• Journal of Wetlands Research
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• v.19 no.1
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• pp.144-154
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• 2017

The riparian vegetation is one of corridor type ecosystems, an ecotone and able to improve the ecological soundness by structural and functional link. And they act as habitats, sources and sinks of species, conduits, filters and barriers. This study was carried out to develop the vegetation model for the fluctuation areas of lake reservoirs consider of hydrologic and soil environments according to the vegetation structure of the reference ecosystem. To develop the case study, 2 sites within 10degree slope of the Daecheong Lake were selected. The riparian vegetation models were built by the results of GIS analysis, remote satellite analysis, field survey results, consider of water level, flooded frequency, soil and topographic index, land cover or land use etc. 1) study area varied from FWL to -5m of NFWL, 2) slope 10% below, 3) vegetations flooded below 100days yearly are Salix koreensis, Salix chaenomeloides, Salix gracilistyla, 4)land cover type classified wildlife grassland, abandoned paddy field, cropland according to landuse (or landcover), 5)finally model was constructed as ecological landscape forest. The model designs were suggested by 2 types in Daecheong lake reservoir. The model for the riparian vegetation corridors could be the basic and useful data to improve the ecological and landscape properties.

• Journal of Environmental Impact Assessment
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• v.14 no.5
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• pp.305-315
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• 2005

The scheme to classify pollution sources in Korean TMDL planning has been pointed out too much complex to implement practically because of requiring a wide range of items to be collected from a field. Within a deficient situation to collect field data, the mathematical scheme that focuses only on counting an uniform area ratio of the different land uses to estimate of pollutant loads from individual sub-catchments has been used without taking into account of the spatial characteristics of major land uses as well as the locations of pollution sources in each sub-catchment. It would cause to significant level of errors to estimate the pollution loads. Therefore, this study proposes a renovated scheme that can be adopted more easily to classify pollution sources in the watershed and reduce the estimation errors in the spatial distribution of pollution sources by introducing a spatial analysis based on digital land cover maps. In order to estimate a unit area to calculate the uniform pollution load, the pollution response unit area that is locating spatially at the same place and having same land use is identified through the application of GIS overlay technique. Unlikely existing conventional method to calculate the pollution load based on equal distribution of pollutants for each administrative boundary, it is assumed that the pollution load from household and livestock sources are generated and washed off from only residential areas. While, pollution from business population comes from commercial area and industrial load from wastewater discharge facilities are from industrial areas. From comparison of the calculated results from the existing the method and the proposed one, it is found that although the estimation of pollution load from sub-catchment in the case of the existing conventional method application results in negligible difference in total pollution amounts from the whole area of Wangsook watershed as a study area, significant difference of pollution load among sub-catchment in which pollution response unit areas are diverse, however, appears in the case of the application of the renovated scheme.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.13-22
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• 2009

Urban expansion has caused environmental problems, traffic jam and real estate. Trend analysis of Urban expansion is needed for analysis and prediction of the existing problem-solving, urban planning and land use. In this study, We constructed database based on MOE(Minister of environment)'s landcover(1980's, 2000's), 1: 25,000 digital topographical map using of DEM and data of the National Statistical Office for urban and build up expand analysis of South Korea. As a result, The rate of increase in population of Gyeonggi-do, Incheon and Ulsan are high but Jeollanam-do is low. Area of development zone was 2.15 fold increase in comparison with before it. Slope aspect is south or east and urban expansion was increase in district such as Chungcheongnam-do, Gyeonggi-do, Jeollanam-do. Existing road of accessibility was high than development zone. Metropolitan city developre it. In conclusion, we found that South Korea urban expansion was developed from metropolitan city. In natural topographical conditions, the development was progress advantageous zone to disadvantageous zone. Also, we found that population was rapidly increase with new development as the center zone in urban expansion zone.

• Korean Journal of Environment and Ecology
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• v.18 no.1
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• pp.53-60
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• 2004

This study was carried out to investigate the effect of green area in apartment complexes to variation of temperature. The inside temperature of each site was estimated by analyzing Landsat ETM＋ image data. The factors on variation of temperature were landcover type, building density, and Normalised Difference Vegetation Index(NDVI). The results of correlation between inside temperature of apartment complex and land cover type showed that the green area ratio had negative(－) correlation and impermeable pavement ratio had positive(＋) correlation. Building-to-land ratio was not significant with inside temperature. A coefficient of correlation between the temperature value and the value of permeable pavement ratio added up green area ratio was higher than a coefficient of correlation between the temperature value and the value of permeable pavement ratio added up impermeable pavement ratio. Thus we may define that permeable pavement area decrease urban temperature with green area in apartment complex. Floor area ratio had no significant correlation with inside temperature. Inside temperature was decreased as the NDVI was increased. To establish the temperature distribution model in a development apartment complex, As the result of regression analysis between inside temperature as dependent variable and permeable pave ratio+green area ratio, green area ratio, building-to-land ratio and NDIT as independent variables, only permeable pavement ratio added up green area ratio of the independent variables was accepted fur regression equation in both two seasons and adjusted coefficient of determination was 41.4 on September, 2000 and 40.4 on June,2001.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.