• Title/Summary/Keyword: 토지정보 모델

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Estimation of Watershed Parameters and Runoff Computation Using GIS (GIS를 이용한 유역매개변수의 추정 및 유출량 산정)

  • Lee, Im-Keun;Ahn, Kyung-Soo
    • Journal of Korea Water Resources Association
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    • v.40 no.1 s.174
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    • pp.11-24
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    • 2007
  • There exist various difficulties in runoff analysis due to many ungauged basins in Korea and the runoff phenomena is also more and more complicated by the change of geologic characteristics due to the urbanization. So, we use GIS technique which is widely used in hydrologic field and cell runoff concept for the fast and effective runoff simulation. This study uses the observations of 6 stage stations in Wi-Cheon watershed and simulates the watershed parameters by using WMS model. We construct DEM by the grids which are consisted based on the criteria of minimum area according to land use. The cell runoff is estimated by an average weighted method using mean annual streamflow and mean maximum daily streamflow obtained from six stage stations. The runoff ratio at arbitrary site is estimated by conducting the direction analysis of streamflow and by removing sinkhole. We compare the simulated and observed runoffs and know that the simulated runoff shows the valid results. So, we could use the geographical information and cell runoff concept for more fast and effective runoff simulation studies.

The Method for Colorizing SAR Images of Kompsat-5 Using Cycle GAN with Multi-scale Discriminators (다양한 크기의 식별자를 적용한 Cycle GAN을 이용한 다목적실용위성 5호 SAR 영상 색상 구현 방법)

  • Ku, Wonhoe;Chun, Daewon
    • Korean Journal of Remote Sensing
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    • v.34 no.6_3
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    • pp.1415-1425
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    • 2018
  • Kompsat-5 is the first Earth Observation Satellite which is equipped with an SAR in Korea. SAR images are generated by receiving signals reflected from an object by microwaves emitted from a SAR antenna. Because the wavelengths of microwaves are longer than the size of particles in the atmosphere, it can penetrate clouds and fog, and high-resolution images can be obtained without distinction between day and night. However, there is no color information in SAR images. To overcome these limitations of SAR images, colorization of SAR images using Cycle GAN, a deep learning model developed for domain translation, was conducted. Training of Cycle GAN is unstable due to the unsupervised learning based on unpaired dataset. Therefore, we proposed MS Cycle GAN applying multi-scale discriminator to solve the training instability of Cycle GAN and to improve the performance of colorization in this paper. To compare colorization performance of MS Cycle GAN and Cycle GAN, generated images by both models were compared qualitatively and quantitatively. Training Cycle GAN with multi-scale discriminator shows the losses of generators and discriminators are significantly reduced compared to the conventional Cycle GAN, and we identified that generated images by MS Cycle GAN are well-matched with the characteristics of regions such as leaves, rivers, and land.

Analysis and Management of Potential Development Area Using Factor of Change from Forest to Build-up (산림의 시가지 변화요인을 통한 잠재개발지 분석 및 관리방안)

  • LEE, Ji-Yeon;LIM, No-Ol;LEE, Sung-Joo;CHO, Hyo-Jin;SUNG, Hyun-Chan;JEON, Seong-Woo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.25 no.2
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    • pp.72-87
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    • 2022
  • For the sustainable development and conservation of the national land, planned development and efficient environmental conservation must be accompanied. To this end, it is possible to induce development and conservation to harmonize by deriving factors affecting development through analysis of previously developed areas and applying appropriate management measures to areas with high development pressure. In this study, the relationship between the area where the land cover changed from forest to urbanization and various social, geographical, and restrictive factors was implemented in a regression formula through logistic regression analysis, and potential development sites were analyzed for Yongin City. The factor that has the greatest impact on the analysis of potential development area is the restrict factors such as Green Belt and protected areas, and the factor with the least impact is the population density. About 148km2(52%) of Yongin-si's forests were analyzed as potential development area. Among the potential development sites, the area with excellent environmental value as a protected area and 1st grade on the Environment Conservation Value Assessment Map was derived as about 13km2. Protected areas with high development potential were riparian buffer zone and special measurement area, and areas with excellent natural scenery and river were preferred as development areas. Protected areas allow certain actions to protect individual property rights. However, there is no clear permit criteria, and the environmental impact of permits is not understood. This is identified as a factor that prevents protected areas from functioning properly. Therefore, it needs to be managed through clear exception permit criteria and environmental impact monitoring.

Nocturnal Surface Cooling and Cold Air Transport Analysis Based on High Density Observation - A Case Study of Eunpyeong New Town in Seoul (고밀도 관측자료를 이용한 야간 지면냉각과 찬공기 이동 분석 - 서울 은평구 뉴타운 사례)

  • Yi, Chae-Yeon;Kim, Kyu-Rang;Choi, Young-Jean;Won, Hye-Young;Scherer, Dieter
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.4
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    • pp.124-137
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    • 2012
  • Climate analysis is important in urban planning for human comfort. Synoptic weather conditions can only resolve the 30% of local variance of wind conditions whereas 70% of the variance arise from local terrain, buildings, and other small scale thermal conditions. Climate Analysis Seoul (CAS) was developed to resolve such micro-scale climate. The Local-scale air temperature Deviation (LD) analysis map from CAS showed the co-existence of built-up and suburban areas in the study region (CR, Cold-air analysis Region) despite its small extent. Temperature, humidity, wind speed, and wind direction were monitored in CR. Hourly observed cooling rate agreed well with LD. Cold air production, transportation, and stagnation was visualized by the observed Vertical Temperature Gradient (VTG) along the small stream in CR. VTG observed at the upper-most stream can be divided into two components: radiative cooling and cold air inflow from outside. Radiative cooling exists regardless of the wind speed whereas cold air inflow occurs only with calm wind. From the regression analyses based on the wind speed, the inflow portion was determined as 84% of radiative cooling. Climate analysis in the future will be able to characterize the changes in cold air by urban development plan to support the human comfort.

