• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.2
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• pp.23-33
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• 2009

Satellite image is very usefully practiced to predict and analyze physical expansion and change of city. Physical expansion and change of city is closely related to the use of land, and continuous growth management focused on the use of land is essential for sustainable city growth. In this research, the change of land cover and land-use were analyzed with basic input data from 1985 to 2000 according to artificial satellite. Moreover, the land-use turnover rate was understood and expansion trend of urban sprawl in Busan metropolitan city and land-use characteristics of the expansion area. The results are, first, the area for urban region was expanded continuously but areas for agriculture area, forest area, and water area had different changes due to administrative district reform of Busan by each year. Second, the urbanization area in Busan was increased by 3.8% from $92.5km^2$ in 1985 to $167.5km^2$ in 2000. Third, the result of analysis on land-use turnover rate showed that agriculture area was turned into urbanized area the most, and forest area was followed by. Fourth, the result of analysis on database and overlay of buildings in Busan established in 2001 showed that agriculture area are had type 1 and 2 neighborhood living facilities (45.63%), apartment house in forest area (18.49%), and factory in water area (31.84%) with high ratio.

• Journal of Korean Society of Forest Science
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• v.98 no.4
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• pp.409-416
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• 2009

Forest biomass estimation is essential for greenhouse gas inventories and terrestrial carbon accounting. Remote sensing allows for estimating forest biomass over a large area. This study was conducted to estimate forest biomass and to produce a forest biomass map for Muju county using forest biomass conversion table developed by field plot data from the 5th National Forest Inventory and Landsat TM-5. Correlation analysis was carried out to select suitable independent variables for developing regression models. It was resulted that the height class, crown closure density, and age class were highly correlated with forest biomass. Six regression models were used with the combination of these three stand variables and verified by validation statistics such as root mean square error (RMSE) and mean bias. It was found that a regression model with crown closure density and height class (Model V) was better than others for estimating forest biomass. A biomass conversion table by model V was produced and then used for estimating forest biomass in the study site. The total forest biomass of the Muju county was estimated about 8.8 million ton, or 128.3 ton/ha by the conversion table.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.787-799
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• 2018

Accurate and effective mapping is critical step to monitor the spatial distribution and change of flood inundated area in large scale flood event. In this study, we try to suggest methods to use low spatial resolution satellite optical imagery for flood mapping, which has high temporal resolution to cover wide geographical area several times per a day. We selected the Sebou watershed flood in Morocco that was occurred in early 2010, in which several hundred $km^2$ area of the Gharb lowland plain was inundated. MODIS daily surface reflectance product was used to detect the flooded area. The study area showed several distinct spectral patterns within the flooded area, which included pure turbid water and turbid water with vegetation. The flooded area was extracted by thresholding on selected band reflectance and water-related spectral indices. Accuracy of these flooding detection methods were assessed by the reference map obtained from Landsat-5 TM image and qualitative interpretation of the flood map derived. Over 90% of accuracies were obtained for three methods except for the NDWI threshold. Two spectral bands of SWIR and red were essential to detect the flooded area and the simple thresholding on these bands was effective to detect the flooded area. NIR band did not play important role to detect the flooded area while it was useful to separate the water-vegetation mixed flooded classes from the purely water surface.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.215-219
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• 2001

Land surface parameterization schemes for atmospheric models as well as decision support tools for ecosystem management require a frequent updating of land cover classification data for regional to global scales. Rice paddies have not been treated independently from other agricultural land classes in many classification systems, despite their atmospheric and ecological significance. A simple but improved method over conventional land cover classification schemes for rice paddy is suggested. Normalized difference vegetation index (NDVI) was calculated for the land area of South Korea at a 1km by 1 km resolution from the visible and the near-infrared channel reflectances of NOAA-AVHRR (Advanced Very High Resolution Radiometer). Monthly composite images of daily maximum NDVI were prepared for May and August, and used to classify 4 major land cover classes : urban, farmland, forests and water body. Among the pixels classified as "forests" in August, those classified as "water body" in May were assigned a "rice paddy" class. The distribution pattern of "rice paddy" pixels was very similar to the reported rice acreage of 1,455 Myons, which is the smallest administrative land unit in Korea. The correlation coefficient between the estimated and the reported acreage of Myons was 0.7, while 0.5 was calculated from the USGS classification.calculated from the USGS classification.

