Education on fine dust is a challenging field, as it must explain abstract phenomena and accompany the demands for behavioral changes. This research studied whether the adoption of augmented reality (AR) technology can effect change in student perspectives with a view to improving the attitudes of passive students regarding fine dust-related matters. With regard to student awareness, 94.0% of students responded that the issue of fine dust in Korea is severe; the higher the degree of interest they had in fine dust, the more severe they perceived the issue to be. On the perceived severity of fine dust in schools, 47.8% viewed it as severe; again, the level differed by the degree of interest. Students (80%) who received a traditional education on fine dust expressed dissatisfaction. The effect of using AR in experiential learning in fine dust environmental education has shown enhanced results compared to before receiving the education, notably in the group with a low degree of interest in fine dust and the group without prior experience in fine dust environmental education. Likewise, in the satisfaction rate for AR-based education on fine dust, 72.5% of participants responded that they had enjoyed the class, 75.9% showed active participation, and 80.0% felt that the content of the education was useful. Considering that the objective of fine dust environmental education is not based on understanding a theory but on maintaining individual health through practice in real life, the use of AR in fine dust environmental education as applied in this study may be interpreted as having a certain level of effect. Additionally, our results demonstrate that the use of AR in classes is effective in arousing students’ interest and inducing participation for better engagement in learning activities, which is, consequently, effective in enhancing the understanding of learning materials by students.

This study evaluated the influence of fine dust environmental education on 90 elementary and middle school students, taking into account factors such as sex, place of residence, experience with environmental education, and experience with augmented reality (AR). The goal was to assess changes in students’ awareness and attitudes towards fine dust. Results showed that fine dust environmental education positively influenced students’ awareness of fine dust. Further analysis by factors revealed that the education was effective regardless of these factors. In addition to increasing awareness of the seriousness of fine dust, students’ attitudes also changed positively. The study conducted a statistical analysis of changes in 10 types of attitudes among the target students before and after our education. After the implementation of the education, students’ attitudes changed positively in all 10 types of attitudes, including checking the weather, restricting activities, personal hygiene, wearing masks, environmental education, separating garbage and cleaning, classroom silence, classroom ventilation, home cleaning, and home environment with statistical significance. These findings underscore the effectiveness and importance of combining fine-dust environmental education with AR technology and can inform the planning of educational programs aimed at improving students’ awareness and attitudes.

The purpose of this research is to extract spectral reflectance characteristics of concretes through basic experiment on concrete specimens and site experiment on actual concrete structures using a field portable spectrometer and a VNIR hyperspectral sensor. A spectrometer (GER-3700) and a VNIR hyperspectral camera (AisaEagle VNIR Hyperspectral Camera) were utilized for extracting spectral characteristics of concrete specimens and actual concrete structures. General concretes show similar pattern with correlation more than 80%, while super high strength concrete shows very different aspect from general concretes. The GER-3700 spectrometer and the VNIR camera were applied to extracting spectral characteristics of the actual concrete structures such as a bridge slab and pier in road construction site. We also made certain in not only interior experiment on concrete specimens but also site experiment on actual concrete structures that both the spectrometer and the VNIR camera vary in spectral reflectance depending on concrete strength. Afterwards if the studies on hyperspectral characteristics of worn-out concretes, concrete aggregate condition diversity, super high-strength concretes are performed in depth, it is helpful in stability evaluation and maintenance management of concrete-based structures or facilities using airborne or satellite hyperspectral images for a wide area.

Climate simulation is often used for evaluation of the sustainability of a species in global scale but not applicable for our study because the global data is too coarse to be used in small and fragmented habitat areas. We examined a weather forecasting model for the habitat analysis of the endangered species of the Korean long-tailed goral (Naemorhedus caudatus raddeanus). The weather research forecasting (WRF) model is implemented to downscale global climate data for a small fragmented habitat of the goral. The coordinates of goral fecal samples were collected during winter 2005 and summer 2006 using GPS and the goral habitat was set with the elevations of fecal samples mostly found. The atmospheric parameters of the habitat were then simulated by WRF and defined as the atmospheric signature of the goral suitable habitat. A series of temperature changes was then projected for the period from 2010s to 2090s to evaluate the change of the habitat for summer (June) and winter (December) seasons. As a result, the suitable habitat of the Korean long-tailed goral would be significantly declined and almost disappeared in the 2070s for summer or 2050s for winter under the climate scenarios of RCP 8.5 by IPCC.

NDVI is often used to investigate how vegetation contributes to the surface urban heat islands (SUHI) effect. Generally, NDVIs obtained for partially vegetated or built-up areas have been found to be less than 0.4. However, anomalous NDVIs that are inconsistent with established concepts and relationships are frequently obtained for non-vegetated urban land cover. It is possible that these anomalous NDVIs have been distorted by the surface colors and patterns of rooftops. Therefore, we obtained NDVIs for an urban industrial area of Gumi, South Korea, and investigated how these NDVIs were affected by such surface colors and patterns. By assessing 148 factory rooftops, obtained NDVIs indeed showed a tendency to be affected by the surface colors and patterns of rooftops. A color classification of white, blue, purple, and red revealed that blue- and purple-colored rooftops resulted in higher NDVIs than other rooftops. Moreover, these rooftops were sometimes misidentified as forest and vegetation. The color tone, affected by brightness intensity, also contributed to the NDVIs obtained for blue- and purple-colored rooftops. Extreme cases showed that NDVIs obtained for rooftop surfaces could attain values indicative of dense vegetation (i.e., NDVIs ≥ 0.6), when blue-colored rooftops were combined with complex surface patterns that generated more shadow. From these results, we concluded that the established relationship between LST and NDVI is likely to be invalid for non-vegetated urban industrial areas, and that NDVIs obtained for such areas should be used with caution, particularly in studies of the SUHI effect.