• Economic Analysis
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• v.27 no.2
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• pp.71-123
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• 2021

In this study, we present a methodology and model to estimate land prices and the value of land assets in North Korea in the absence of any data about land characteristics from North Korean authorities. Using this framework, we experimentally make market price-based estimates for land assets across the entire urban area of North Korea. First, we estimate the determinants of land prices in South Korea using data on market prices of land from the late 1970s, when it was estimated that the income level gap between South Korea and North Korea wasn't relatively large, and from the early 1980s, when urbanization levels in both of them were similar. Second, we calculate land prices and their relative ratios for each city and urban area in North Korea around 2015 by substituting proxy variables of determinants of land prices derived through a geographic information analysis of North Korea into the function of land prices that we have already estimated. Finally, we estimate the value of land assets in urban areas across North Korea by combining the ratio of housing transaction prices surveyed in several cities in North Korea with the relative prices estimated in this research. As a result, land prices in urban areas in North Korea, looking at the relative ratio of price by city, are estimated to be the highest, at 100.00, in Tongdaewon district of Pyongyang, and to be the lowest, at 1.70, in Phungso county, Ryanggang Province. Meanwhile, the value of land assets in urbanized areas was estimated at $21.6 billion in 2015, which was 1.2 to 1.3 times the GDP of North Korea that year. This ratio is similar to South Korea's in the 1978-1980 period, when the South Korean economy grew at an average rate of 6%. Considering North Korea's growth rate of about 1% in the 2013-2014 period, its ratio of land assets to GDP appears very high.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.279-288
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• 2019

We evaluated the land cover classification performance of SegNet, which features semantic segmentation of aerial imagery. We selected four semantic classes, i.e., urban, farmland, forest, and water areas, and created 2,000 datasets using aerial images and land cover maps. The datasets were divided at a 8:2 ratio into training (1,600) and validation datasets (400); we evaluated validation accuracy after tuning the hyperparameters. SegNet performance was optimal at a batch size of five with 100,000 iterations. When 200 test datasets were subjected to semantic segmentation using the trained SegNet model, the accuracies were farmland 87.89%, forest 87.18%, water 83.66%, and urban regions 82.67%; the overall accuracy was 85.48%. Thus, deep learning-based semantic segmentation can be used to classify land cover.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.81-99
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• 2015

The acceleration of global warming has required better understanding of carbon cycles over local and regional areas such as the Korean peninsula. Since forests serve as a carbon sink, which stores a large amount of terrestrial carbon, there has been a demand to accurately estimate such forest carbon sequestration. In Korea, the National Forest Inventory(NFI) has been used to estimate the forest carbon stocks based on the amount of growing stocks per hectare measured at sampled location. However, as such data are based on point(i.e., plot) measurements, it is difficult to identify spatial distribution of forest carbon stocks. This study focuses on urban areas, which have limited number of NFI samples and have shown rapid land cover change, to estimate grid-based forest carbon stocks based on UNFCCC Approach 3 and Tier 3. Land cover change and forest carbon stocks were estimated using Landsat 5 TM data acquired in 1991, 1992, 2010, and 2011, high resolution airborne images, and the 3rd, 5th~6th NFI data. Machine learning techniques(i.e., random forest and support vector machines/regression) were used for land cover change classification and forest carbon stock estimation. Forest carbon stocks were estimated using reflectance, band ratios, vegetation indices, and topographical indices. Results showed that 33.23tonC/ha of carbon was sequestrated on the unchanged forest areas between 1991 and 2010, while 36.83 tonC/ha of carbon was sequestrated on the areas changed from other land-use types to forests. A total of 7.35 tonC/ha of carbon was released on the areas changed from forests to other land-use types. This study was a good chance to understand the quantitative forest carbon stock change according to the land cover change. Moreover the result of this study can contribute to the effective forest management.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.215-223
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• 2020

The objective of this study is to develop a prediction model of specific degradation using data mining classification especially for the rivers in South Korea river. A number of critical predictors such as erosion and sediment transport were extracted for the prediction model considering watershed morphometric characteristics, rainfall, land cover, land use, and bed material. The suggested model includes the elevations at the mid relative area of the hypsometric curve of watershed morphomeric characteristics, the urbanization ratio, and the wetland and water ratio of land cover factors as the condition factors. The proposed model describes well the measured specific degradation of the rivers in South Korea. In addition, the development model was compared with the existing models, since the existing models based on different conditions and purposes show low predictability, they have a limit about the application of Korean River. Therefore, this study is focusing on improving the applicability of the existing model

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.305-316
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• 2018

