• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.306-309
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• 2004

The susceptibility of landslides and the effect of landslide-related factors at Penang in Malaysia using the Geographic Information System (GIS) and remote sensing data have been evaluated. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land use from Landsat TM (Thermatic Mapper) satellite images; and the vegetation index value from SPOT HRV (High Resolution Visible) satellite images. Landslide hazardous areas were analysed and mapped using the landslide-occurrence factors employing the probability-frequency ratio method. To assess the effect of these factors, each factor was excluded from the analysis, and its effect verified using the landslide location data. As a result, land 'cover had relatively positive effects, and lithology had relatively negative effects on the landslide susceptibility maps in the study area. In addition, the landslide susceptibility maps using the all factors showed the relatively good results.

• 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.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.635-646
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• 2018

This study sought to identify the characteristics of seasonal concentration differences of particulate matter influenced by land cover types associated with particulate matter emission and reductions, namely forest and urbanized regions. PM10 and PM2.5 was measured with quantitative concentration in 2016 on 23 urban air monitoring stations in Seoul, classified the stations into 3 groups based on the ratio of urbanized and forest land covers within a range of 3km around station, and analysed the differences in particulate matter concentration by season. The center values for the urbanized and forest land covers by group were 53.4% and 34.6% in Group A, 61.8% and 16.5% in Group B, and 76.3% and 6.7% in Group C. The group-specific concentration of PM10 and PM2.5 by season indicated that the concentration of Group A, with high ratio of forests, was the lowest in all seasons, and the concentration of Group C, with high ratio of urbanized regions, had the highest concentration from spring to autumn. These inter-group differences were statistically significant. The concentration of Group C was lower than Group B in the winter; however, the differences between Groups B to C in the winter were not statistically significant. Group A concentration compared to the high-concentration groups by season was lower by 8.5%, 11.2%, 8.0%, 6.8% for PM10 in the order of spring, summer, autumn and winter, and 3.5%, 10.0%, 4.1% and 3.3% for PM2.5. The inter-group concentration differences for both PM10 and PM2.5 were the highest in the summer and grew smaller in the winter, this was thought to be because the forests' ability to reduce particulate matter emissions was the most pronounced during the summer and the least pronounced during the winter. The influence of urbanized areas on particulate matter concentration was lower compared to the influence of forests. This study provided evidence that the particulate matter concentration was lower for regions with higher ratios of forests, and subsequent studies are required to identify the role of green space to manage particulate matter concentration in cities.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.64-64
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• 2003

The aim of this study is to apply and verify of logistic regression at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database.13${\times}$1ure, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the logistic regression coefficient were overlaid for landslide susceptibility mapping. Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.371-384
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• 2015

Although GOCI has potential for land surface monitoring, there have been only a few cases for land applications. It might be due to the lack of reliable land products derived from GOCI data for end-users. To use for land applications, it is often essential to provide cloud-free composite over land surfaces. In this study, we proposed a cloud detection method that was very important to make cloud-free composite of GOCI reflectance and vegetation index. Since GOCI does not have SWIR and TIR spectral bands, which are very effective to separate clouds from other land cover types, we developed a multi-temporal approach to detect cloud. The proposed cloud detection method consists of three sequential steps of spectral tests. Firstly, band 1 reflectance threshold was applied to separate confident clear pixels. In second step, thick cloud was detected by the ratio (b1/b8) of band 1 and band 8 reflectance. In third step, average of b1/b8 ratio values during three consecutive days was used to detect thin cloud having mixed spectral characteristics of both cloud and land surfaces. The proposed method provides four classes of cloudiness (thick cloud, thin cloud, probably clear, confident clear). The cloud detection method was validated by the MODIS cloud mask products obtained during the same time as the GOCI data acquisition. The percentages of cloudy and cloud-free pixels between GOCI and MODIS are about the same with less than 10% RMSE. The spatial distributions of clouds detected from the GOCI images were also similar to the MODIS cloud mask products.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.5
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• pp.27-35
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• 2010

The characteristics of delivered nutrient loads were analyzed and the regression equations to estimate delivery ratios of nutrients (TN and TP) were developed using HSPF simulation results at six subwatersheds within the Bochung A unit watershed during 1998-2007. TN delivery ratio was higher than TP delivery ratio because significant amounts of TP was considered to be attached at soil as ${PO_4}^-$ during delivery process from discharged point of nutrient source to main stream. As a results of correlation analysis, factors related to geomorphic characteristics had not statistical correlation with TN and TP delivery ratios. TN loading rate from living and specific stream flow had statistical negative and positive correlation, respectively, with TN delivery ratio. TP loading rates from all sources and from land cover and specific stream flow had statistical negative, negative and positive correlation, respectively. The specific stream flow represents the most strong correlation with nutrient delivery ratios. The regression equations to estimate delivery ratios for TN and TP were developed by including statistical correlated factors and showed high efficiency of 0.98 and 0.95 of coefficient of determination for TN and TP, respectively.

