Gi-Seong Jeon, Wonkook Kim. Korean J. Remote Sens. 2024;40:1127-39. https://doi.org/10.7780/kjrs.2024.40.6.1.20

The urban heat island (UHI) has been a critical social problem as urbanization intensifies worldwide, significantly impacting human life by exacerbating heat-related health issues, increasing energy demand for cooling, and resulting in associated environmental problems. However, the fine-scale diurnal and spatial characteristics of UHI remain poorly understood due to the limited resolution of traditional satellite datasets. This study aims to quantify the diurnal and spatial dynamics of surface urban heat islands (SUHI) in Busan and Daegu—the two hottest metropolitan cities in Korea—by integrating high-resolution ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) (70 m) and Geostationary Korea Multi-Purpose Satellite-2A (GK-2A) (2 km) land surface temperature (LST) data. Using the combined datasets, season-representative diurnal LST variations were characterized, and locational heat intensification (LHI) was evaluated across land use types and densities at sub-district scales. The results show that the maximum SUHI intensity reached 10 °C in Daegu and 7 °C in Busan during summer, up to 8 °C higher than estimates from coarse-resolution data. Industrial areas recorded the highest LST (47 °C in Daegu and 43 °C in Busan) with rapid morning intensification rates of 2.0 °C/h and 1.9 °C/h, respectively. Dense urban land uses amplified LHI by nearly twofold compared to less dense urban areas. These findings emphasize the critical role of land use density and industrial heat emissions in shaping urban thermal environments, providing key insights for use in urban heat mitigation and climate-adaptive planning.

This study develops an immersive marine Information and Communication Technology (ICT) convergence framework designed to enhance coastal climate resilience by improving accessibility, visualization, and communication of scientific research on Dokdo (Dok Island) in the East Sea. High-resolution spatial datasets, multi-source marine observations, underwater imagery, and validated research outputs were integrated into an interactive virtual-reality (VR) and web-based three-dimensional (3D) platform that translates complex geophysical and ecological information into intuitive experiential formats. A geospatially accurate 3D virtual model of Dokdo was constructed from maritime and underwater spatial data and coupled with immersive VR scenarios depicting sea-level variability, coastal morphology, wave exposure, and ecological characteristics. To evaluate practical usability and pro environmental public engagement, a three-phase field survey (n = 174) and a System Usability Scale (SUS) assessment (n = 42) were conducted. The results indicate high satisfaction (88.5%), strong willingness to re-engage (97.1%), and excellent usability (mean SUS score = 80.18), demonstrating the effectiveness of immersive content for environmental education and science communication crucial for achieving Sustainable Development Goal 14 targets. The proposed platform supports stakeholder engagement, affective learning, early climate risk perception, conservation planning, and multidisciplinary science–policy dialogue. In addition, it establishes a foundation for a digital twin system capable of integrating real-time ecological sensor data for environmental monitoring and scenario-based simulation. Overall, this integrated ICT-driven framework provides a transferable model for visualizing marine research outputs, enhancing public understanding of coastal change, and supporting sustainable and adaptive decision-making in small island and coastal regions.

The urban heat island (UHI) has been a critical social problem as urbanization intensifies worldwide, significantly impacting human life by exacerbating heat-related health issues, increasing energy demand for cooling and the associated environmental problems. To accurately assess the risk of heat intensification for human health and ecosystem, it is important to quantify the significance at specific times and locations. However, there have been little analyses that capture both the diurnal and spatial variations due to the limitations of traditional satellite datasets. This study investigates the fine-scale spatio-temporal behaviors of the heat island effect in Korea's most heat-impacted metropolitan cities, by utilizing relatively new land surface temperature (LST) data: ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). The analysis demonstrated that our high-resolution assessment revealed surface urban heat island (SUHI) intensities during summer to be 5–8 ℃ higher compared to those derived from coarse-resolution data. The intensification rates by land uses were also quantified with greater accuracy, showing that industrial areas experienced changes of up to roughly 2 ℃/hour during the early morning in summer. The spatial characteristics of heat intensification were examined across various land use types, revealing that densely clustered urban land uses can amplify heat intensification, with industrial areas experiencing a doubling effect.

The coastal waters of Ulleungdo and Dokdo form a transition zone where cold and warm currents intersect, resulting in highly variable marine conditions and sensitive changes in macroalgal distribution. Improving the accuracy of remote-sensing-based macroalgae classification in such environments requires a region-specific dataset that systematically compiles taxon-level spectral reflectance. In this study, we designed a passive underwater observation system (type-1) and an active multi-purpose observation system (type-2), and acquired spectral reflectance using three observation methods applied to underwater and ground environments: T1U (type-1, underwater, natural sunlight), T2U (type-2, underwater, LED illumination with shading cover), and T2G (type-2, ground, natural sunlight). The objective of this study was to build spectral reflectance data for dominant macroalgae in the Ulleungdo–Dokdo coastal region and to quantitatively evaluate observation-condition–dependent spectral characteristics and their implications for classification. Based on reflectance spectra obtained from the three observation methods, taxon-specific spectral shapes of Phaeophyceae, Chlorophyta, and Rhodophyta reproduced characteristic features consistent with previous reports, including reflectance humps near to 575, 600, and 650 nm for Phaeophyceae, a relatively flat spectral shape for Chlorophyta, and an absorption feature within 400-550 nm with reflectance humps near to 600 and 650 nm for Rhodophyta. Cross-method comparisons using two species measured in all three methods (Eisenia bicyclis and Codium fragile) showed that species-specific spectral shapes were consistently reproduced in both reflectance and first-derivative reflectance, confirming interoperability among T1U, T2U, and T2G. In T2U, localized noise was observed in the 400-500 nm range due to insufficient LED radiance, indicating the need for signal correction in the blue band region. Cosine-similarity analysis based on first-derivative reflectance indicated generally high within-taxon similarity among species (approximately 0.90-0.99), whereas mean between-taxon similarity was lower (approximately 0.75-0.89), demonstrating that taxon-level spectral shapes are quantitatively distinguishable. The spectral reflectance dataset and observation protocols developed in this study provide hyperspectral reflectance reference information for dominant macroalgae and benthic substrates in the Ulleungdo-Dokdo coastal region, supporting remote-sensing–based classification and distribution monitoring, observation-method design, and future standardization of macroalgal spectral data.