• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.28-43
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• 2022

This study classified UAV image-based physical spatial types for parks in urban areas of Changwon City and analyzed thermal comfort characteristics according to physical spatial types by comparing them with ENVI-met thermal comfort results. Physical spatial types were classified into four types according to UAV-based NDVI and SVF characteristics. As a result of ENVI-met thermal comfort, the T_MRT difference between the tree-dense area and other areas was up to 30℃ or more, and it was 19. 6℃ at 16:00, which was the largest during the afternoon. As a result of analyzing UAV-based physical spatial types and thermal comfort characteristics by time period, it was confirmed that the physical spatial types with high NDVI and high SVF showed a similar to thermal comfort change patterns by time when using UAV, and the physical spatial types with dense trees and artificial structures showed a low correlation to thermal comfort change patterns by time when using UAV. In conclusion, the possibility of identifying the distribution of thermal comfort based on UAV images was confirmed for the spatial type consisting of open and vegetation, and the area adjacent to the trees was found to be more thermally pleasant than the open area. Therefore, in the urban planning stage, it is necessary to create an open space in consideration of natural covering materials such as grass and trees, and when using artificial covering materials, it is judged that spatial planning should be done considering the proximity to trees and buildings. In the future, it is judged that it will be possible to quickly and accurately identify urban climate phenomena and establish urban planning considering thermal comfort through ground LIDAR and In-situ measurement-based UAV image correction.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.19-33
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• 2013

In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.