• 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.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1819-1827
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• 2021

Land-use/cover change caused by rapid urbanization in South Korea is one of the concerns in flood risk management because groundwater recharge by precipitation hardly occurs due to an increase in impermeable surfaces in urban areas. This study investigated the hydrologic effects of land-use/cover on groundwater recharge in the Yeonje-gu district of Busan, South Korea. A statistical time series analysis was conducted with temporal variations of precipitation and groundwater level to estimate lag-time based on correlation coefficients calculated from auto-correlation function (ACF), cross-correlation function (CCF), and moving average (MA) at five sites. Landform and land-use/cover within 250 m radius of the monitoring wells(GW01, GW02, GW03, GW04, and GW05) at five sites were identified by land cover and digital map using Arc-GIS software. Long lag-times (CCF: 42-71 days and MA: 148-161 days) were calculated at the sites covered by mainly impermeable surfaces(GW01, GW03, and GW05) while short lag-times(CCF: 4 days and MA: 67 days) were calculated at GW04 consisting of mainly permeable surfaces. The results suggest that lag-time would be one of the good indicators to evaluate the effects of land-use/cover on estimating groundwater recharge. The results of this study also provide guidance on the application of statistical time series analysis to environmentally important issues on creating an urban green space for natural groundwater recharge from precipitation in the city and developing a management plan for hydrological disaster prevention.

• Journal of the Korean earth science society
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• v.42 no.3
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• pp.247-263
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• 2021

Climate change has been accelerating in coastal waters recently; therefore, the importance of coastal environmental monitoring is also increasing. Chlorophyll-a concentration, an important marine variable, in the surface layer of the global ocean has been retrieved for decades through various ocean color satellites and utilized in various research fields. However, the commonly used chlorophyll-a concentration algorithm is only suitable for application in clear water and cannot be applied to turbid waters because significant errors are caused by differences in their distinct components and optical properties. In addition, designing a standard algorithm for coastal waters is difficult because of differences in various optical characteristics depending on the coastal area. To overcome this problem, various algorithms have been developed and used considering the components and the variations in the optical properties of coastal waters with high turbidity. Chlorophyll-a concentration retrieval algorithms can be categorized into empirical algorithms, semi-analytic algorithms, and machine learning algorithms. These algorithms mainly use the blue-green band ratio based on the reflective spectrum of sea water as the basic form. In constrast, algorithms developed for turbid water utilizes the green-red band ratio, the red-near-infrared band ratio, and the inherent optical properties to compensate for the effect of dissolved organisms and suspended sediments in coastal area. Reliable retrieval of satellite chlorophyll-a concentration from turbid waters is essential for monitoring the coastal environment and understanding changes in the marine ecosystem. Therefore, this study summarizes the pre-existing algorithms that have been utilized for monitoring turbid Case 2 water and presents the problems associated with the mornitoring and study of seas around the Korean Peninsula. We also summarize the prospective for future ocean color satellites, which can yield more accurate and diverse results regarding the ecological environment with the development of multi-spectral and hyperspectral sensors.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.2
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• pp.20-29
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• 2019

The purpose of this study is to verify and reconstruct the record information for big old trees of Jeju on the basis of the precise map of Jeju island in 1918 which was produced 100 years ago. For the analysis of high altitude, coordinate system and georeferencing were performed by selecting representative points using ArcGIS. We extracted digitized information by using point extraction method and extracted attribute information based on legend type and relative size in map. Based on the map of the past 100 years ago, the present situation of the big old tree in Jeju was analyzed and their characteristics were analyzed. In addition, based on the information of the protected big old trees in present, we discussed the characteristics of past tree (1918), present tree (2019), and contribution of big old tree in Jeju landscape and vegetation. As a result, 1,013 individuals were distributed in Jeju Island 100 years ago. Even when it was intensive in the use of timber, the big old trees were protected, and contributed as a representative component of Jeju's unique landscape. The remaining distribution of Jeju's big old tree is 159 trees. As in the past, distribution has been confirmed around the lowlands, but declines in numbers are found throughout the island. The major factors for the decline of individuals are large-scale development projects such as reaching the limit of life, natural disturbance (typhoon, disease, pest, drought, etc.). However, it is presumed that a large number of individuals have played a leading role in shaping the current forests as contributing to important species sources in the restoration process of Jeju vegetation. However, it is presumed that a large number of individuals (405) have played a leading role in forming the present forest by contributing to the species pool in the restoration process of Jeju vegetation.

