• Journal of the Korean Institute of Landscape Architecture
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• v.13 no.1
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• pp.43-66
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• 1985

Korea needs proper and rational public policies on conservation and use of forest land and other natural resources because of the accelerating expansion of national land developments in recent years. Unfortunately, there is no systematic planning system to support the needs. Generally, forest land use planning needs suitability analysis based on efficient land classification system. The goal of this study was to classify a forest land using multivariate satistical methods. A case study was carried out in winter of 1983 on a mountainous area higher than 100m above sea level located at Mt. Kwanak in Anyang -city, Kyung-gi-do (province). The study area was 19.80 km$^2$wide and was divided into 1, 383 Operational Taxonomic Units (OTU's) by a 120m$\times$120m grid. Fourteen descriptors were identified and quantified for each OTU from existing national land data : elevation, slope, aspect, terrain form, geologic material, surface soil permeability, topsoil type, depth of the solum, soil acidity, forest cover type, stand size class, stand age class, stand density class, and simple forest soil capability class. For this study, a FORTRAN IV program was written for input and output map data, and the computer statistics packages, SPSS and BMD, were used to perform the multivariate statistical analysis. Fourteen variables were analyzed to investigate the characteristics of their fire quench distribution and to estimate the correlation coefficients among them. Principal component analysis was executed to find the dimensions of forest land characteristics, and factor scores were used for proper samples of OTU throughout the study area. In order to develop the classes of forest land classification based on 102 surrogates, cluster and discriminant analyses of principal descriptor variable matrix were undertaken. Results obtained through a series of multivariate statistical analyses were as follows ; 1) Principal component analysis was proved to be a useful tool for data selection and identification of principal descriptor variables which represented the characteristics of forest land and facilitated the selection of samples.

• Journal of Korean Society of Forest Science
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• v.88 no.3
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• pp.352-363
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• 1999

It has been rare to obtain reliable information related to the size of forest land in North Korea. Several sources of forest statistics, ranging from the first map of forest distribution in Korean Peninsula produced in 1910 to official data reported by the North Korea Government in 1997, were gathered and analyzed to define the characteristics of forest cover changes over years. In addition, Landsat satellite data obtained from 1973 to 1993 were processed for the two study areas of the provinces of Pyungyang and Heasan, where the topography and land use pattern are significantly different each other. Using three sets of multitemporal Landsat imagery, land cover ma-ps were produced by computer classification. Although forest statistics reported before 1990 are somewhat inconsistent, they mere gradually decreasing over years. The estimates of 1991 satellite data and the recent statistics reported in 1998 shows very steep decline in forest lands as compared to the ones before 1990. The abrupt decrease of forest lands after 1990 was also found on the detailed analysis of Landsat data for the two study areas of Pyungyang and Heasan. The rapid decline of forest lands may have something to do with the poor economic situation of the country and the continuing natural disasters of severe flooding and drought. Unstocked forest, which was not classified into forest land, was a very distinct and pervasive land cover type that can be easily observed on satellite imagery. Since unstocked forest land in North Korea may be a critical factor for degrading environmental quality as well as for the continuing natural disasters, further analysis is necessary to define the exact extent and the physical characteristics of the cover type.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.19-26
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• 2006

Andong and Imha reservoir adjoins each other, but turbid water shows too much different when it rains. The characteristics of geological rock in basin and agricultural area around river boundary are pointed out as the major reason of turbid water of Imha reservoir. This study analyzed rock type of topsoil layer using soil map by National Institute of Agricultural Science and Technology (NIAST). Among rock types, sedimentary rock affects on the occurrence of turbid water. In the analysis of sedimentary rock type, the distribution of sedimentary rock of Imha basin shows 1.87 times higher than that of Andong basin. Also, the distribution of sedimentary rock of Imha basin shows higher than that of Andong basin within 1,600m from river channel in according to the buffer zone of river boundary. And Agricultural area of Imha basin shows higher than that of Andong basin in analysis of land cover within 1,600 m from river channel. As this agricultural characteristics of Imha basin, cover management factor of Imha basin represents more higher that that of Andong basin.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.116-119
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• 2005

As to the synthetical estimation of land covering parameters or the compounded land covering classification for multi-resolution satellite data, former researches mainly adopted linear or nonlinear regression models to describe the regression relationship of land covering parameters caused by the degradation of spatial resolution, in order to improve the retrieval accuracy of global land covering parameters based on 1;he lower resolution satellite data. However, these methods can't authentically represent the complementary characteristics of spatial resolutions among different satellite data at arithmetic level. To resolve the problem above, a new compounded land covering classification method at arithmetic level for multi-resolution satellite data is proposed in this .paper. Firstly, on the basis of unsupervised clustering analysis of the higher resolution satellite data, the likelihood distribution scatterplot of each cover type is obtained according to multiple-to-single spatial correspondence between the higher and lower resolution satellite data in some local test regions, then Parzen window approach is adopted to derive the real likelihood functions from the scatterplots, and finally the likelihood functions are extended from the local test regions to the full covering area of the lower resolution satellite data and the global covering area of the lower resolution satellite is classified under the maximum likelihood rule. Some experimental results indicate that this proposed compounded method can improve the classification accuracy of large-scale lower resolution satellite data with the support of some local-area higher resolution satellite data.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.75-85
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• 2020

