• Journal of The Geomorphological Association of Korea
• /
• v.24 no.1
• /
• pp.63-76
• /
• 2017

This research was classified mountain areas with high ecological, environmental and resource value among the macro scaled terrain that can be checked at the space scale of less than 1:1,000,000 and analyzed the topographical characteristics. It has been confirmed that the mountains of the Korean peninsula belong to the groups IV, V, VI(classification by Kapos et al.(2000)) as a result of applying the quantitative standards for designation of mountain areas to the global mountain system. The area of mountains calculated using high resolution DEM is equivalent to 48% of the area of the Korean peninsula, and the result is quite different from the general idea of which 70% is the mountain area of the Korean peninsula. The mountain areas show the distribution of geomorphons, that is different from the plains and the hills and also, it shows the differences between the mountains of the groups IV~ VI classified according to the altitude. As a result of analyzing the relations among type pattern, slope, and relief, specific geomorphons are concentrated at $10^{\circ}$ and $20^{\circ}$ and it shows the possibility to classify the mountainous areas into two groups based on the result that the distribution of landform patterns are bimodal in the relation to the amount of relief.

• The Journal of the Acoustical Society of Korea
• /
• v.14 no.2
• /
• pp.101-112
• /
• 1995

In order to construct a feature map-based phoneme classification system for speech recognition, two procedures are usually required. One is clustering and the other is labeling. In this paper, we present a phoneme classification system based on the Kohonen's Self-Organizing Feature Map (SOFM) for clusterer and labeler. It is known that the SOFM performs self-organizing process by which optimal local topographical mapping of the signal space and yields a reasonably high accuracy in recognition tasks. Consequently, SOFM can effectively be applied to the recognition of phonemes. Besides to improve the performance of the phoneme classification system, we propose the learning algorithm combined with the classical K-mans clustering algorithm in fine-tuning stage. In order to evaluate the performance of the proposed phoneme classification algorithm, we first use totaly 43 phonemes which construct six intra-class feature maps for six different phoneme classes. From the speaker-dependent phoneme classification tests using these six feature maps, we obtain recognition rate of $87.2\%$ and confirm that the proposed algorithm is an efficient method for improvement of recognition performance and convergence speed.

• Journal of Korean Society of Rural Planning
• /
• v.3 no.2
• /
• pp.102-111
• /
• 1997

For rational agricultural land use planning, it is quite necessary to get hold of land suitability precisely and to make decision on land use patterns accordingly. In the methodological viewpoint, objective and scientific evaluation techniques for land suitability classification should be supported for the systematic land use planning. As one of technical development approaches to rational land use planning, this study tried to frame a land suitability evaluation system for agricultural purposes. Evaluation unit is defined as a tract of land bounded by road, other land units and topographical features. And quantification theory was applied in the determination works of evaluation criteria. The administrative area of Namsa-myon(district), Yongin-si(city), Kyunggi-do(province) was selected for the case study. In order to check the feasibility of the evaluation system developed in the study, field check team, consisting of 2 government officers and 2 representative farmers, carried out evaluation works by observation on 148 sample land units, 10% of total 1,480 ones. Between estimated and observed results, there showed very good relationship of its multiple correlation coefficient, R=0.9467.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.1415-1417
• /
• 2003

In this study, as the passing of a year, the changes of tidal flat area in Seohan Bay, North Korea was monitored through using Landsat ETM Data and the ancient topological map. The map to present tidal flat distribution characteristic based on the ancient topographical map (1918) was constructed as GIS DB. In addition, a tidal flat distribution map was estimated by using the satellite images with unsupervised classification method. Even though it is difficult to approach to study area, it was possible to gain the data and to monitor the change of the coast tidal flat by comparing to area change yielded.

• Journal of The Geomorphological Association of Korea
• /
• v.17 no.1
• /
• pp.1-14
• /
• 2010

This paper deals with the classification and distribution of geomorphic surfaces and analysis on effects of geomorphic processes on the landforms in the inaccessable DMZ (Demilitarized Zone) to Wonsan Bay of East Sea coast of Chugaryeong Rift Valley, Central Korea. DEM (Digital Elevation Model) and Landsat images are used for the above anlaysis. The geomorphic surfaces are classified by TPI (Topographical Position Index) for the analysis of the convexity and concavity calculated using topographical elements such as elevation, steepness, and relief. In the Chugayreong Valley, 10 geomorphic surfaces are classified as steep valley, shallow valley, upland drainage, U-shaped valley, plain, open slope, upper slope, local ridge, midslope ridge, and high ridge. Zonal Statistics presents average characteristics of geomorphological processes of surfaces by the relationships between bedrock and relief, surface and relief, and between surface and NDVI. So, these analysis can help to understand geomorphological process such as dissection of lava plateau and watershed divide evolution.

