• Title/Summary/Keyword: 시가화지역

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Effect on the Temperature in Forest Dominant Vegetation Change (산림 우점식생 변화가 온도에 미치는 영향)

  • An, Mi-Yeon;Hong, Suk-Hwan
    • Korean Journal of Environment and Ecology
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    • v.32 no.1
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    • pp.97-104
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    • 2018
  • This study investigated the effect of forest type changes in Daegu, the hottest city in Korea, on the land surface temperature (LST). The LST change by forest type was analyzed by 2scene of Landsat TM image from 1990 to 2007. The land cover types were classified into 4 types; forest areas, urban areas, cultivated areas and other areas, and water areas. The forest areas were further classified into the coniferous tree areas and the broadleaf tree areas. The result of the statistical analysis of the LST change according to the forest type showed that the LST increased when the forest was changed to the urban area. The LST increased by about $0.6^{\circ}C$ when a broadleaf tree area was changed to an urban area and about $0.2^{\circ}C$ when a coniferous tree area was changed to an urban area. This was the temperature change as the result of the simple type change for 17 years. The temperature change was larger when considering both cases of the forest type being retained and changed. The LST increased by $2.3^{\circ}C$ more when the broadleaf tree areas were changed to the urban areas than when broadleaf trees were maintained. The LST increased by $1.9^{\circ}C$ more when the coniferous tree areas were changed to the urban areas than when the coniferous tree areas were maintained. The LST increased by $0.4^{\circ}C$ more when the broadleaf tree areas were destroyed than when the coniferous tree areas were destroyed. The results confirmed that the protection of broadleaf trees in urban forests was more effective for mitigating climate change.

A Study on the Change of Built-up Areas using Remote Sensing Data (원격탐사 자료를 활용한 시가화지역의 변화에 관한 연구)

  • Kim, Yoon-Soo;Jung, Eung-Ho;Ryu, Ji-Won;Kim, Dae-Wuk
    • Journal of the Korean Association of Geographic Information Studies
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    • v.8 no.2
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    • pp.1-9
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    • 2005
  • This study was performed to analyze time series landuse pattern of urban areas and the change of the areas by using remotely sensed multiple sensors. The results were as follows. First, according to the result of time series analysis, most agricultural land has been changed into built-up areas by development work such as the land development or land readjustment project, arrangement of science parks or military facilities, and location of public establishment like government buildings. Second, if the expansion of built-up areas maintains the present scale and speed, it seems that a lot of parts of land would be changed into built-up areas, especially centering around agricultural land, so it is necessary to establish the plan for urban space. Third, I have synthetically collected the data of the project of urban development and systematically monitored the process of in expansion the built-up areas up to now (from the past). I hereby could lay the foundation that makes us scientifically forecast the direction of expansion in the built-up areas by the urban development in the future.

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Estimating Land Assets in North Korea: Framework Development & Exploratory Application (북한지역 토지자산 추정에 관한 연구: 프레임워크 개발 및 탐색적 적용)

  • Lim, Song
    • 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.

Groundwater Recharge According to Land Cover Change in Urban Area (도시지역의 토지피복 변화에 따른 지하수 함양량)

  • Lee, Seung-Hyun;Bae, Sang-Keun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.1913-1917
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    • 2009
  • 국제사회의 분위기와 더불어 국내에서도 에너지 자원의 지속적인 개발과 이용에 대한 관심이 높아지고 있다. 그 중 수자원의 지속적인 확보와 개발은 가장 현실적이고 우선적인 문제로 인식되고 있으며 수자원확보/환경/개발 및 이용 등의 여러 분야에서 그간의 정량적 성과가 하나 둘씩 도출되어 적용 단계에 이르기도 하였다. 하지만 지하수의 경우 기초자료의 미흡과 불확실성, 함양량 및 개발가능량에 대한 산정기법의 적용성 문제, 체계화된 개발 및 이용에 대한 인식이 부족한 실정이다. 특히, 도시지역의 경우는 인구의 증가로 인하여 지하수이용량이 급격하게 증가하고 잠재적 지하수오염 가능성이 높아져 지하수환경의 악화를 초래하고 이로 인하여 하천 환경에도 영향을 미칠 수 있기 때문에 지하수개발가능량의 평가 및 체계적인 이용과 관리가 반드시 필요하나 지하수함양에 결정적인 영향을 미치는 토지피복상태가 지속적으로 변화하여 지하수함양량에도 매년 변화가 있으며 이에 따라 개발가능량도 변하고 있어 지하수 개발과 관리 및 이용에 많은 어려움을 겪고 있는 실정이다. 본 논문에서는 부산광역시 수영구 일대를 대상으로 도시화 현상으로 변화하는 토지피복상태를 분석하고 그 결과를 반영하여 1961년부터 2007년까지의 지하수함양량 및 함양률을 산정하였다. 연구대상지역의 토지피복상태는 1975년 이전까지는 시가화지역이 18.6%, 농업지역이 30.0%, 산림이 48.8%, 초지가 0.1%, 나지가 2.0%, 수역이 0.5%를 차지하고 있었으나 1980년${\sim}$1985년에 농업지역이 18.3% 감소하고 시가화지역이 15.0% 증가하는 큰 변화가 나타났으며 1995년${\sim}$2000년에도 농업지역이 5.5% 감소하고 시가화지역이 5.4% 증가하는 변화를 나타냈다. 전 연도에 걸쳐 산림지역과 초지, 나지, 수역에서의 변화는 크지 않았다. 연구대상지역의 평균 강우량은 1509.3mm이고 지하수평균함양량은 216.0mm이며 지하수평균함양률은 14.3%로 나타났다. 연최대함양량은 강우량이 2138.1mm인 1970년에 408.9mm이며 연최대함양률은 강우량이 1492.6mm인 1984년에 19.8%이다. 연최소함양량은 강우량이 901.5mm인 1988년에 71.9mm이며 연최소함양률은 같은해에 8.0%로 나타났다. 또한 연도의 증가에 따라 강우량은 증가하였으나 지하수함양량은 감소하는 경향을 나타내었다.

