• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.3
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• pp.14-24
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• 2007

The purpose of this study was to investigate how the landscape characteristics and the physical factors of landscape would affect the preference for the Gapcheon in Daejeon Metropolitan City. The Gapcheon was divided in three sections of the outskirts, Expopark areas, and residential complexes. After selecting seven landscape points where the sections could be expressed best, photographs were taken both in the upstream and downstream direction. The questionnaire used to evaluate the river's landscape included 20 items of adverbs that described the form of the river and one item to rate the overall preference. By analyzing the 14 pictures taken, the occupancy rates of the landscape elements in terms of the sky, river, vegetation of the river, mountain, and artificial structures. Image factor analysis was conducted for each of the sections in order to analyze the landscape characteristics of the Gapcheon, and then regression analysis was conducted in order to analyze the relationships among the physical factors influencing the preference of the landscapes. The results were as follows : Factors that compose the visual characters of urban river were classified be the aesthetic factor, the emotional factor and the situation factor. These 3 factors showed a 65.8% total variance. The river landscape with the biggest preference was the one from the Daedeok Grand Bridge as the occupancy area of the mountain, sky, and river was large and distributed evenly and the vegetation of the river was in a good harmony with the surroundings. After carrying out regression analysis to examine the relationships between the visual preference of Gapcheon and the physical factors of landscape(the sky, river, vegetation of the river, mountain, and artificial structure), the following regressions model was made : PRE=5.906+0.017(river)-0.053(artificial structure)-0.060(vegetation of the river) (R-square=0.48).

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.49-54
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• 2011

Recently Korean government announced the vision for low-carbon green growth. Quantifying of the carbon storage, distribution, and change of urban trees is vital to understanding the role of vegetation in the urban environment. In the city planning the carbon storage estimation has become an important factor. In this paper, KOMPSAT-2 satellite imagery was used to develop a method to predict the urban forest carbon storage from the Normalized Difference Vegetation Index (NDVI) computed from a time sequence image data. The total carbon storage change by trees in the 6 administrative zonings of Jinju was estimated using the image data in 2007 and 2009. Therefore the paper presents a method based on the satellite images, which can estimate the spread of urban tree and carbon storage variation using KOMPSAT-2.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.2
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• pp.133-140
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• 2007

In this study we did the monitor the change of a urban land coverage to forecast and to deal with various city problems according to urban development. The amount of change of a land coverage used the landsat satellite image and was calculated by analyzing the situation and the distribution aspect of land cover of the road circumstance by time series. We interpreted two images which are taken picture different time and calculated the amount of the area change through integration of the spatial analysis technique of remote sensing and GIS for this study. We could create the development model of the urban area by continuous analysis of satellite and geographic data.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.136-146
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• 2015

The active control of a vehicle based on vehicle recognition is one of key technologies for the intelligent vehicle, and the part-based image representation is necessary to recognize vehicles with only partial shapes of vehicles especially in urban scene where occlusions frequently occur. In this paper, we implemented a part-based image representation scheme using non-negative tensor factorization(NTF) and realized a robust vehicle recognition system using the NTF feature. The result shows that the proposed method gives more intuitive part-based representation and more robust recognition in urban scene.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 1994.05a
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• pp.29-36
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• 1994

The purpose of this study is to suggest the basic design elements for dwelling environment planning of downtown in Taegu.The evaluation of the dwelling environment should be approached from the satisfaction and the cognitive of the residents, that are based on their desire and various values on the conditions of residential area. This paper concerns the satisfaction and the congnitive image structure of the residents in the various dwelling types, from which design elements for dwelling environments can be derived. The results are as folIows: 1) The analysis on the satisfaction of dwell ins environment shows lots of displeasure about the lack of open-spaces and the housing low-quality, neighborhood in Mun-hwa, Korean style housing and the low-rise apartment areas. In order to make the variety types of dowelling in downtown district, the improvement of housing qualities and the expantion of the urban facilities for the open-spaces and communities are need. 2) The design elements of dwelling environments in downtown find out the important planning elements for urban design. The evaluation of the cognitive image structures about the safety and affection should be considered in design for urban dwelling areas.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.322-325
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• 2004

Recently the domestic technologies to manage forest and to control all related information were developed very rapidly by integrating FGIS (Forest Geographic Information System) and IT (Information technology). However, there still exists a mapping problem for example when overlaying a topography maps scaled in 1/5,000 to a forest type map scaled in 1/25.000. Moreover, there is a greater need to introduce the advanced spatial technologies such as high-resolution satellite image such as IKONOS and GIS to forest. In this study, 3D high-resolution forest mapping system was developed to possibly overlay with all kinds of scale maps and provide the all detailed information by using high-resolution satellite image and GIS. Through this system, all related forest officials could have and maintain the data consistency for their job and share the standard forest database with other post.

