• Korea Science and Art Forum
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• v.29
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• pp.305-318
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• 2017

The need for recognizing the crime in the urban spaces as a social problem and finding out specific approaches such as the study of space design and various guidelines for crime prevention is increasing. In this regard, "Crime Prevention Through Environmental Design" (marked as "CPTED") is actively underway. Yeomri-dong Salt Way is the first place to which the Seoul Crime Prevention Design Project was appled. The business objective of improving the local environment has been implemented rationally through cooperation and voluntary participation between subject of the project executives and community members. Since its efficiency has been proven, the sites have been expanded since then and becomes a benchmarking example of each local government.This kind of problem solving effort has the same context in purpose and direction of the 'Village Art Project' which has been implemented since 2009 with the aim of promoting the culture of the underdeveloped area and encouraging the participation of the residents by introducing the public art. It is noteworthy that this trend is centered around the characteristics of community functions and values. The purpose of this study is to propose the application method of community furniture as a way to increase the efficiency of CPTED to improve the 'quality of life' of residents. To do this, we reviewed CPTED, community design, public art literature and prior research, and identified the problems and implications based on the site visit Yeomri-dong of Seoul and Gamcheon Village of Pusan which is the successful model of "Seoul Root out Crime by Design" and 'Maeulmisul Art Project' respectively. The common elements of the two case places identified in this study are as follows: First, the 'lives' of community residents found its place in the center through the activation of community by collaborative activities in addition to the physical composition of the environment. Second, community design and introduction of public art created a new space, and thereby many people came to visit the village and revitalize the local economy. Third, it strengthened the natural monitoring, the territoriality and control, and the activity increase among the CPTED factors. The psychological aspect of CPTED and the emotional function of public art are fused with the 'community furniture', thereby avoiding a vague or tremendous approach to the public space through a specific local context based on the way of thinking and emotion of local people and it will be possible to create an environment beneficial for all. In this way, the possibility and implication of the fusion of CPTED and public art are expected to be able to reduce the social cost through the construction of the crime prevention infrastructure such as expansion of the CPTED application space, and to suggest a plan to implement the visual amenity as a design strategy to regenerate city.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1779-1790
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• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.