• 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.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1653-1667
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• 2020

In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.109-130
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• 2022

The Vietnamese government has proposed contract farming through a new type of cooperative as an institutional innovation which aims to restructure the agricultural sector. However, policy changes often impact farmers, who bear the primary effects of the transition process. Understanding households' strategies for land use and livelihood is crucial for policymaking in the agricultural development field. This study was conducted in the rural Binh Dao commune in Central Vietnam. We analyzed household members' labor force changes and their livelihood behaviors after their participation in a contract farming scheme using qualitative analysis methods combined with geographic information system (GIS) support, based on secondary data and in-depth interviews of 190 farmers. Simultaneously, we created a digital map of the cooperative's production area to investigate changes in land use and production activities. The findings show that contract farming shaped the vertical coordination of the value chain from the farmers to the cooperative and agricultural product trading companies. Subsequently, it encouraged land use and labor efficiency due to mechanical support. In addition, it also increased productivity and protected farmers from market risks. However, despite its positive effects on agricultural productivity in this case, the contract farming scheme could not achieve the restructuring of the rural labor force toward non-agricultural sectors. Ironically, farmers in the Binh Dao commune tended to increase cultivable land during the agricultural restructuring program, rather than switching their labor forces to non-agricultural sectors. The lack of stable non-farming job opportunities in rural Vietnam results in challenges to the efficiency of agricultural restructuring programs. Consequently, farmers in the Binh Dao commune are still smallholder farmers, depending on the family labor force.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1125-1139
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• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.