• Journal of Environmental Impact Assessment
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• v.17 no.4
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• pp.243-253
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• 2008

The purpose of this study was to simulate the reduction effect of soil loss in the Yongdam reservoir watershed using SWAT model. To evaluate accuracy for flow and sediment yield of SWAT model, calibration was performed for the period from Jan. 2002 to Dec. 2003, and the verification for Jan. 2005 to Dec. 2005. The calibration and the verification were carried out using data observed at the Cheoncheon gaging station. The $R^2$ and EI values in terms of a flow were 0.8 and 0.78 respectively for calibration, whereas they for verification were 0.88 and 0.86 respectively. In terms of a sediment yield, they were 0.7 and 0.48 respectively for calibration, whereas for verification were 0.64 and 0.54 respectively. As a results from model simulation, annual mean soil loss rates in terms of forest, paddy and upland were 0.02 ton/ha/yr, 0.15 ton/ha/yr and 7.58 ton/ha/yr, respectively. The results show that the land use type of a upland has more significant impact on a total soil loss as well as a sediment yield than other types of land use. The sediment delivery ratio was determined to be about 0.35. In this study 2 land cover change scenarios for upland area were considered. These scenarios were used an input to SWAT model in order to evaluate their impact on soil loss and sediment delivery. The results show that a reduction of the upland area would reduce the soil loss and sediment yield.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.3
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• pp.39-45
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• 2010

Quantification of carbon absorption and understanding the human induced land use changes (LUC) forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by LUC through remote sensing technology. The Landsat imagery four time periods was classified with the hybrid classification method in order to quantify carbon absorption by LUC. Thereafter, for estimating the amount of carbon absorption, the stand biomass of forest was estimated with the total weight, which was the sum of individual tree weight. Individual tree volumes could be estimated with the crown width extracted from digital forest cover type map. In particular, the carbon conversion index and the ratio of the $CO_2$ molecular weight to the C atomic weight, reported in the IPCC guideline, was used to convert the stand biomass into the amount of carbon absorption. Total carbon absorption has been modeled by taking areal estimates of LUC of four time periods and carbon factors for land use type and standing biomass. Results of this study, through LUC suggests that over a period of construction, 7.10 % of forest and 9.43 % of barren were converted into urban. In the conversion process, there has been a loss of 6.66 t/ha/y (7.94 %) of carbon absorption from the study area.

• Journal of Bio-Environment Control
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• v.31 no.2
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• pp.114-124
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• 2022

The Saemangeum has a dry surface characteristic with a low moisture content ratio due to the saline and silt soil, so the vegetation cover is low compared to other areas. In areas with low vegetation cover, wind erosion has a high probability of scattering dust. If the vegetation cover is increased by cultivating crops that can withstand the Saemangeum reclaimed environment, scattering dust can be reduced by reducing the flow rate at the bottom. Thus, the purpose of this study is to analyze the effect of suppressing the generation of fine dust and scattering dust by cultivating winter forage crops on the Saemangeum reclaimed land. While growing 0.5 ha of barley and 0.5 ha of triticale in Saemangeum reclaimed land, the concentration of fine dust was monitored according to agricultural work and growth stage. Changes in the concentrations of PM-10, PM-2.5, and PM-1.0 were monitored on the leeward, the windward and centering on the crop field. As a result of monitoring, PM-1.0 had little effect on crop cultivation. the concentration of PM-10 and PM-2.5 increased according to tillage and harvesting, and tillage had a higher increasing the concentration of PM-10 and PM-2.5 than that of harvesting. According to the growth stage of crops, the effect of suppressing scattering dust was shown, and the effect of suppressing scattering dust was higher in the heading stage than in the seedling stage. So, it was found that there was an effect of suppressing scattering dust other than the effect of land covering. Through this study, it was possible to know about the generation and suppression effect of scattering dust according to crop cultivation.

• 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.