A Study on Institutional Improvement for effective Operation of Korea's Free Economic Zone (한국의 경제자유구역의 효율적 운영을 위한 개선과제에 관한 연구)

  • Hong, Song-Hon;Lee, Jae-Young
    • International Commerce and Information Review
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    • v.13 no.2
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    • pp.235-258
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    • 2011
  • Our country is operating designating the 6 free economic zones. Korea has designated fixed areas as economic special zones and made their management and living conditions equivalent to the level of advanced countries they are to support. One-Stop Service for the administrative demands that require the assistance at a national level in foreign investment, education, finance etc. However, these free economic zones are modified by regional development projects rather than inviting foreign capital. For the free economic zones to be operated effectively, the following methods should be followed: first, active management support activities should be constructed for the purpose of attracting foreign capital, second, a business model specifically designed to attract foreign capital should be implemented, third and finally, the independence and professionalism for the free economic zones should be strengthened.

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Soil Moisture Estimation Using KOMPSAT-3 and KOMPSAT-5 SAR Images and Its Validation: A Case Study of Western Area in Jeju Island (KOMPSAT-3와 KOMPSAT-5 SAR 영상을 이용한 토양수분 산정과 결과 검증: 제주 서부지역 사례 연구)

  • Jihyun Lee;Hayoung Lee;Kwangseob Kim;Kiwon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1185-1193
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    • 2023
  • The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

Predicting the Effects of Rooftop Greening and Evaluating CO2 Sequestration in Urban Heat Island Areas Using Satellite Imagery and Machine Learning (위성영상과 머신러닝 활용 도시열섬 지역 옥상녹화 효과 예측과 이산화탄소 흡수량 평가)

  • Minju Kim;Jeong U Park;Juhyeon Park;Jisoo Park;Chang-Uk Hyun
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.481-493
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    • 2023
  • In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

Change Prediction of Forestland Area in South Korea using Multinomial Logistic Regression Model (다항 로지스틱 회귀모형을 이용한 우리나라 산지면적 변화 추정에 관한 연구)

  • KWAK, Doo-Ahn
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.4
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    • pp.42-51
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    • 2020
  • This study was performed to support the 6th forest basic planning by Korea Forest Service as predicting the change of forestland area by the transition of land use type in the future over 35 years in South Korea. It is very important to analyze upcoming forestland area change for future forest planning because forestland plays a basic role to predict forest resources change for afforestation, production and management in the future. Therefore, the transitional interaction between land use types in future of South Korea was predicted in this study using econometrical models based on past trend data of land use type and related variables. The econometrical model based on maximum discounted profits theory for land use type determination was used to estimate total quantitative change by forestland, agricultural land and urban area at national scale using explanatory variables such as forestry value added, agricultural income and population during over 46 years. In result, it was analyzed that forestland area would decrease continuously at approximately 29,000 ha by 2027 while urban area increases in South Korea. However, it was predicted that the forestland area would be started to increase gradually at 170,000 ha by 2050 because urban area was reduced according to population decrement from 2032 in South Korea. We could find out that the increment of forestland would be attributed to social problems such as urban hollowing and localities extinction phenomenon by steep decrement of population from 2032. The decrement and increment of forestland by unbalanced population immigration to major cities and migration to localities might cause many social and economic problems against national sustainable development, so that future strategies and policies for forestland should be established considering such future change trends of land use type for balanced development and reasonable forestland use and conservation.

The Analysis of Reduction Efficiency of Soil Erosion and Sediment Yield by a Ginseng Area using GIS Tools

  • Lee, Geun-Sang;Jeon, Dae-Youn
    • Spatial Information Research
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    • v.17 no.4
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    • pp.431-443
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    • 2009
  • Recently, turbidity problem is one of the hot issues in dam and reservoir management works. Main reason to bring about high density turbid water is sediment yield by rainfall intensity energy. Because existing researches didn't consider diverse types of crops, it was difficult to calculate more accurate soil erosion and sediment yield. This study was evaluated the reduction efficiency of soil erosion and sediment yield using ginseng layer extracted from IKONOS satellite image, and the area and the ratio of ginseng area represented $0.290km^2$ and 0.94%. The reduction efficiency of soil erosion considering ginseng area represented low value in 0.9% using GIS-based RUSLE model, because the area of ginseng was small compared to areas of other agricultural lands. To reflect future land use change, this study was calculated the reduction efficiency of soil erosion and sediment yield by considering many scenarios as kinds of crops of paddy, dry field, orchard, and other agricultural areas convert to the ginseng district. As result of analysis of them according to scenarios, scenario (1) in which dry field was converted to ginseng area and scenario (2) in which fully agricultural lands were converted to ginseng area showed high reduction efficiency as 31.3% and 34.8% respectively, compared to existing research which didn't consider ginseng area. Methodology suggested in this study will be very efficient tools to help reservoir management related to high density turbid water.

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Status of Groundwater Potential Mapping Research Using GIS and Machine Learning (GIS와 기계학습을 이용한 지하수 가능성도 작성 연구 현황)

  • Lee, Saro;Fetemeh, Rezaie
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1277-1290
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    • 2020
  • Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.