• Journal of IKEEE
• /
• v.28 no.3
• /
• pp.352-359
• /
• 2024

This paper proposes a CNN-ViT hybrid model that automatically evaluates the aesthetic quality of images by combining local and global features. In this approach, CNN is used to extract local features such as color and object placement, while ViT is employed to analyze the aesthetic value of the image by reflecting global features. Color composition is derived by extracting the primary colors from the input image, creating a color palette, and then passing it through the CNN. The Rule of Thirds is quantified by calculating how closely objects in the image are positioned near the thirds intersection points. These values provide the model with critical information about the color balance and spatial harmony of the image. The model then analyzes the relationship between these factors to predict scores that align closely with human judgment. Experimental results on the AADB image database show that the proposed model achieved a Spearman's Rank Correlation Coefficient (SRCC) of 0.716, indicating more consistent rank predictions, and a Pearson Correlation Coefficient (LCC) of 0.72, which is 2~4% higher than existing models.

• Journal of Korea Spatial Information System Society
• /
• v.2 no.2 s.4
• /
• pp.5-23
• /
• 2000

Since 1995, national and local governments have competitively initiated many and large GIS projects and audit for the projects becomes an important issue. So far, the audit in the Information Technology(IT) area has tried to deal with the issue but ineffectiveness has been found for the successful GIS project management. Effective auditing is a critical element for the project management. In order to establish a proper audit model for the GIS projects and to promote auditing activities in the projects, this study constructs two hypotheses and tries to prove them. The hypotheses are as follows : 1) For a good audits model for GIS, unique characteristics of a GIS project audit items and the scope of the audit need to be identified. 2) The scope of audit needs to be classified according to the requests from tasks in the projects. To prove the hypotheses, this study analyzes positive aspects of audit in IT and construction projects, clarifies the audit items in GIS projects by comparing with them, and classifies the scope of the GIS audit based on various types of GIS projects. As a results, 5 types of the GIS audit are identified : (1) audit for project management, (2) audit focused on IT, (3) audit characterized by GIS technologies, (4) GIS database audit and (5) consulting services for critical problems in the projects. In addition, 4 criteria in classifying the GIS projects are suggested for the GIS audit. The 4 criteria are domain, scope, duration, and GIS applications technologies. Especially, GIS technology considered in this study includes GIS software, methodologies for GIS development, GIS database and quality control of GIS data, which are not usually reflected in the existing studies about in GIS audit. Because the GIS audit depends on a type of GIS projects, scopes of the audit can be flexibly reconstructed in accordance with the types of GIS projects. This is a key to effective and realistic audit for the future GIS projects. Strategies for effective GIS audit are also proposed in terms of the following: GIS project management, goal establishment in each audit stage, documentation from GIS audit, timing strategies for intensive GIS audit, and designing team structure.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.27 no.2
• /
• pp.78-95
• /
• 2024

For the establishment and comparison of environmental plans across various domains, considering climate change and urban issues, it is crucial to build spatial data at the regional scale classified with consistent criteria. This study mapping the Local Climate Zone (LCZ) of Changwon City, where active climate and environmental research is being conducted, using the protocol suggested by the World Urban Database and Access Portal Tools (WUDAPT). Additionally, to address the fragmentation issue where some grids are classified with different climate characteristics despite being in regions with homogeneous climate traits, a filtering technique was applied, and the LCZ classification characteristics were compared according to the filtering radius. Using satellite images, ground reference data, and the supervised classification machine learning technique Random Forest, classification maps without filtering and with filtering radii of 1, 2, and 3 were produced, and their accuracies were compared. Furthermore, to compare the LCZ classification characteristics according to building types in urban areas, an urban form index used in GIS-based classification methodology was created and compared with the ranges suggested in previous studies. As a result, the overall accuracy was highest when the filtering radius was 1. When comparing the urban form index, the differences between LCZ types were minimal, and most satisfied the ranges of previous studies. However, the study identified a limitation in reflecting the height information of buildings, and it is believed that adding data to complement this would yield results with higher accuracy. The findings of this study can be used as reference material for creating fundamental spatial data for environmental research related to urban climates in South Korea.

• Korean Journal of Soil Science and Fertilizer
• /
• v.42 no.1
• /
• pp.21-28
• /
• 2009

Detailed information on soil characteristics is of great importance for the use and conservation of soil resources that are essential for human welfare and ecosystem sustainability. This paper introduces soil inventory of Korea focusing on national soil database establishment, information systems, use, and future direction for natural resources management. Different scales of soil maps surveyed and soil test data collected by RDA (Rural Development Administration) were computerized to construct digital soil maps and database. Soil chemical properties and heavy metal concentrations in agricultural soils including vulnerable agricultural soils were investigated regularly at fixed sampling points. Internet-based information systems for soil and agro-environmental resources were developed based on 'National Soil Survey Projects' for managing soil resources and for providing soil information to the public, and 'Agroenvironmental Change Monitoring Project' to monitor spatial and temporal changes of agricultural environment will be opened soon. Soils data has a great potential of further application in estimation of soil carbon storage, water capacity, and soil loss. Digital mapping of soil and environment using state-of-the-art and emerging technologies with a pedometrics concept will lead to future direction.

