Coastal erosion, a worldwide social issue, has garnered substantial attention. Numerous methods have been implemented to control coastal erosion problems; however, the presence of rigid structures limits erosion mitigation, thereby causing various challenges. For instance, in the case of submerged breakwaters, local scour in front of the structure and scour caused by the flow occurring in open inlets affect the subsidence and stability of the structure and can also cause structural failure. To solve these problems, this paper proposes a hybrid method of using a submerged breakwater with an artificial coral reef installation; further, this study evaluates the attenuation of waves and mitigation of sediment transportation through large-scale 3D hydraulic experiments. We found that the hybrid method with an artificial coral reef installed in the open inlet shows excellent wave control and plays a clearly beneficial role in the advancement of the shoreline. The artificial coral reef method reduced the return flow generated by the drag force at the breakwater shoulder and open inlet. In addition, scour at the breakwater shoulder was inhibited by collecting the sand escaping offshore. Simultaneously, scour at the open inlet was also mitigated. The application of the hybrid method compensated for the problems caused by local scour and erosion in the submerged breakwater, thereby leading to the improvement of its function. Therefore, the hybrid method proposed in this paper was determined to be applicable not only for submerged breakwaters, but also for various structures for controlling coastal erosion.

Analysis of the progression of forest fires is critical in understanding fire regimes and managing the risk of active fires. Major fire events in Korea mostly occur in the eastern mountainous areas (Gangwon Province), where the wind and moisture conditions are prone to fire in the late winter season. Despite the significance of the fire events in the area both in terms of frequency and severity, their spatial progression characteristics and their dependency on forest types have not been sufficiently analyzed so far, particularly with satellite data. This study first derived the severity map for the Uljin fire which occurred in March 2022, using a series of satellite images acquired over the fire period with very high frequency (every 5 days), and analyzed the characteristics of spatio-temporal progression in terms of forest types. The analysis revealed that the core fire area expanded very rapidly in the first few days, followed by an intensification phase that elevated severity in the active areas with marginal expansion in the peripheral areas. The analysis of the progression showed that the fire did not expand selectively by the forest type, despite the clear difference in their severity levels in the burned areas, where coniferous forest exhibited 3 times higher severity than deciduous forest.

Kim, W.; Kim, S.H.; Baek, S.-I.; Kim, H., and Oh, J., 2021. A preliminary study on benthic mapping of Uljin coast based on airborne hyperspectral imagery towards the whitening detection. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 464–468. Coconut Creek (Florida), ISSN 0749-0208. This paper performed a preliminary investigation on the benthic identification methodology that is based on a semi-analytical optical model as a mean for detecting the whitening in the subtidal zone near Uljin, South Korea. Airborne hyperspectral images were acquired using a CASI-1500 sensor for the study area, and the preprocessing including radiometric, geometric, and atmospheric correction were applied to obtain subsurface remote sensing reflectance that is the input to the semi-analytical inversion method. Although the measured bottom reflectance was not available for the area, the experiment conducted with the typical substrate reflectance revealed the spatial distribution of bottom substrates in the area, with an implication to the whitening progress. It is concluded that a closure test with field-measured water quality variables and the collection of bottom substrate reflectance are warranted for more accurate substrate fraction estimates and the whitening detection.

Red tide poses significant ecological and economic threats to marine ecosystems, coastal communities, and the aquaculture industry, which requires prompt synoptic observation of its spatial distribution for rapid response. Despite progress in remote sensing techniques for detecting various types of algal blooms, a thorough quantification approach specifically tailored to red tide has not been fully explored. In particular, combination of a multispectral camera and a manned aircraft platform has not been addressed yet despite their potential for adaptability and applicability. This study introduces a novel quantitative methodology for the RedEdge-MX multispectral camera specifically for red tide quantification. The proposed framework presents processes for data preprocessing including calibration and atmospheric correction (AC), and radiance-based quantification algorithms. Validation conducted with in-situ measurements from extensive field campaigns showed that the proposed approach produced variance approximately 30~45% and a bias of less than 5% relative to concurrent field data.

Coastal resilience has received significant attention for managing beach erosion issues. We introduced flexible artificial coral reef (ACR) structures to diminish coastal erosion, but planar installation effects should be considered to evaluate the feasibility of coastline maintenance. In this study, we conducted a three-dimensional large-scale experiment to investigate the characteristics of planar installation of ACR, focusing on the wave mitigation performance, wave profile deformation with delay, nearshore current movement, deposition and erosion trends, and beach profile variation. We found that the ACR diminished the wave height by ~50% and the current intensity by ~60% compared with that of a conventional submerged breakwater made of dolos units. Using the dispersion velocity of the dye in a tracer experiment, the dispersion time of the ACR was approximately 1.67-times longer than that of the dolos and the current velocity was reduced, revealing that ACR significantly reduced structural erosion. With dolos, severe erosion of >10 cm occurred behind the structure, whereas there was only slight erosion with the ACR. Moreover, in a vertical beach-profile analysis, the ACR exhibited greater shoreline accretion than that of dolos. These results indicate the potential of ACR in improving coastal resilience.

Titanium dioxide (TiO₂) is a photocatalyst that can be used to remove nitrogen oxide (NO_x). When applied to cementitious materials, it reacts with photons in sunlight or artificially generated light to reduce the concentration of particulate matter in the atmosphere. The concentration of TiO₂ applied to the cementitious surface is difficult to quantify in a non-destructive manner after its application; however, knowledge of this residual amount is important for inspection and the evaluation of life expectancy. This study proposes a remote sensing technique that can estimate the concentration of TiO₂ in the cementitious surface using a hyperspectral sensor. In the experiment, cement cores of varying TiO₂ concentration and carbon contents were prepared and the surfaces were observed by TriOS RAMSES, a directional hyperspectral sensor. Machine-learning-based algorithms were then trained to estimate the TiO₂ concentration under varying base material conditions. The results revealed that the best-performing algorithms produced TiO₂ concentration estimates with a ~6% RMSE and a correlation close to 0.8. This study presents a robust machine learning model to estimate TiO₂ and activated carbon concentration with high accuracy, which can be applied to abrasion monitoring of TiO₂ and activated carbon in concrete structures.