• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.194-198
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• 2008

Significant soil erosion and water quality degradation issues are occurring at highland agricultural areas of Kangwon province because of agronomic and topographical specialities of the region. Thus spatial and temporal modeling techniques are often utilized to analyze soil erosion and sediment behaviors at watershed scale. The Soil and Water Assessment Tool (SWAT) model is one of the watershed scale models that have been widely used for these ends in Korea. In most cases, the SWAT users tend to use the readily available input dataset, such as the Ministry of Environment (MOE) land cover data ignoring temporal and spatial changes in land cover. Spatial and temporal resolutions of the MOE land cover data are not good enough to reflect field condition for accurate assesment of soil erosion and sediment behaviors. Especially accelerated soil erosion is occurring from agricultural fields, which is sometimes not possible to identify with low-resolution MOD land cover data. Thus new land cover data is prepared with cadastral map and high spatial resolution images of the Doam-dam watershed. The SWAT model was calibrated and validated with this land cover data. The EI values were 0.79 and 0.85 for streamflow calibration and validation, respectively. The EI were 0.79 and 0.86 for sediment calibration and validation, respectively. These EI values were greater than those with MOE land cover data. With newly prepared land cover dataset for the Doam-dam watershed, the SWAT model better predicts hydrologic and sediment behaviors. The number of HRUs with new land cover data increased by 70.2% compared with that with the MOE land cover, indicating better representation of small-sized agricultural field boundaries. The SWAT estimated annual average sediment yield with the MOE land cover data was 61.8 ton/ha/year for the Doam-dam watershed, while 36.2 ton/ha/year (70.7% difference) of annual sediment yield with new land cover data. Especially the most significant difference in estimated sediment yield was 548.0% for the subwatershed #2 (165.9 ton/ha/year with the MOE land cover data and 25.6 ton/ha/year with new land cover data developed in this study). The results obtained in this study implies that the use of MOE land cover data in SWAT sediment simulation for the Doam-dam watershed could results in 70.7% differences in overall sediment estimation and incorrect identification of sediment hot spot areas (such as subwatershed #2) for effective sediment management. Therefore it is recommended that one needs to carefully validate land cover for the study watershed for accurate hydrologic and sediment simulation with the SWAT model.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.197-205
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• 2004

Wetlands are lands with a mixture of water, herbaceous or woody vegetation and wet soil. And linear spectral mixture analysis (LSMA) is one of the most often used methods in handling the spectral mixture problem. This study aims to test LSMA is an enhanced routine for classification of wetland land-covers in Paldang reservoir and vicinity (paldang Reservoir) using Landsat TM and ETM+ imagery. In the LSMA process, reference endmembers were driven from scatter-plots of Landsat bands 3, 4 and 5, and a series of endmember models were developed based on green vegetation (GV), soil and water endmembers which are the main indicators of wetlands. To consider phenological characteristics of Paldang Reservoir, a soil endmember was subdivided into bright and dark soil endmembers in spring and a green vegetation (GV) endmember was subdivided into GV tree and GV herbaceous endmembers in fall. We found that LSMA fractions improved the classification accuracy of the wetland land-cover. Four endmember models provided better GV and soil discrimination and the root mean squared (RMS) errors were 0.011 and 0.0039, in spring and fall respectively. Phenologically, a fall image is more appropriate to classify wetland land-cover than spring's. The classification result using 4 endmember fractions of a fall image reached 85.2 and 74.2 percent of the producer's and user's accuracy respectively. This study shows that this routine will be an useful tool for identifying and monitoring the status of wetlands in Paldang Reservoir.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.249-260
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• 2017

UHI (Urban Heat Island) is an important environmental issue occurring in highly developed (or urbanized) area such as Seoul Metropolitan City of Korea due to modification of the land surface by man-made structures. With the advance of the remote sensing technique, land cover types and LST (Land Surface Temperature) influencing UHI were frequently investigated describing that they have a positive relationship. However, the concept of land cover considers material characteristics of the urban cover in a comprehensive way and does not provide information on how human activities influence on LST in detail. Instead, land use reflects ways of land use management and human life patterns and behaviors, and explains the relationship with human activities in more details. Using this concept, LST was segmented according to land use types from the Landsat imagery to identify the human-induced heat from the surface and interannual and seasonal variation of LST with GIS. The result showed that the LST intensity of Seoul was greatest in the industrial area and followed by the commercial and residential areas. In terms of size, the residential area could be defined as the major contributor among six urban land use types (i.e., residential, industrial, commercial, transportation, etc.) affecting UHI during daytime in Seoul. For temperature, the industrial area was highest and could be defined as a major contributor. It was found that land use type was more appropriate to understand the human-induced effect on LST rather than land cover. Also, there was no significant change in the interannual pattern of LST in Seoul but the seasonal difference provided a trigger that the human life pattern could be identified from the satellite-derived LST.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.984-987
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• 2003

In order to rapidly catch up urban region’s detailed land-use or land-cover information; this research used the post-classification algorithm (Spatial Reclassification Kernel: SPARK) to create a land-use map of Taichung City. We discussed the urban land-use classification model with the IKONOS images. The conclusions may be distinguished as follows:(a) Using the Maximum-Likelihood algorithm to classify seven broad land-cover categories. The overall accuracy in this stage achieves 92.72% and Kappa coefficient will be obtained 0.91; and (b) Using the SPARK method to classify images for detect the land-use, the overall accuracy achieves higher 89.64% and Kappa coefficient will be 0.86. To conclude, the research process in this study can fully and carefully describe local land-use pattern and assist the demand of land management and resources planning reference.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.313-316
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• 2003

Growing urban areas modify patterns of local land use and land cover. Land use changes associated with an urban area can be extensive. One way to understand and document land use change and urbanization is to establish benchmark maps compiled from satellite imagery The use of satellite imagery for monitoring urban growth has been widely demonstrated. Multi-temporal LANSAT TM image data has created the potential for monitoring urban change and land cover identification. In this study, for extracting urban boundary GLCM method and visual interpretation were used in CORONA imagery and SPOT imagery.