As the urbanization ratio increases, the heat environment in cities is becoming more important due to the urban heat island. In this study, the heat island spatial analysis was calculated and conducted for analysis of urban thermal environment of Sejong city, which was launched in 2012 and has been developed rapidly. To analyze the ratio and change rate of urban area, a multi temporal land cover map (2013 to 2015 and 2017) of study area is generated based on Landsat-8 OLI/TIRS (Operational Land Imager / Thermal Infrared Sensor) satellite imagery. Then, we select an TIR (Thermal Infrared) band from the two TIR bands provided by the Landsat-8, which is used for calculating the heat island potential, through the accuracy evaluation of the brightness temperature and AWS (Automatic Weathering Station) data. Based on the selected band and surface emissivity, land surface temperature is calculated and the estimated heat island potential change is analyzed. As a result, the land surface temperature of the high ratio and change rate of urban area was significantly higher than the surrounding area around $3^{\circ}C$ to $4^{\circ}C$, and the heat island potential was also higher around $4^{\circ}C$ to $5^{\circ}C$. However, the heat island phenomenon was alleviated in urban areas with high rate of change that also show high green area ratio. Therefore, we demonstrated that dense urban area increases the possibility of inducing heat island, but it can mitigate the heat island through green areas.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.2
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• pp.15-23
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• 2012

This study was accomplished by analyzing the change of land cover pattern in high-rise buildings in Korea. For this study, we selected 15 locations of high-rise buildings. The ratio of average building coverage and paved area was 79.7%, and both green and water area were low, relatively. The biotope area factor of the site showed low percentage by 15.90% due to the underground space development. As a result of correlation analysis between the time of construction and land-cover type, building coverage has been decreased according to the stream of time. However, biotope area factor has been increased And, the paved area has m correlation. It was identified that reducing paved area is effective to enhance the ecological functions of a high-rise building outdoor.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.162-162
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• 2020

토양수분은 TDR(Time Domain Reflectometry)이나 Tensiometer 등의 장비를 이용하여 측정을 시행하고 있으나, 이를 위해서는 많은 인력과 경제적 자원이 소비될 뿐만 아니라 시공간적으로 측정할 수 있는 범위에 한계가 있다. 지상 관측의 대안으로 MIRAS(Microwave Imaging Radiometer with Aperture Synthesis)나 SMAP(Soil Moisture Active Passive), AMSR2(Advanced Microwave Scanning Radiometer 2) 등의 수동 마이크로파 위성 센서를 이용한 공간 토양수분 관측이 수행되었으나, 낮은 공간 해상도(9~36km)는 지역 규모의 토양수분 분포를 나타내기 충분하지 않고, 높은 불확실성을 내포하고 있다. 본 연구에서는 금강 상류의 용담댐 유역(930.0㎢)을 대상으로 Sentinel-1 C-band SAR(Synthetic Aperture Radar) 영상을 이용한 토지 피복 및 토양 속성을 고려한 10m 해상도의 토양수분 산출을 수행하였다. 용담댐 유역은 산림 79.7%, 논 9.0%, 밭 5.4%, 주거지 2.9%의 토지 피복 비율을 가지며 토양은 사양토(66.6%)와 양토(20.9%)가 우세하다. Sentinel-1 C-band SAR 영상은 SeNtinel Application Platform(SNAP)을 이용하여 전처리 후, 후방산란계수로 변환하였다. 토양수분 알고리즘은 TU-Wien change detection algorithm과 Regression model을 활용하였고, 검증을 위한 실측 토양수분 자료는 한국수자원공사(K-water)에서 제공하는 5년(2014~2018)간의 토양수분 관측자료를 이용하였다. 산출된 토양수분은 결정계수(Coefficient of determination, R²) 및 평균제곱근오차(Root Mean Square Error, RMSE)를 이용하여 실측 토양수분과 비교하였다. Sentinel-1 C-band SAR 영상을 이용한 고해상도의 토양수분 산출은 토지 피복 및 토양 속성을 고려한 지역 규모의 공간 토양수분 분포 및 시간적 변화를 표현 가능할 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.144-144
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• 2015

