pollution is represented differently by the amount of emission. With the assumption, the acceptable air pollutant emission which keeps the air quality under the environmental standard is estimated, then the proper population is calculated in the case of Gwacheon, Gyeonggi. The result is as follow: First, air pollution concentrations of CO, $NO_2$, $SO_2$ which are estimated by using IDW interpolation of GIS don't excess the air environmental standard. Second, the result of correlation analysis between air pollutant emission and air pollution concentration shows that CO and $NO_2$ has high correlationship with total source of pollution and linear source of pollution, and $SO_2$ with linear source of pollution. Third, the results of regression analysis show that the acceptable population is bigger that the real population in the case of CO, and with the estimation of $NO_2$ and $SO_2$, the current population in the urban center and boundaries where the residential and commerce land uses are concentrated is bigger than the acceptable population. The consequence of this study is that the estimation of carrying capacity can suggest the acceptable human activities which keep the air quality under the environmental standard. This can leads the sustainable urban development by control the human activities under the carrying capacity of urban environment.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.34-47
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• 2009

Rapid urbanization is causing environmental and ecological damage, development thoughtless for the environment, and social and economical issues. It is important to grasp urban growth situations and characteristics, reflect them, and establish a policy for the solution of issues pursuant to urbanization and the sustainable and efficient development of national land. This research aims to be used as basic data in establishing an urban policy by analyzing the situations and characteristics of urban growth for the past 20 years in our entire country rather than an existing district. For this, some urban districts were sampled using a 1980s and 2000s version of land cover map produced by Ministry of Environment, and then pattern analysis for urban growth by administrative district ranks was conducted using GIS and a statistical technique. As a result, the development zone area after 1980s has increased by 2.5 times as compared to that before 1980s, and especially in the farm villages neighboring the national capital region, it has increased by 21.2 times. Special cities and metropolitan cities were developed at the districts being low in altitude, close to the principal road and the major downtown, high in road ratio, and restricted environmentally, ecologically and legally, and were diverted from mountains, forests and grassland to urban land. On the other hand, farm villages neighboring a large city, farm villages neighboring the national capital region, and local farm villages were developed at the districts being high in altitude, far from the principal road and the major downtown, low in road ratio, and not restricted environmentally, ecologically and legally, and were diverted from farmland to urban land. That is, it can be seen that urban development has been actively realized despite the unfavorable topographical conditions in the suburban districts due to lack of available land and various regulations and policies as urban growth around big cities expands.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.1-24
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• 2014

This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scenarios. The secondary impact of the weather extreme on food security in the developing world is also assessed using trend analysis. Many studies have reported on the significant reduction in maize production in the USA due to the extreme weather event (combined heat wave and drought) that occurred in 2012. However, most of these studies focused on yield and did not assess the potential effect of weather extremes on food prices and security. The overall goal of this study was to use geo-spatial crop modeling and trend analysis to quantify the impact of weather extremes on both yield and, followed food security in the developing world. We used historical weather data for severe extreme events that have occurred in the USA. The data were obtained from the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA). In addition we used five climate scenarios: the baseline climate which is typical of the late 20th century (2000s) and four future climate scenarios which involve a combination of two emission scenarios (A1B and B1) and two global circulation models (CSIRO-Mk3.0 and MIROC 3.2). DSSAT 4.5 was combined with GRASS GIS for geo-spatial crop modeling. Simulated maize grain yield across all affected regions in the USA indicates that average grain yield across the USA Corn Belt would decrease by 29% when the weather extremes occur using the baseline climate. If the weather extreme were to occur under the A1B emission scenario in the 2050s, average grain yields would decrease by 38% and 57%, under the CSIRO-Mk3.0 and MIROC 3.2 global climate models, respectively. The weather extremes that occurred in the USA in 2012 resulted in a sharp increase in the world maize price. In addition, it likely played a role in the reduction in world maize consumption and trade in 2012/13, compared to 2011/12. The most vulnerable countries to the weather extremes are poor countries with high maize import dependency ratios including those countries in the Caribbean, northern Africa and western Asia. Other vulnerable countries include low-income countries with low import dependency ratios but which cannot afford highly-priced maize. The study also highlighted the pathways through which a weather extreme would affect food security, were it to occur in 2050 under climate change. Some of the policies which could help vulnerable countries counter the negative effects of weather extremes consist of social protection and safety net programs. Medium- to long-term adaptation strategies include increasing world food reserves to a level where they can be used to cover the production losses brought by weather extremes.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.828-836
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• 2010

This study was conducted to evaluate soil erosion risk with a standard unit watershed in the upper Han river basin using the spatial soil erosion map according to the change of landuse. The study area is 14,577 $km^2$, which consists of 10 subbasins, 107 standard unit watersheds. Total annual soil loss and soil loss per area estimated were $895{\times}10^4\;Mg\;yr^{-1}$ and 6.1 Mg $ha^{-1}\;yr^{-1}$, respectively. A result of analysis with a subbasin as a unit showed that annual soil losses and soil loss per area in Namhan river basins was more than in Bukhan river ones. Predicted annual soil loss according to the landuse ranked as Forest & Grassland > Upland ${\gg}$ Urban & Fallow area > Paddy field > Orchard. Upland area covered 6.2% of the study area, but the contribution of total annul soil loss was 40.6% and that of Forest & Grassland was 44.2%. As a evaluation of soil erosion risk using the spatial soil erosion map, we could precisely conformed the potential hazardous region of soil erosion in each unit watersheds. The ratio of regions, graded as higher "Moderate" for annual soil loss, were respectively 8.7%, 7.9% and 7.8% in 1001, 1002 and 1003 subbasins in Namhan river basin. Most landuse of these area was upland, and these area is necessary to establish soil conservation practices to reduce soil erosion based on the field observation.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1177-1186
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• 2021