• 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 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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.4
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• pp.33-47
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• 2022

Wild boars(Sus scrofa) are expanding their range of behavior as their habitats change. Appearing in urban centers and private houses, it caused various social problems, including damage to crops. In order to prevent damage and effectively manage wild boars, there is a need for ecological research considering the characteristics and movement characteristics of wild boars. The purpose of this study is to analyze home range and identify land cover types in key areas through tracking wild boars, and to predict the movement connectivity of wild boars in consideration of previous studies and their preferred land use characteristics. In this study, from January to June 2021, four wild boars were captured and tracked in Jinju city, Gyeongsangnam-do, and the preferred land cover type of wild boars was identified based on the MCP 100%, KDE 95%, and KDE 50% results. As a result of the analysis of the home range for each individual, it was found that 100% of MCP was about 0.68km², 2.77km², 2.42km², and 0.16km², and the three individuals overlapped the home range, refraining from habitat movement and staying in the preferred area. The core areas were analyzed as about 0.55km², 2.05km², 0.82km², and 0.14km² with KDE 95%., and about 0.011km², 0.033km², 0.004km², and 0.003km² with KDE 50%. When the preferred land cover type of wild boar was confirmed based on the results of analysis of the total home range area and core area that combined all individuals, forests were 55.49% (MCP 100%), 54.00% (KDE 95%), 77.69% (KDE 50%), respectively, with the highest ratio, and the urbanization area, grassland, and agricultural area were relatively high. A connectivity scenario was constructed in which the ratio of the land cover type preferred by the analyzed wild boar was reflected as a weight for the resistance value of the connectivity analysis, and this was compared with the connectivity evaluation results analyzed based on previous studies and wild boar characteristics. When the current density values for the wild boar movement data were compared, the average value of the existing scenario was 2.76, the minimum 1.12, and the maximum 4.36, and the weighted scenario had an average value of 2.84, the minimum 0.96, and the maximum 4.65. It was confirmed that, on average, the probability of movement predictability was about 2.90% better even though the weighted scenario had movement restrictions due to large resistance values. It is expected that the identification of the movement route through the movement connectivity analysis of wild boars can be suggested as an alternative to prevent damage by predicting the point of appearance. In the future, when analyzing the connectivity of species including wild boar, it is judged that it will be effective to use movement data on actual species.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.1
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• pp.73-83
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• 2016

Forest degradation reduces ecosystem services provided by forest and could lead to change in composition of species. In North Korea, there has been significant forest degradation due to conversion of forest into terrace fields for food production and cut-down of forest for fuel woods. This study analyzed the phenological changes in North Korea, in terms of vegetation and moisture in soil and vegetation, from March to Octorber 2013, using MODIS (MODerate resolution Imaging Spectroradiometer) images and indexes including NDVI (Normalized Difference Vegetation Index), NDSI (Normalized Difference Soil Index), and NDWI (Normalized Difference Water Index). In addition, marginal farmland was derived using elevation data. Lastly, degraded terrace fields of 16 degree was analyzed using NDVI, NDSI, and NDWI indexes, and marginal farmland characteristics with slope variable. The accuracy value of land cover classification, which shows the difference between the observation and analyzed value, was 84.9% and Kappa value was 0.82. The highest accuracy value was from agricultural (paddy, field) and forest area. Terrace fields were easily identified using slope data form agricultural field. Use of NDVI, NDSI, and NDWI is more effective in distinguishing deforested terrace field from agricultural area. NDVI only shows vegetation difference whereas NDSI classifies soil moisture values and NDWI classifies abandoned agricultural fields based on moisture values. The method used in this study allowed more effective identification of deforested terrace fields, which visually illustrates forest degradation problem in North Korea.

• Journal of the Korean Professional Engineers Association
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• v.15 no.1
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• pp.46-50
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• 1982

Following rapid industrial development and urbanization in Korea, there is a need for the Government to implement effective control of pollution and to undertake specific schemes in areas where pollution of the environment is severe. In response to this need, Government of Korea prepare Han River Basin Environmental Master Plan Project for water, air, solid waste to cover environmental protection of the Han River Basin. The Project area is approximately 27,000 sq. Km extending over Seoul, Kyunggi, Kwangwon, Chungbuk Province. The total population of Master Plan Project area is approximately 11.6 million, or one-third of the total population of Korea. There are about 8,000 industries, including those located in 16 industrial complexes, in the project area. The scope of work and terms of reference are the following: (1) A Summary of existing land use and forecasts for changes in land use by the year 2,000. (2) Emission inventories for air, waste water, and solid wastes. (3) Forecasts of future population growth patterns and pollution loadings. (4) Identification of specific projects needs to reduce pollution levels and satisfy the environmental quality standards. (5) A Program of enforcement to include (i) self monitoring, and (ii) governmental inspections and surveillance. (6) A program for quality improvement and quality assurance of environmental measurements. (7) Reports summarizing all data collected analyzed during the study. (8) Conceptual design and feasibility studies, including cost estimates, for needed pollution control projects. (9) A financial plan for future detailed design and construction of public facilities, for financial incentives to industry, and for user charges for industrial use of public treatment of disposal works.