본 연구는 서울과 5대 광역시를 대상으로 (1) 과거추세가 연장되는 시나리오와 (2) 최근 활발하게 논의되고 있는 스마트 성장, 컴펙트 개발 등을 고려한 도시성장 시나리오를 전제로 미래의 토지이용의 변화를 예측하였다. 토지이용 변화 예측에는 로지스틱 회귀 분석을 기반으로 한 CLUE-s(Conservation of Land Use and its Effects at Small regional extent) 모형을 이용하였다. 토지이용 변화예측을 위해 WAMIS(WAter Management Information System)에서 제공하는 1975년부터 2000년까지의 5년 단위의 토지이용별 통계자료와 환경부에서 제공하는 2008년 토지이용도를 구축하였으며, 각 토지이용 항목은 총 6가지(시가지, 수역, 산림, 논, 밭, 초지)로 재분류하였다. 도시성장 시나리오는 지자체 조례에 따른 물리적 개발기준과 국토 환경성 평가 지도를 바탕으로 개발 제한 구역을 설정하고, 미래 인구변화와 토지수요 수요량 추정을 통해 미래 토지이용 변화 예측 시나리오를 구축하였다. 또한 도로망, 하천망과 유효 토심, 토양통 등을 고려한 토양 속성을 토지 피복 변화 예측을 위한 모형의 동적 요소(driving factor)로 대입하였다. 두 가지의 시나리오를 통해 미래 토지 이용 변화 예측결과 각 시나리오에 따라 확연히 다른 양상의 토지이용 변화 패턴을 보였다. 과거추세가 연장되는 시나리오에서는 물리적인 토지개발 기준 범위 내에서 무작위로 토지이용이 변화하며 시가지가 급속하게 성장하는 패턴을 보여주었다. 반면, 도시성장 시나리오를 전제로 하였을 경우 기존의 시가지와 연계하여 인근에 위치한 미개발지가 시가지로 변화하는 양상을 보였으며, 로그 추세로 증가 혹은 감소하는 패턴에 따라 변화폭이 줄어들며 종래에는 각 토지이용의 변화량이 0%로 수렴하는 모습을 보였다. 토지이용 변화 비율은 두 가지 시나리오 모두 주로 산지와 농지가 감소하고 시가지가 증가하는 모습을 보였다. 본 연구를 통해 구축한 미래 토지이용 변화 시나리오는 수문생태계에 큰 영향을 주는 지표의 변화에 대해 회귀분석을 기반으로 정량적인 예측을 가능케 함으로써 기후변화 시나리오 등 다양한 미래 예측 시나리오와의 접목을 통해 미래 수자원 예측 연구에 활용도를 높일 수 있을 것이라 기대한다.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.635-646
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• 2018

This study sought to identify the characteristics of seasonal concentration differences of particulate matter influenced by land cover types associated with particulate matter emission and reductions, namely forest and urbanized regions. PM10 and PM2.5 was measured with quantitative concentration in 2016 on 23 urban air monitoring stations in Seoul, classified the stations into 3 groups based on the ratio of urbanized and forest land covers within a range of 3km around station, and analysed the differences in particulate matter concentration by season. The center values for the urbanized and forest land covers by group were 53.4% and 34.6% in Group A, 61.8% and 16.5% in Group B, and 76.3% and 6.7% in Group C. The group-specific concentration of PM10 and PM2.5 by season indicated that the concentration of Group A, with high ratio of forests, was the lowest in all seasons, and the concentration of Group C, with high ratio of urbanized regions, had the highest concentration from spring to autumn. These inter-group differences were statistically significant. The concentration of Group C was lower than Group B in the winter; however, the differences between Groups B to C in the winter were not statistically significant. Group A concentration compared to the high-concentration groups by season was lower by 8.5%, 11.2%, 8.0%, 6.8% for PM10 in the order of spring, summer, autumn and winter, and 3.5%, 10.0%, 4.1% and 3.3% for PM2.5. The inter-group concentration differences for both PM10 and PM2.5 were the highest in the summer and grew smaller in the winter, this was thought to be because the forests' ability to reduce particulate matter emissions was the most pronounced during the summer and the least pronounced during the winter. The influence of urbanized areas on particulate matter concentration was lower compared to the influence of forests. This study provided evidence that the particulate matter concentration was lower for regions with higher ratios of forests, and subsequent studies are required to identify the role of green space to manage particulate matter concentration in cities.

• Ecology and Resilient Infrastructure
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• v.6 no.2
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• pp.79-88
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• 2019

In order to study the water quality status and its causal environmental factors, the water quality variables of chemical oxygen demand (COD), chlorophyll a (Chl a), Total phosphorus (TP), and total nitrogen (TN), the hydrogeomorphologic variables of water level fluctuation, total water storage, dam elevation, watershed area, and shoreline development index, and the land cover variables of forest, agricultural area, and urbanized area in the watershed were investigated in total 73 reservoirs with various operational purposes, water level fluctuation and geographical distribution in South Korea. The water quality was more eutrophic in the reservoirs of the more urbanized and agricultural area in the watershed, the low altitude, the narrow water level fluctuation, the narrowed watershed area, and the more circular shape. In terms of the purposes of reservoir operation, the reservoirs for agricultural irrigation were more eutrophic than the reservoirs for flood control. The results of the variable selection and path analysis showed that COD determined by Chl a and TP was directly affected by water level fluctuation and the shoreline development of the reservoirs. TP was directly affected by the urbanized area of the watershed which was related to the elevation of the reservoir. TP was also influenced by the water level fluctuation and the shoreline development. In conclusion, the eutrophication of the reservoirs in Korea would be influenced by the land use of the watershed, hydrological and geographical characteristics of the reservoir, water level fluctuation by the anthropogenic management according to the reservoir operation purpose, and the location of the reservoirs.