낙상은 여러 가지 원인에 의해 넘어지거나 떨어지는 것을 의미한다. 낙상사고는 응급실 내원 손상 환자의 가장 큰 비율 을 차지하며, 2021년 낙상사고는 2011년 대비 5.8% 증가하였다. 특히 보행 중 낙상 사고는 주로 경사진 도로나 지면, 물 이나 눈, 또는 빙판으로 덮여 있는 도로에서 발생하고 있으며, 이는 보행자의 안전을 위협하고 있다. 개인적인 노력 외에 도 공중환경 개선이 필요하나, 이에 대한 연구는 부족한 실정이다. 따라서 본 연구에서는 소방청 추락낙상사고 오픈 API 를 활용하여 보행 중 낙상사고가 일어난 지역의 시·공간적 특성을 파악하고자 한다. 서울시 100x100 그리드별 보행자 낙 상사고 건수를 바탕으로 Moran’s I 분석을 수행하여 공간적 자기 상관성을 파악하였다. 보행자 낙상사고 다발지역이 분 포하는 양상을 파악하고, High-High(HH)로 구분된 상위 지역에 대하여 공간적 특징을 분석하였다. 연구결과는 보행자 도로 유지보수 및 야간 주의 표시 등의 예방책이 필요함을 시사하며, 보행자 안전 증진에 기여할 수 있을 것으로 기대된 다.

PURPOSES : To prevent an increasing number of drowsiness-related accidents, considering driver fatigue is necessary, which is the main cause of drowsiness accidents. The purpose of this study is to propose a methodology for selecting drowsiness hotspots using continuous driving time, a variable that quantifies driver fatigue. METHODS : An analysis was conducted by dividing driver fatigue, which changes according to time and space, into temporal and spatiotemporal scenarios. The analysis technique derived four evaluation indicators (precision, recall, accuracy, and F1 score) using a random forest classification model that is effective for processing large amounts of data. RESULTS : Both the temporal and spatiotemporal scenarios performed better in models that reflected the characteristics of road sections with changes in time and space. Comparing the two scenarios, it was found that the spatiotemporal scenario showed a difference in precision of approximately 10% compared with the temporal scenarios. In addition, [Model 2-2] of the spatiotemporal scenario showed the best predictive power by assessing the model’s accuracy via a comparison of (1-recall) and precision. This shows better performance in predicting drowsy accidents by considering changes in time and space together rather than constructing only temporal changes. CONCLUSIONS : To classify hotspots of drowsiness, spatiotemporal factors must be considered. However, it is possible to develop a methodology with better performance if data on individuals driving vehicles can be collected.

Headwater streams provide various microhabitats, resulting in high diversity of macroinvertebrate community. In this study, we compared the differences of communities between two adjacent headwater streams (Jangjeon stream (GRJ; GRJ1-GRJ5) and Haanmi stream (GRH; GRH1-GRH3)) in Jungwang and Gariwang mountains, Gangwon-do and evaluated the effects of habitat condition to the macroinvertebrates community composition. In order to characterize the macroinvertebrate communities and extract influential environmental factors, we applied to Cluster analysis (CA), Indicator species analysis and Non-metric multidimensional scaling (NMDS). Total 33,613 individuals in 3 phyla, 5 classes, 13 orders, 51 families, and 114 taxa (genera or species) were collected. Gammarus sp. was dominant at the upper stream of GRJ, whereas Chironomidae spp. was abundant at GRH and the downstream of GRJ. The CA classified samples into six clusters (1-6) reflecting spatial and temporal variation of benthic macroinvertebrate communities. Benthic macroinvertebrate community composition was significantly different between two adjacent streams. Sweltsa sp. 1, Psilotreta kisoensis, Rhyacophila shikotsuensis and Serratella setigera were identified as representative indicator species for clusters 1, 2, 3 and 5, respectively. Similar to CA results, NMDS revealed the spatial and temporal differences of benthic macroinvertebrate communities, indicating the difference of community composition as well as microhabitat condition. Forest composition, proportion of boulders (>256 mm), and water velocity were main factors affecting the macroinvertebrate community composition.