• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.277-292
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• 2020

The purpose of this study is to propose the possibility of precise surface sedimentary facies classification and a more accurate classification method by generating the large-scale map of surface sedimentary facies based on UAV data and object-based image analysis (OBIA) for Hwang-do tidal flat in Cheonsu bay. The very high resolution UAV data extracted factors that affect the classification of surface sedimentary facies, such as RGB ortho imagery, Digital elevation model (DEM), and tidal channel density, and analyzed the principal components of surface sedimentary facies through statistical analysis methods. Based on principal components, input data to be used for classification of surface sedimentary facies were divided into three cases such as (1) visible band spectrum, (2) topographical elevation and tidal channel density, (3) visible band spectrum and topographical elevation, tidal channel density. The object-based image analysis classification method was applied to map the classification of surface sedimentary facies according to conditions of input data. The surface sedimentary facies could be classified into a total of six sedimentary facies following the folk classification criteria. In addition, the use of visible band spectrum, topographical elevation, and tidal channel density enabled the most effective classification of surface sedimentary facies with a total accuracy of 63.04% and the Kappa coefficient of 0.54.

• Journal of Korean Society of Forest Science
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• v.83 no.3
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• pp.322-330
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• 1994

The Universal Soil Loss Equation (USLE) has been widely used to predict long-term soil loss by incorporating several erosion factors, such as rainfall, soil, topography, and vegetation. This study is aimed to introduce the LISLE within geographic information system(GIS) environment. The Kwangneung Experimental Forest located in Kyongki Province was selected for the study area. Initially, twelve years of hourly rainfall records that were collected from 1982 to 1993 were processed to obtain the rainfall factor(R) value for the LISLE calculation. Soil survey map and topographic map of the study area were digitized and subsequent input values(K, L, S factors) were derived. The cover type and management factor (C) values were obtained from the classification of Landsat Thematic Mapper(CM) satellite imagery. All these input values were geographically registered over a common map coordinate with $25{\times}25m^2$ ground resolution. The USLE was calculated for every grid location by selecting necessary input values from the digital base maps. Once the LISLE was calculated, the resultant soil loss values(A) were represented by both numerical values and map format. Using GIS to run the LISLE, it is possible to pent out the exact locations where soil loss potential is high. In addition, this approach can be a very effective tool to monitor possible soil loss hazard under the situations of forest changes, such as conversion of forest lands to other uses, forest road construction, timber harvesting, and forest damages caused by fire, insect, and diseases.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.363-368
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• 2003

We have successfully developed a more effective algorithm to extract the lineament in the area covered by wide alluvial deposits characterized by a relatively narrow range of brightness in the Landsat TM image, while the currently used algorithm is limited to the mountainous areas. In the new algorithm, flat areas mainly consisting of alluvial deposits were selected using the Local Enhancement from the Digital Elevation Model (DEM). The aspect values were obtained by 3${\times}$3 moving windowing of Zevenbergen & Thorno's Method, and then the slopes of the study area were determined using the aspect values. After the lineament factors in the alluvial deposits were revealed by comparing the threshold values, the first rank lineament under the alluvial deposits were extracted using the Hough transform In order to extract the final lineament, the lowest points under the alluvial deposits in a given topographic section perpendicular to the first rank lineament were determined through the spline interpolation, and then the final lineament were chosen through Hough transform using the lowest points. The algorithm developed in this study enables us to observe a clearer lineament in the areas covered by much larger alluvial deposits compared with the results extracted using the conventional existing algorithm. There exists, however, some differences between the first rank lineament, obtained using the aspect and the slope, and the final lineament. This study shows that the new algorithm more effectively extracts the lineament in the area covered with wide alluvlal deposits than in the areas of converging slope, areas with narrow alluvial deposits or valleys.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.517-525
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• 2013

Time-series data of Normal Difference Vegetation Index (NDVI) obtained by the Moderate-resolution Imaging Spectroradiometer(MODIS) satellite imagery gives a waveform that reveals the characteristics of the phenology. The waveform can be decomposed into harmonics of various periods by the Fourier transformation. The resulting $n^{th}$ harmonics represent the amount of NDVI change in a period of a year divided by n. The values of each harmonics or their relative relation have been used to classify the vegetation species and to build a vegetation map. Here, we propose a method to estimate the annual amount of carbon absorbed on the forest from the $1^{st}$ harmonic NDVI value. The $1^{st}$ harmonic value represents the amount of growth of the leaves. By the allometric equation of trees, the growth of leaves can be considered to be proportional to the total amount of carbon absorption. We compared the $1^{st}$ harmonic NDVI values of the 6220 sample points with the reference data of the carbon absorption obtained by the field survey in the forest of South Korea. The $1^{st}$ harmonic values were roughly proportional to the amount of carbon absorption irrespective of the species and ages of the vegetation. The resulting proportionality constant between the carbon absorption and the $1^{st}$ harmonic value was 236 tCO2/5.29ha/year. The total amount of carbon dioxide absorption in the forest of South Korea over the last ten years has been estimated to be about 56 million ton, and this coincides with the previous reports obtained by other methods. Considering that the amount of the carbon absorption becomes a kind of currency like carbon credit, our method is very useful due to its generality.