• Journal of Korean Society of Forest Science
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• v.107 no.4
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• pp.486-496
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• 2018

Pine wilt disease (PWD) in Gyeonggi province was first detected in Gwangju in 2007, and ever since has caused extensive damage. Insect vector and host tree in Gyeonggi province are Monochamus saltuarius and Pinus koraiensis, respectively, which are different from the southern region that consist of Monochamus alternatus and Pinus densiflora. Consequently, spread and mortality characteristics may be different, but our understanding is limited. In this research, we utilized the spatial data of newly infected trees in Gyeonggi province from 2008 to 2015 to analyze how it is related to various environmental and human factors, such as elevation, forest type, and road network. We also analyzed the minimum distance from newly infected tree to last year's closest infected tree to examine the dispersal characteristics based on new outbreak locations. Annual number of newly infected trees rapidly increased from 2008 to 2013, which then stabilized. Number of administrative districts with infected trees was 5 in 2012, 11 in 2013, and 15 in 2014. Most of the infected trees was Pinus koraiensis, with its proportion close to 90% throughout the survey period. Mean distance to newly infected trees dramatically decreased over time, from 4,111 m from 2012 to 2013, to approximately 600 m from 2013 to 2014 and 2014 to 2015. Most new infections occurred in higher elevation over time. Distance to road from newly infected trees continuously increased, suggesting that natural diffusion dispersal is increasingly occurring compared to human-influenced dispersal over time.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.5
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• pp.66-77
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• 2019

This study investigated the feasibility of wintering evergreen broad-leaf trees in the Incheon coastal area through a climate analysis. The coldest monthly mean air temperature ranged from $-2.9^{\circ}C{\sim}-1.6^{\circ}C$. The warmth index of the coastal area of Incheon ranged from $98.89^{\circ}C{\cdot}month-109.03^{\circ}C{\cdot}month$, while the minimum air temperature year ranged from $-13.9^{\circ}C{\sim}-3.6^{\circ}C$. This proved that the Incheon coastal area was not suitable for evergreen broad-leaf trees to grow as the warmth index ranges from $101.0^{\circ}C{\cdot}month{\sim}117.0^{\circ}C{\cdot}month$, and the temperature year-round is $-9.2^{\circ}C$ or higher. This suggests the coastal areas of Incheon is not suitable for the growth of evergreen broad-leaf trees, however some evergreen broad-leaf trees lived in some parts of the area. Wind speed reduction and temperature effect simulations were done using Landschaftsanalyse mit GIS program. As a result of the simulations of wind speed reduction and temperature effects affecting the evergreen broad-leaf trees, it was discovered that a coastal wind velocity of 8.6m/sec was alleviated to be 5m/sec~7m/sec when the wind reached the areas where evergreen broad-leaf trees were present. It was also discovered that species that grew in contact with buildings benefited from a temperature increase of $1.1^{\circ}C{\sim}3.4^{\circ}C$ due to the radiant heat released by the building. Simulation results show that the weather factors affecting the winter growth damages of evergreen broad-leaved trees were wind speed reduction and local warming due to buildings. The wind speed reduction by shielding and local warming effects by buildings have enabled the wintering of evergreen broad-leaved trees. Also, evergreen broad-leaved trees growing in the coastal area of Incheon could be judged to be gradually adapting to low temperatures in winter. This study reached the conclusion that the blockage of wind, and the proximity of buildings, are required for successfully wintering evergreen broad-leaf trees in the coastal area of Incheon.