• Spatial Information Research
• /
• v.20 no.6
• /
• pp.129-137
• /
• 2012

For construction project in extreme cold region, it is essential to establish basic data on the site such as topographical data from the early stage of construction of planning and designing, and it is needed to frequently perform site investigation when necessary. However, extreme cold regions are characteristic of being at long distance and difficult in approaching, and special regions such as Antarctica, in particular, are hard to conduct site investigation. Although a site investigation may be conducted, those who can visit Antarctica are sufficiently limited so that most of the staff may participate in construction without knowledge of the site and increase the risk of errors in decision making or designing. In order to resolve such problems, the authors in this study identified methods of building wide-area topographical data and bedrock classification data of exposed areas via remote sensing and of building precise topographical data on the construction site. Also, the authors attempted to present methods by which such data can be managed and visualized integrally via three-dimensional GIS technology and all the participants in construction can learn sense of field and conduct necessary analysis as frequent as possible. The areas around the Jangbogo Antarctic Station were selected to be the research area for conducting effective integrational management and three-dimensional visualization of various spatial data such as wide-area digital elevation model, ortho-images, bedrock classification data, local precise digital elevation model, and site images. The results of this study may enable construction firms to analyze local environments for construction whenever they need for construction in extreme cold regions and then support construction work including decision making or designing.

• Korean Journal of Environment and Ecology
• /
• v.26 no.3
• /
• pp.382-393
• /
• 2012

The purpose of this study was to research the vegetation structure of the Bongamsa Forest Genetic Resourses Resreve Area in Mt. Heuyang, Mungyeong, Gyeongsangbuk-do. For doing this, ninety-two plots($100m^2/plot$) were set up and investigated, and then Classification analysis and Ordination analysis were carried out. As a result, the vegetation of this area is divided to nine communities; Quercus mongolica community, Quercus variabilis community, Pinus densiflora community, Pinus densiflora-Quercus serrata community, Pinus densiflora-Quercus mongolica community, Quercus serrata community, Decideous broad leaf community, Pinus koraiensis community, Larix kaempferi community. To compare between the communities, statistical analyses were conducted with topographical condition and the results of the vegetational investigation of each community. In altitude, slope, the number of species, the number of individuals in canopy and the number of individuals of understory layer, the mean averages among the communities were different in statistically significance. Then we analysed the vegetation community structure with Importance Percentage of each stratum. The oak tree communities were expected to keep or expand the actual communities because oak trees are spread widely in canopy and understory layers. But the pine tree dominant communities were expected to be succeeded to oak tree communities in the future because of the wide expansion of oak trees.

• Journal of The Geomorphological Association of Korea
• /
• v.25 no.3
• /
• pp.1-18
• /
• 2018

In Korea, 64% of the land is known as mountain area, but the definition and classification standard of mountain are not clear. Demand for utilization and development of mountain area is increasing. In this situation, the unclear definition and scope of the mountain area can lead to the destruction of the mountain and the increase of disasters due to indiscreet permission of forestland use conversion. Therefore, this study analyzed the variables and criteria that can extract the mountain boundaries through the questionnaire survey and the terrain analysis. We developed a mountain boundary extraction algorithm that can classify topographic mountain by using selected variables. As a result, 72.1% of the total land was analyzed as mountain area. For the three catchment areas with different mountain area ratio, we compared the results with the existing data such as forestland map and cadastral map. We confirmed the differences in boundary and distribution of mountain. In a catchment area with predominantly mountainous area, the algorithmbased mountain classification results were judged to be wider than the mountain or forest of the two maps. On the other hand, in the basin where the non-mountainous region predominated, algorithm-based results yielded a lower mountain area ratio than the other two maps. In the two maps, we was able to confirm the distribution of fragmented mountains. However, these areas were classified as non-mountain areas in algorithm-based results. We concluded that this result occurred because of the algorithm, so it is necessary to refine and elaborate the algorithm afterward. Nevertheless, this algorithm can analyze the topographic variables and the optimal value by watershed that can distinguish the mountain area. The results of this study are significant in that the mountain boundaries were extracted considering the characteristics of different mountain topography by region. This study will help establish policies for stable mountain management.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.3D
• /
• pp.445-450
• /
• 2008

Recently, environmental and ecological approaches is in progress in urban stream, especially the guarantee of instream flow becomes very important. In this paper, it is suggested that water volume estimation method utilizing the topographical shape data obtained by field investigation and satellite image to manage the urban stream efficiently. The data obtained at Gap River is the study area are analysed and those results are as belows. First, surveying to investigate topographic shape characteristics of urban stream is carried out. In details, the gradient characteristics from water surface to bottom in case of sand area and in case of grass area are 0.013 and 0.065 respectively. In conclusion, the gradient characteristic of grass area is five times bigger than that of sand area. Besides, IKONOS image is classified by spectrum analysis and Minimum Distance Method and the sand area extraction method by the generalization method as Median filter is suggested to calculate water volume. Finally, mapping process on the sand area extracted from the topographical shape field data in river and satellite images is carried out by the GIS spatial analysis. And on the assumption that the water level was 1m at that time when satellite image was taken, the water volume was $225,258m^3$. It is clarified that the effect of water volume improvement was about 10.5% in comparison with water volume that had no consideration on the gradient characteristics of sand-bar.

• Journal of the Korean earth science society
• /
• v.22 no.2
• /
• pp.138-146
• /
• 2001

The land cover over Korean peninsula was classified using a multi-temporal NOAA/AVHRR (Advanced Very High Resolution Radiometer) data. Four types of phenological data derived from the 10-day composited NDVI (Normalized Differences Vegetation Index), maximum and annual mean land surface temperature, and topographical data were used not only reducing the data volume but also increasing the accuracy of classification. Self organizing feature map (SOFM), a kind of neural network technique, was used for the clustering of satellite data. We used a decision tree for the classification of the clusters. When we compared the classification results with the time series of NDVI and some other available ground truth data, the urban, agricultural area, deciduous tree and evergreen tree were clearly classified.