This study examines machine learning cross-validation to utilized create ROI for classification of land cover. The study area located in Sejong and one KOMPSAT-3A image was used in this analysis: procedure on October 28, 2019. We used four bands(Red, Green, Blue, Near infra-red) for learning cross validation process. In this study, we used K-fold method in cross validation and used SVM kernel type with cross validation result. In addition, we used 4 kernels of SVM(Linear, Polynomial, RBF, Sigmoid) for supervised classification land cover map using extracted ROI. During the cross validation process, 1,813 data extracted from 3,500 data, and the most of the building, road and grass class data were removed about 60% during cross validation process. Based on this, the supervised SVM linear technique showed the highest classification accuracy of 91.77% compared to other kernel methods. The grass' producer accuracy showed 79.43% and identified a large mis-classification in forests. Depending on the results of the study, extraction ROI using cross validation may be effective in forest, water and agriculture areas, but it is deemed necessary to improve the distinction of built-up, grass and bare-soil area.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.65-77
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• 2012

This study examined changes in land cover for the past 25 years in Busan and subsequently evaluated heat island potential by using land surface temperature and observation temperature data. The results were as below. The urban area of Busan increased by more than 2.5 times for the past 25 years from 1975 to 2000. It was believed that an increase in the pavement area of city within such a short period of time was an unprecedented phenomenon unique to our country. It could be assumed that urban heat island would be worsened through this process. After analyzing the land temperature according to the land cover, it was shown that there were noticeable changes in the temperature of urban & built-up and mountain & forest areas. In particular, the temperature rose to $36{\sim}39^{\circ}C$ in industrial areas during the summer, whereas it went down to $22{\sim}24^{\circ}C$ in the urban areas at whose center there were mountains. It was found that heat island potential according to the level of land cover had various values depending on the conditions of land cover. Among the areas of urbanization, the industrial area's heat island potential is 6 to $8^{\circ}C$, and the residential and commercial area's is $0{\sim}5^{\circ}C$, so it has been found that there is high possibility to induce urban heat islands. Meanwhile, in the forest or agricultural area or the waterside, the heat island potential is $-6{\sim}-3^{\circ}C$. With this study result, it is possible to evaluate the effects of temperature increase according to the urban land use, and it can be used as foundational data to improve urban thermal environment and plan eco-friendly urban development.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.3
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• pp.77-85
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• 2007

Assessment of soil erosion is a cost and time-consuming task. There are many models developed to predict soil erosion from an area, but Universal Soil Loss Equation (USLE) is most widely used empirical equation for estimating annual soil erosion. Soil erosion depends upon-rainfall intensity, type of soil, land cover and land use, slope degree, slope length and soil conservation practice. All these parameters are have spatial distribution and hence satellite remote sensing and Geographic Information System (GIS) are applicable in the assessment of the influence on soil erosion. GIS has been integrated with the USLE (Universal Soil Loss Equation) model in identification of rainfall-based erosion to the Bocheong River which is the representative basin of IHP due to Typhoon Rusa. Similar studies are available in literature, ranging from those that use a simple model such as USLE to others of a more sophisticated nature.

• Economic and Environmental Geology
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• v.38 no.1
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• pp.33-43
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• 2005

The purpose of this study is to make and validate landslide susceptibility map using artificial neural network and GIS in Kangneung area. For this, topography, soil, forest, geology and land cover data sets were constructed as a spatial database in GIS. From the database, slope, aspect, curvature, water system, topographic type, soil texture, soil material, soil drainage, soil effective thickness, wood type, wood age, wood diameter, forest density, lithology, land cover, and lineament were used as the landslide occurrence factors. The weight of the each factor was calculated, and applied to make landslide susceptibility maps using artificial neural network. Then the maps were validated using rate curve method which can predict qualitatively the landslide occurrence. The landslide susceptibility map can be used to reduce associated hazards, and to plan land use and construction as basic data.

• Journal of Korea Planning Association
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• v.53 no.7
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• pp.109-126
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• 2018

The purpose of this study is to identify the spatial types for thermal environment improvement considering heat flux and its spatial context through empirical orthodox formulas. First, k-means clustering was used to classify values of three kinds of heat flux - latent, sensible and storage heat. Next, from the k-means clustering, we defined a type of thermal environment (type LHL) where improvement is needed for more comfortable and pleasant thermal environment in the city, among the eight types. Lastly, we compared and analyzed the characteristics of each classified thermal environmental types based on land cover types. From the study, we found that the ratio of impervious surfaces, roads, and buildings of the type LHL is higher than those of the type HLH (relatively thermal comfort environment). In order to improve the thermal environment, the following contents are proposed to urban planners and designers depending on the results of the study. a) Increase the green zone rate by 10% to reduce sensible heat; b) Reduce the percentage of impermeable surfaces and roads by 10% ; c) Latent heat increases when water and green spaces are expanded. This study will help to establish a minimum criterion for a land cover rate for the improvement of the urban thermal environment and a standard index for the thermal environmental improvement can be derived.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.232-232
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• 2015

Land use and climate changes are the important factors to determine the runoff and sediment loads from the watershed. The changes also affected to runoff volume/pattern to the dam operation and may cause flood and drought situations in the downstream area. Sirikit Dam is one of the biggest dams in Thailand which cover about 25 % of the runoff into the Central Plain where the Bangkok Capital is located. The study aims to determine the effect of land use change to the runoff/sediment volume pattern and the rainfall-runoff-sediment relationship in the different land use type. Field measurements of the actual rainfall, runoff and sediment in the selected four sub-basins with different type of land use in the Upper Nan Basin were conducted and the runoff ratio coefficients and sediment yield were estimated for each sub-basin. The effect of the land use change (deforestation) towards runoff/sediment will be investigated. The study of the climate change impact on the runoff in the future scenarios was conducted to project the change of runoff volume/pattern into the Sirikit Dam. The improvement of the Sirikit Dam operation rule was conducted to reduce the weakness of the existing operation rules after Floods 2011. The newly proposed dam operation rule improvement will then be evaluated from the water shortage situations in the downstream of Sirikit Dam under various conditions of changes of both land use and climate when compared with the situations based on the existing reservoir operation rules.