• Journal of Korea Spatial Information System Society
• /
• v.9 no.1
• /
• pp.105-115
• /
• 2007

Data mining extracts interesting knowledge from a large database. Among numerous data mining techniques, research work is primarily concentrated on clustering and association rules. The clustering technique of the active research topics mainly deals with analyzing spatial and attribute data. And, the technique of association rules deals with identifying frequent patterns. There was an advanced apriori algorithm using an existing bit-clustering algorithm. In an effort to identify an alternative algorithm to improve apriori, we investigated FP-Growth and discussed the possibility of adopting bit-clustering as the alternative method to solve the problems with FP-Growth. FP-Growth using bit-clustering demonstrated better performance than the existing method. We used chess data in our experiments. Chess data were used in the pattern mining evaluation. We made a creation of FP-Tree with different minimum support values. In the case of high minimum support values, similar results that the existing techniques demonstrated were obtained. In other cases, however, the performance of the technique proposed in this paper showed better results in comparison with the existing technique. As a result, the technique proposed in this paper was considered to lead to higher performance. In addition, the method to apply bit-clustering to GML data was proposed.

• Journal of the Korean Geotechnical Society
• /
• v.38 no.7
• /
• pp.5-24
• /
• 2022

The current performance evaluation of slope anchors qualitatively determines the physical bonding between the anchor head and ground as well as cracks or breakage of the anchor head. However, such performance evaluation does not measure these primary factors quantitatively. Therefore, the time-dependent management of the anchors is almost impossible. This study is an evaluation of the 3D numerical model by SfM which combines UAS images with terrestrial LiDAR to collect numerical data on the damage factors. It also utilizes the data for the quantitative maintenance of the anchor system once it is installed on slopes. The UAS 3D model, which often shows relatively low precision in the z-coordinate for vertical objects such as slopes, is combined with terrestrial LiDAR scan data to improve the accuracy of the z-coordinate measurement. After validating the system, a field test is conducted with ten anchors installed on a slope with arbitrarily damaged heads. The damages (such as cracks, breakages, and rotational displacements) are detected and numerically evaluated through the orthogonal projection of the measurement system. The results show that the introduced system at the resolution of 8K can detect cracks less than 0.3 mm in any aperture with an error range of 0.05 mm. Also, the system can successfully detect the volume of the damaged part, showing that the maximum damage area of the anchor head was within 3% of the original design guideline. Originally, the ground adhesion to the anchor head, where the z-coordinate is highly relevant, was almost impossible to measure with the UAS 3D numerical model alone because of its blind spots. However, by applying the combined system, elevation differences between the anchor bottom and the irregular ground surface was identified so that the average value at 20 various locations was calculated for the ground adhesion. Additionally, rotation angle and displacement of the anchor head less than 1" were detected. From the observations, the validity of the 3D numerical model can obtain quantitative data on anchor damage. Such data collection can potentially create a database that could be used as a fundamental resource for quantitative anchor damage evaluation in the future.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.4 no.3
• /
• pp.13-20
• /
• 2001

The purpose of this study is development of the management and guide system for convenient use of new address guide system for systematic management and use of spatial information gained by mapping of numerical map of building and road to large basic new address, survey and input of main gate, decision of the road session, naming and input of road name, grant of numbering of all houses and buildings, new address guide, real life geographical information and added information service on web site in Jecheon-si city area. In this study, the development and establishment of new address management and guide system in local cities are designed by making full use of GIS function of client server based system. A guide system is designed the same database as management system, and it is transformed into Web GIS environment and developed in order to add the various functions of life GIS as well as new address guide. In the result, the effectiveness of new address system and guide of Jecheon-si city could be highly increased owing to not only citizens' easy access but also easy availability of various informations necessary in life by developed its system.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.11 no.1
• /
• pp.31-44
• /
• 2008

The 1st phase framework data implementation of National Geographic Information Systems (NGIS) used 1:5,000 digital map with 5 years updating period which is lacking in the latest information. This is a significant factor which hinders the use of framework data. This study proposed the efficient technical method of a location based object data management and system implementation for updating framework data. First, we did an object-oriented data modeling and database design using a location based features identifier(UFID: Unique Feature IDentifier). The second, we developed the system with various functions such as a location based UFID creation, input and output, a spatial and attribute data editing, an object based data processing using UML(Unified Modeling Language). Finally, we applied the system to the study area and got high quality data of 99% accuracy and 35% benefit effect of personnel expenses compare to the previous method. We expect that this study can contribute to the maintenance of national framework data as well as the revitalization of various GIS markets by providing user the latest framework data and that we can develop the methods of a feature-change modeling and monitoring using an object based data management.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.2
• /
• pp.57-70
• /
• 2012

The aim of this study is to analyse the landslide susceptibility and the future hazard in Inje, Korea using probability rainfalls and artificial neural network (ANN) environment based on geographic information system (GIS). Data for rainfall probability, topography, and geology were collected, processed, and compiled in a spatial database using GIS. Deokjeok-ri that had experienced 694 landslides by Typhoon Ewinia in 2006 was selected for analysis and verification. The 50% of landslide data were randomly selected to use as training data while the other 50% being used for verification. The probability of landslides for target years (1 year, 3 years, 10 years, 50 years, and 100 years) was calculated assuming that landslides are triggered by 1-day rainfall of 202 mm or 3-day cumulative rainfalls of 449 mm.

• Journal of Digital Convergence
• /
• v.14 no.5
• /
• pp.263-271
• /
• 2016

Localizing an object in image is a common task in the field of computer vision. As the existing methods provide a detection for the single object in an image, they have an utilization limit for the use of the application, due to similar objects are in the actual picture. This paper proposes an efficient method of object localization for image recognition. The new proposed method uses color correlation back-projection in the YCbCr chromaticity color space to deal with the object localization problem. Using the proposed algorithm enables users to detect and locate primary location of object within the image, as well as candidate regions can be detected accurately without any information about object counts. To evaluate performance of the proposed algorithm, we estimate success rate of locating object with common used image database. Experimental results reveal that improvement of 21% success ratio was observed. This study builds on spatially localized color features and correlation-based localization, and the main contribution of this paper is that a different way of using correlogram is applied in object localization.