• Korean Journal of Geomatics
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• v.5 no.1
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• pp.27-34
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• 2005

Unsupervised classification is an important area of research in image processing because supervised classification has the disadvantages such as long task-training time and high cost and low objectivity in training information. This paper focuses on unsupervised classification, which can extract ground object information with the minimum 'Spectral Angle Distance' operation on be behalf of 'Spectral Euclidian Distance' in the clustering process. Unlike previous studies, our algorithm uses the unit vector, not the spectral distance, to compute the cluster mean, and the Single-Pass algorithm automatically determines the seed points. Atmospheric correction for more accurate results was adapted on the Hyperion data and the results were analyzed. We applied the algorithm to the Hyperion and ETM+ data and compared the results with K-Means and the former USAM algorithm. From the result, USAM classified the water and dark forest area well and gave more accurate results than K-Means, so we believe that the 'Spectral Angle' can be one of the most accurate classifiers of not only multispectral images but hyperspectral images. And also the unit vector can be an efficient technique for characterizing the Remote Sensing data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.113-119
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• 2003

Building information is extremely important for many applications within the urban environment. Sufficient techniques and user-friendly tools for information extraction from remotely sensed imagery are urgently needed. This paper presents an automatic and manual approach for extracting footprints of buildings in urban areas from airborne Light Detection and Ranging (LIDAR) data. First a digital surface model (DSM) was generated from the LIDAR point data. Then, objects higher than the ground surface are extracted using the generated DSM. Based on general knowledge on the study area and field visits, buildings were separated from other objects. The automatic technique for extracting the building footprints was based on different window sizes and different values of image add backs, while the manual technique was based on image segmentation. A comparison was then made to see how precise the two techniques are in detecting and extracting building footprints. Finally, the results were compared with manually digitized building reference data to conduct an accuracy assessment and the result shows that LIDAR data provide a better shape characterization of each buildings.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.325-335
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• 2006

This paper evaluates and maps the quality of life in the Atlanta, Georgia metropolitan area in 2000. Three environmental variables from Landsat TM data, four socioeconomic variables from census data, and a hazard-related variable from toxic release inventory (TRI) database were integrated into a geographic information system (GIS) environment for the quality of life assessment. To solve the incompatibility problem in areal units among different data, the four socioeconomic variables aggregated by zonal units were spatially disaggregated into individual pixels. Principal components analysis (PCA) was employed to integrate and transform environmental, socioeconomic, and hazard-related variables into a resultant quality of life score for each pixel. Results indicate that the highest quality of life score was found around Sandy Springs, Roswell, Alphretta, and the northern parts of Fulton County along Georgia 400 whereas the lowest quality of life score was clustered around Smyma of Cobb County, the inner city of Atlanta, and Hartsfield-Jackson International Airport. The results also reveals that normalized difference vegetation index (NDVI) and relative risk from TRI facilities are two versatile indicators of environmental and socioeconomic quality of an urban area in the United States.

• Journal of Korean Society of Rural Planning
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• v.28 no.3
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• pp.25-33
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• 2022

Due to the standardized urban development since the industrial era, many urban spaces have experienced non-placeness. Recently, although interest in urban landscape, history, and cultural elements has been increasing, landscape management and control measures are being implemented mainly in large cities due to the low status of rural areas in the country. From this point of view, this study tried to lay the foundation for basic research in related fields by classifying the characteristics and types of streetscapes located near large cities, and to suggest directions that should be considered when managing streetscapes in the future. As a result of the analysis of landscape adjectives, the village felt secluded due to the low density compared to the city street overall, but it did not have a unique image of the region. Three factors were derived through factor analysis, and preference was affected in the order of aesthetic, regularity, and uniqueness. In addition, the research site was classified into three types through cluster analysis, and it was confirmed that the differences by type were due to aesthetics and naturalness. On the other hand, the uniqueness is generally low in all regions, so it seems that fundamental countermeasures are needed.