• Journal of the Korean Geographical Society
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• v.40 no.2 s.107
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• pp.221-241
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• 2005

Land Use and Land Cover Changes (LUCC) occur over a wide range of space and time scales, and involve complex natural, socio-economic, and institutional processes. Therefore, modelling and predicting LUCC demands an understanding of how various measured properties behave when considered at different scales. Understanding spatial and temporal variability of driving forces and constraints on LUCC is central to understanding the scaling issues. This paper aims to 1) assess the heterogeneity of land cover change processes over the landscape in northern Ghana, where intensification of agricultural activities has been the dominant land cover change process during the past 15 years, 2) characterise dominant land cover change mechanisms for various spatial scales, and 3) identify the optimal spatial scale for LUCC modelling in a savanna landscape. A multivariate statistical method was first applied to identify land cover change intensity (LCCI), using four time-sequenced NDVI images derived from LANDSAT scenes. Three proxy land use change predictors: distance from roads, distance from surface water bodies, and a terrain characterisation index, were regressed against the LCCI using a multi-scale hierarchical adaptive model to identify scale dependency and spatial heterogeneity of LUCC processes. High spatial associations between the LCCI and land use change predictors were mostly limited to moving windows smaller than 10$\times$10km. With increasing window size, LUCC processes within the window tend to be too diverse to establish clear trends, because changes in one part of the window are compensated elsewhere. This results in a reduced correlation between LCCI and land use change predictors at a coarser spatial extent. The spatial coverage of 5-l0km is incidentally equivalent to a village or community area in the study region. In order to reduce spatial variability of land use change processes for regional or national level LUCC modelling, we suggest that the village level is the optimal spatial investigation unit in this savanna landscape.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.3
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• pp.46-53
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• 2009

Urbanization brings several changes to the natural environment. Its consequences can have a direct effect on climatic features, as in the Urban Heat Island Effect. One factor that directly affects the urban climate is the green area. In urban areas, vegetation is suppressed in order to accommodate manmade buildings and streets. In this paper we analyze the effect of green areas on the urban temperature in Seoul. The period selected for analysis was July 30th, 2007. The ground temperature was measured using Landsat TM satellite imagery. Land cover was calculated in terms of city area, water, bare soil, wet lands, grass lands, forest, and farmland. We extracted the surface temperature using the Linear Regression Model. Then, we did a regression analysis between air temperature at the Automatic Weather Station and surface temperature. Finally, we calculated the temperature decrease area and the population benefits from the green areas. Consequently, we determined that a green area with a radius of 500m will have a temperature reduction area of $67.33km^2$, in terms of urban area. This is 11.12% of Seoul's metropolitan area and 18.09% of the Seoul urban area. We can assume that about 1,892,000 people would be affected by this green area's temperature reduction. Also, we randomly chose 50 places to analysis a cross section of temperature reduction area. Temperature differences between the boundaries of green and urban areas are an average of $0.78^{\circ}C$. The highest temperature difference is $1.7^{\circ}C$, and the lowest temperature difference is $0.3^{\circ}C$. This study has demonstrated that we can understand how green areas truly affect air temperature.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.203-217
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• 2024

The Land Use, Land-Use Change and Forestry (LULUCF) sector of the National Greenhouse Gas Inventory is crucial for obtaining data on carbon sinks, necessitating accurate estimations. This study analyzes cases of countries applying the LULUCF sector at the Tier 3 level to propose enhanced methodologies for carbon sink estimation. In nations like Japan and Western Europe, satellite spatial information such as SPOT, Landsat, and Light Detection and Ranging (LiDAR)is used alongside national statistical data to estimate LULUCF. However, in Korea, the lack of land use change data and the absence of integrated management by category, measurement is predominantly conducted at the Tier 1 level, except for certain forest areas. In this study, Space-borne LiDAR Global Ecosystem Dynamics Investigation (GEDI) was used to calculate forest canopy heights based on Relative Height 100 (RH100) in the cities of Icheon, Gwangju, and Yeoju in Gyeonggi Province, Korea. These canopy heights were compared with the 1:5,000 scale forest maps used for the National Inventory Report in Korea. The GEDI data showed a maximum canopy height of 29.44 meters (m) in Gwangju, contrasting with the forest type maps that reported heights up to 34 m in Gwangju and parts of Icheon, and a minimum of 2 m in Icheon. Additionally, this study utilized Ordinary Least Squares(OLS)regression analysis to compare GEDI RH100 data with forest stand heights at the eup-myeon-dong level using ArcGIS, revealing Standard Deviations (SDs)ranging from -1.4 to 2.5, indicating significant regional variability. Areas where forest stand heights were higher than GEDI measurements showed greater variability, whereas locations with lower tree heights from forest type maps demonstrated lower SDs. The discrepancies between GEDI and actual measurements suggest the potential for improving height estimations through the application of high-resolution remote sensing techniques. To enhance future assessments of forest biomass and carbon storage at the Tier 3 level, high-resolution, reliable data are essential. These findings underscore the urgent need for integrating high-resolution, spatially explicit LiDAR data to enhance the accuracy of carbon sink calculations in Korea.

