Earticle

This study aimed to analyze long-term changes in soil CO2 flux (Rsoil, soil respiration) using a chronosequence approach in forests affected by forest fires on the east coast of Korea. Rsoil was measured seasonally along with soil temperature and moisture to assess its response to environmental variation. Additionally, soil physicochemical properties and fine root (≤2 mm) biomass were analyzed to investigate their correlations with Rsoil. Total carbon (TC) and nitrogen (TN) concentration in soil, and fine root biomass were initially low, peaked during the mid-recovery stage, and then tended to stabilize, whereas soil permeability, sand, silt, and clay contents exhibited distinct patterns. Rsoil increased exponentially with soil temperature, showing higher coefficient of determination (R2) in late recovery stage (0.67) and unburned stands (0.72) than in early stage (0.30). Temperature sensitivity (Q10) of Rsoil showed no significant differences among recovery stages, however the Q10 values exhibited relatively low in early stage compared to other stages. The relationship between soil moisture and Rsoil was weak overall, except in the unburned (R2=0.27, p＜0.01). Rsoil at 20°C (R20, μmol CO2 m-2 s-1) increased with the duration of recovery, with values of 2.38±0.34, 4.11±0.25, 3.14±0.13, and 4.23±0.38 in early-, mid-, late stages, and unburned, respectively. R20 was positively correlated with soil permeability, TC, TN, and fine root biomass (p＜0.05). These findings highlight the importance of Rsoil as an indicator of soil recovery, contribute to the assessment of post-fire soils and the understanding of soil carbon dynamics.

이 글은 한국 언어문화 교육의 내용과 실제는 주로 한국 사회・문화 교육의 차원에서 이루어지지만, 다른 한국어교육의 영역에서도 유용 하다는 점을 전제로 하였다. 즉 한국어교육에서 언어와 문화는 뗄 수 없는 관계라는 점을 전제로 하여, 한국어교육의 맥락에서 이루어지는 언어교육, 문화교육의 통합 교육적 현상을 한국 언어문화 교육이라는 개념으로 포괄하고자 하였다. 그리고 이러한 논의를 통해서 한국 언어문화 교육의 질적 향상 방안을 살펴보는 것을 주된 목적으로 하였다. 이러한 목적을 위해서 세부적으 로는 한국 언어문화 교육 내용의 구체화, 한국 언어문화 교육 방법의 다양화, 한국 언어문화 교육 연구의 심화라는 문제에 초점을 맞추어 그 해결 방안을 모색하였다. 특히 언어문화 교육 방법에서는 필자의 전공인 한국문학 작품을 활용하는 교육적 효용성에 중점을 두고 구체 적인 교수-학습 방법을 제안하였다.

Journal of the International Network for Korean Language and Culture 12-1, 1-22. This study assumes that contents and practices of languagecultural education in Korean language education are useful not only for social-cultural education of Korean language education but also for other areas of Korean language education. As the relation between language and culture is inseparable in Korean language education, this study intends to integrated language education and culture education that are conducted in the context of Korean language education through the concept of language and culture education. The main purpose of this study is to find a qualitative improvement plan for language and culture education in Korean language education. In order to the purpose, this study focuses on actualizing educational contents, diversifying educational methods and intensifying educational researches of language and culture education in Korean language education. Particularly, focusing on educational usefulness, this study offers education methods that make use of Korean literatures that is my major study.(Seoul National University)

The recent increase in the frequency and severity of forest fires driven by climate change have raised concerns about secondary disasters, such as soil erosion and landslides, in forest-fire-affected areas. Effective restoration, including soil protection and vegetation recovery, is essential for mitigating these risks. In South Korea, most studies have mainly focused on localized changes or the initial stages of post-fire recovery and remain limited in both temporal and spatial scopes. We conducted a bibliometric analysis to examine and compare research trends over the past 45 years regarding post-fire restoration and the application of nature-based solutions (NbS) to fire-affected areas. The results indicated a marked increase in international publications on post-fire restoration since the 2000s, with most studies originating from the United States and European countries where forest fires are particularly frequent. In South Korea, research on post-fire restoration has increased significantly since 2010. However, no studies on NbS applications have been published to date. Our findings highlight that despite ongoing restoration efforts in South Korea, a comprehensive evaluation of restoration techniques is still lacking. To achieve sustainable restoration and management of forest-fire-affected areas, it is essential to systematically monitor changes in soil and hydrological conditions. Based on these data, diverse restoration techniques, including NbS, should be implemented, and their effectiveness should be quantitatively assessed.

In recent decades, the increasing frequency and severity of wildfires driven by climate change and other factors have led to a significant expansion of research on wildfire spread. This study presents a bibliometric analysis of wildfire spread research from 1982 to 2024. We compiled a dataset of scholarly publications and applied cluster analysis to identify major research topics. Using silhouette scores, we determined an optimal cluster number of approximately 20, and visualized the topic clusters with a two-dimensional embedding. We also analyzed publication trends over time, citation patterns, and keyword co-occurrence networks to understand the evolution and impact of each research topic. The results reveal a dramatic growth in wildfire spread studies over the past decade. We identified several distinct research clusters, including climate change impacts, fire behavior modeling, remote sensing applications, wildfire management strategies, and ecological effects of fires, among others. Some topics, such as climate-related wildfire research and remote sensing, have grown especially rapidly in recent years. Citation analysis indicates that certain longstanding research areas carry high influence, while emerging topics are gaining attention. The keyword network highlights interdisciplinary connections linking climate, ecology, and technology in wildfire research. This comprehensive overview of the wildfire spread research landscape offers insights into past developments and emerging directions, which can inform future research and policymaking in wildfire management.

This research aimed to assess the possibility of detecting forest degradation using time-series satellite imagery and three different deep learning-based change detection techniques. The dataset used for the deep learning models was composed of two sets, one based on surface reflectance (SR) spectral information from satellite imagery, combined with Texture Information (GLCM; Gray-Level Co-occurrence Matrix) and terrain information. The deep learning models employed for land cover change detection included image differencing using the Unet semantic segmentation model, multi-encoder Unet model, and multi-encoder Unet++ model. The study found that there was no significant difference in accuracy between the deep learning models for forest degradation detection. Both training and validation accuracies were approximately 89% and 92%, respectively. Among the three deep learning models, the multi-encoder Unet model showed the most efficient analysis time and comparable accuracy. Moreover, models that incorporated both texture and gradient information in addition to spectral information were found to have a higher classification accuracy compared to models that used only spectral information. Overall, the accuracy of forest degradation extraction was outstanding, achieving 98%.