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A Study on the Relationship between Land Cover Type and Urban Temperature - focused on Gimhae city - (토지피복유형 특성과 도시 온도의 관계 분석 - 김해시를 대상으로 -)

  • SONG, Bong-Geun;PARK, Kyung-Hun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.2
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    • pp.65-81
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    • 2019
  • This study analyzed the relationship of land cover type, urban temperature in Gimhae city, Gyeongsangnam-do, South Korea. Date were used for land cover map, MODIS LST, and detailed temperature data on the Korean Peninsula based on RCP between 2000 and 2010. The correlation between urban area and surface temperature was 0.417, 0.512 for agricultural area and -0.607 for forest area. The correlation between surface temperature and air temperature was 0.301. The relationship with air temperature was analyzed as 0.275 for urban area, agriculture area 0.226, forest area 0.350. Urban and agricultural areas showed increased surface and air temperature as the area increased, while forest areas showed opposite improvements. In structural equation models, urban and agricultural areas had direct effects on the rise of surface temperature, whle forest areas had direct effects on the reduction of air temperature. In the future, it is necessary to use measured temperature data near the surface to understand the relationship between surface temperature and temperature according to the changes in spatial characteristics, which will prepare measures for urban heat island mitigation at the level of urban and environmental planning.

A Study on the Criteria for Demarcating Ecological Types of Urban Areas by the Affection of Ecosystems - Case Study in Gangdong-Gu, Seoul - (시가화지역 생태적 유형구분을 위한 관련지표 특성 연구 - 서울시 강동구를 사례로 -)

  • Hong, Suk-Hwan;Lee, Kyong-Jae
    • Journal of the Korean Institute of Landscape Architecture
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    • v.36 no.2
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    • pp.24-31
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    • 2008
  • Studies for demarcation of urban areas by ecological type have been developed, but the demarcation of urban areas by ecological perception is thus far dependent on artificial land use. Therefore, the purpose of this study is to find factors that account for the urban area ecosystems by surveying a variety of ecosystem factors. By land use type, the urban area of Gangdong District, Seoul was defined. Then ecological factors in each polygon were surveyed. Ecological factors are associated with energy use(building coverage ratio, floor area ratio and ground temperature), water circulation(biotope area factors and impermeable pave ratio) and biological diversity(bird appearance index and green area ratio). The correlation between each factor was analyzed. The results indicate that urban ground temperature is divided into three groups(high, middle and low) by the biotope area factor. The bird population is divided into two groups(abundant and scarce) by the green area ratio. Therefore, demarcating the urban areas by ecological type is applicable to the biotope area factor and green area ratio.

KOMPSAT-3A Urban Classification Using Machine Learning Algorithm - Focusing on Yang-jae in Seoul - (기계학습 기법에 따른 KOMPSAT-3A 시가화 영상 분류 - 서울시 양재 지역을 중심으로 -)

  • Youn, Hyoungjin;Jeong, Jongchul
    • Korean Journal of Remote Sensing
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    • v.36 no.6_2
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    • pp.1567-1577
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    • 2020
  • Urban land cover classification is role in urban planning and management. So, it's important to improve classification accuracy on urban location. In this paper, machine learning model, Support Vector Machine (SVM) and Artificial Neural Network (ANN) are proposed for urban land cover classification based on high resolution satellite imagery (KOMPSAT-3A). Satellite image was trained based on 25 m rectangle grid to create training data, and training models used for classifying test area. During the validation process, we presented confusion matrix for each result with 250 Ground Truth Points (GTP). Of the four SVM kernels and the two activation functions ANN, the SVM Polynomial kernel model had the highest accuracy of 86%. In the process of comparing the SVM and ANN using GTP, the SVM model was more effective than the ANN model for KOMPSAT-3A classification. Among the four classes (building, road, vegetation, and bare-soil), building class showed the lowest classification accuracy due to the shadow caused by the high rise building.

Analysis of the Seasonal Concentration Differences of Particulate Matter According to Land Cover of Seoul - Focusing on Forest and Urbanized Area - (서울시 토지피복에 따른 계절별 미세먼지 농도 차이 분석 - 산림과 시가화지역을 중심으로 -)

  • Choi, Tae-Young;Moon, Ho-Gyeong;Kang, Da-In;Cha, Jae-Gyu
    • 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.