• Korean Journal of Environment and Ecology
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• v.19 no.4
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• pp.375-384
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• 2005

This study was conducted selecting 44 places with a block unit subject to urban area in Gangnam-gu, to analyze a temperature change according to land use and green structure. In this study, it was used the broad-wide urban temperature, supported by Landset TM and ETM+ satellite image 6scene(1999${\~}$2002). The result of the research, the land use pattern has slightly influence on a temperature change of urban area. The result from correlation analysis between temperature and the factors affected by land cover type, such as building-to-land ratio(A correlation coefficient is 0.368${\~}$0.709) have positive correlation and green area ratio(a correlation coefficient is -0.551${\~}$-0.860) have negative correlation. The result from correlation analysis between temperature and green capacity of the land, crown projection area ratio, each factor have negative correlation with temperature, as showing that a correlation coefficient of green capacity of the land is -0.577(June 2006)${\~}$-0.882(June 1999) and crown projection area ratio's is -0.549(June 2001)${\~}$-0.817(June 1999). The result of the regression analysis for establishing urban area temperature change prediction model showed that green capacity of the land of the explanation variable was accepted.

• Journal of the Korean Geographical Society
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• v.35 no.1
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• pp.3-15
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• 2000

산업화와 더불어 심각해지고 있는 수질오염 문제를 해결하기 위해서는 여러 가지 수질관리 방안이 요구된다. 수질오염이 과거에는 국지적이었으나 점차 광범한 지역으로 확장됨에 다라 지속적인 수질 모니터링에 어려움이 따른다. 본 연구에서는 위성영상을 사용한 원격탐사 기법으로 수역의 수질환경 인자를 추출하고자 한다. 사용된 영상은 Landasat TM이며, 연구지역은 한강하류 지역이다. 수질분석 인자는 클로로필-a, 부유물질, 투명도 등을 선정하였으며, 수면분광반사율의 특징 및 수질인자별 처리기법을 개발하는데 목적을 두었다. 분광특성 분석결과를 요약하면, 첫 번째 스펙트럼 반사율 분석결과 클로로필-a의 농도는 0.4~0.5$\mu\textrm{m}$ 파장대역에서 낮은 반사치 경향을 보이며, 녹색파장대인 0.57$\mu\textrm{m}$ 부근에서 반사율이 높아진다. 두 번째 부유물질의 반사도는 농도가 증가할수록 0.8$\mu\textrm{m}$ 부근에서 상대적으로 낮은 반사율이 나타난다. 마지막으로 투명도가 낮은 수면은 0.55$\mu\textrm{m}$에서 높은 반사율 경향을 보인다. Landsat TM영상을 이용하여 주성분분석 및 비연산처리를 실시하여 수질분석을 시도한 결과를 보면 클로로필-a와 투명도는 제1주성분 영상 및 제2주성분 영상에서 현장 실측자료와 유사한 결과를 얻을 수 있었으며, 부유물질은 밴드 2와 밴드 4의 비연산처리를 통하여 분포도를 작성할 수 있었다. 이상의 결과들은 계절적 및 시간적 변화에 따라 파장대역이 달라질 수 있다. 그러므로 위성자료를 이용하여 보다 정확한 수질환경 인자를 추출하기 위해서는 현장실측 및 수역의 분광반사 특성을 지속적으로 조사하여야 한다.때문으로 경주 산사태와 포함-구릉포간 국도면의 산사태가 이 종류의 산사태에 속한다.열 인식의 신뢰도를 향상시킬수 있는 방법을 제안하였다.작성하여 최신 의료영상 처리 기법을 쉽게 임상에 적용하고 실험할 수 있는 장점이 있다. 지대에서 가능하였고, 파종기는 중생종보다 이르게 나타났다. 등숙만한출수기 기준의 안전작기는 조생종과 중생종은 태백고냉지대와 태백준고냉지대, 소백산간지대 일부지역을 제외한 다른 지역에서 설정되었고, 중만생종은 태백고냉지대, 태백준고냉지대, 동해안북부지대, 소백산간지대, 노령소백산간지대의 일부 지역은 벼 담수직파가 불가능하게 판단되었다. information on the regular basis of time and provide it when the users query over the Web-database gateway. The other approach is a shopping agent mechanism, which stores information on "how to shop" and the shopping agent collects the information of product items just after users query about the product and provide the information in real time or notify them by alerting service. Thirty nine shopping information services are compared and classified in this paper and they are extracted from "Naver" and "Yahoo! Korea". The final result shows that most services are just a

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.133-145
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• 2010

This study analyzed the characteristics of sediment produce by landslide triggered by rainfall. One-dimensional unsaturated groundwater model and infinite slope stability analysis were used to estimate the behavior of soil moisture and slope stability according to rainfall, respectively. Slope stability analysis was performed considering on soil depth and characteristics of trees. As the results considering on recovery of the failed slopes, much amount of sediment was produced in 1963, 1970, and 2002. As the results of verification of simulation results using Landsat 5 TM images, we can find differences of landslide location between the results from model and satellite images. These differences can be caused by uncertainties of the rough parameters in the model. However, in the case that Obong-dam basin was divided into two subbasin, Wangsan-chun and Doma-chun basin, the results of each subbasin show errors around 20%. And only 4% of error occurred in the case of comparing landslide area on the entire Obong-dam basin. These errors seem insignificant considering on the errors which can be caused from the analyses in this study such as estimation of sediment produce, soil cover classification, and estimation of landslide area.