As the Arctic melt ponds play an important role in determining the interannual variation of the sea ice extent and changes in the Arctic environment, it is crucial to monitor the Arctic melt ponds with high accuracy. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), which is the NASA's latest altimeter satellite based on the green laser (532 nm), observes the global surface elevation. When compared to the CryoSat-2 altimetry satellite whose along-track resolution is 250 m, ICESat-2 is highly expected to provide much more detailed information about Arctic melt ponds thanks to its high along-track resolution of 70 cm. The basic products of ICESat-2 are the surface height and the number of reflected photons. To aggregate the neighboring information of a specific ICESat-2 photon, the segments of photons with 10 m length were used. The standard deviation of the height and the total number of photons were calculated for each segment. As the melt ponds have the smoother surface than the sea ice, the lower variation of the height over melt ponds can make the melt ponds distinguished from the sea ice. When the melt ponds were extracted, the number of photons per segment was used to classify the melt ponds covered with open-water and specular ice. As photons are much more absorbed in the water-covered melt pondsthan the melt ponds with the specular ice, the number of photons persegment can distinguish the water- and ice-covered ponds. As a result, the suggested melt pond detection method was able to classify the sea ice, water-covered melt ponds, and ice-covered melt ponds. A qualitative analysis was conducted using the Sentinel-2 optical imagery. The suggested method successfully classified the water- and ice-covered ponds which were difficult to distinguish with Sentinel-2 optical images. Lastly, the pros and cons of the melt pond detection using satellite altimetry and optical images were discussed.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.83-98
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• 2021

Urban green space is an important component for enhancing urban ecosystem health. Thus, identifying the spatial structure of urban green space is required to manage a healthy urban ecosystem. The Ministry of Environment has provided the level 3 land cover map(the highest (1m) spatial resolution map) with a total of 41 classes since 2010. However, specific urban green information such as street trees was identified just as grassland or even not classified them as a vegetated area in the map. Therefore, this study classified detailed urban green information(i.e., tree, shrub, and grass), not included in the existing level 3 land cover map, using two types of high-resolution(<1m) remote sensing data(i.e., airborne LiDAR and RGB ortho imagery) in Suwon, South Korea. U-Net, one of image segmentation deep learning approaches, was adopted to classify detailed urban green space. A total of three classification models(i.e., LRGB10, LRGB5, and RGB5) were proposed depending on the target number of classes and the types of input data. The average overall accuracies for test sites were 83.40% (LRGB10), 89.44%(LRGB5), and 74.76%(RGB5). Among three models, LRGB5, which uses both airborne LiDAR and RGB ortho imagery with 5 target classes(i.e., tree, shrub, grass, building, and the others), resulted in the best performance. The area ratio of total urban green space(based on trees, shrub, and grass information) for the entire Suwon was 45.61%(LRGB10), 43.47%(LRGB5), and 44.22%(RGB5). All models were able to provide additional 13.40% of urban tree information on average when compared to the existing level 3 land cover map. Moreover, these urban green classification results are expected to be utilized in various urban green studies or decision making processes, as it provides detailed information on urban green space.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.161-176
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• 2021

In this study, one of the distributed hydrologic models, VELAS, was used to analyze the variation of hydrologic elements based on water balance analysis to evaluate the groundwater recharge in more detail than the annual time scale for the past and future. The study area is located in Yanggok-ri, Seobu-myeon, Hongseong-gun, Chungnam-do, which is very vulnerable to drought. To implement the VELAS model, spatial characteristic data such as digital elevation model (DEM), vegetation, and slope were established, and GIS data were constructed through spatial interpolation on the daily air temperature, precipitation, average wind speed, and relative humidity of the Korea Meteorological Stations. The results of the analysis showed that annual precipitation was 799.1-1750.8 mm, average 1210.7 mm, groundwater recharge of 28.8-492.9 mm, and average 196.9 mm over the past 18 years from 2001 to 2018 in the study area. Annual groundwater recharge rate compared to annual precipitation was from 3.6 to 28.2% with a very large variation and average 14.9%. By the climate change RCP 8.5 scenario, the annual precipitation from 2019 to 2100 was 572.8-1996.5 mm (average 1078.4 mm) and groundwater recharge of 26.7-432.5 mm (average precipitation 16.2%). The annual groundwater recharge rates in the future were projected from 2.8% to 45.1%, 18.2% on average. The components that make up the water balance were well correlated with precipitation, especially in the annual data rather than the daily data. However, the amount of evapotranspiration seems to be more affected by other climatic factors such as temperature. Groundwater recharge in more detailed time scale rather than annual scale is expected to provide basic data that can be used for groundwater development and management if precipitation are severely varied by time, such as droughts or floods.