Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been used for land use classification and water body identification. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed by Landsat 8 has improved, enabling better characterization of land cover and increased data size. Therefore, it is necessary to explore the most appropriate and practical water identification methods that take advantage of the improved image quality and use the fewest inputs based on the original OLI bands. The objective of the study is to explore the potential of a J48 decision tree (JDT) in identifying water bodies using reflectance bands from Landsat 8 OLI imagery. J48 is an open-source decision tree. The test site for the study is in the Northern Han River Basin, which is located in Gangwon province, Korea. Training data with individual bands were used to develop the JDT model and later applied to the whole study area. The performance of the model was statistically analysed using the kappa statistic and area under the curve (AUC). The results were compared with five other known water identification methods using a confusion matrix and related statistics. Almost all the methods showed high accuracy, and the JDT was successfully applied to the OLI image using only four bands, where the new additional deep blue band of OLI was found to have the third highest information gain. Thus, the JDT can be a good method for water body identification based on images with improved resolution and increased size.
His research interests are in geodesy, surveying, geospatial information, and natural hazard analysis.
GNSS signal multipath occurs when the GNSS signal re ects o objects in the antenna environment and arrives at the antenna via multiple paths. A bridge environment is one that is prone to multipath with the bridge structure, as well as passing vehicles providing static and dynamic sources of multipath. In this paper, the Wavelet Transform (WT) is applied to bridge data collected on the Machang cable stayed bridge in Korea. The WT algorithm was applied to the GNSS derived bridge de ection data at the mid-span. Up to 41% improvement in RMS was observed after wavelet shrinkage de-noising was applied. Application of this algorithm to the torsion data showed signi cant improvement with the residual average and RMS decreased by 40% and 45% respectively. This method enabled the generation of more accurate information for bridge health monitoring systems in terms of the analysis of frequency, mode shape and three dimensional de ections.
There are no quantitative criteria for the location, size, etc. of shelter during floods. An empirical study was conducted on the location distribution of the shelters considering their accessibility. In this study, a safety zone that can be immediately evacuated using a pedestrian-level network was identified for each shelter. For the area under study, GIS network analysis was used to divide the area to be evacuated for each shelter and to generate a base map so that the most accessible shelter can easily be identified. We found that it is possible to identify a suitable shelter and evacuation route using pedestrian networks. In an emergency, it should be possible to get to the evacuation shelter as soon as possible, to avoid the high risks due to flooding. We conclude that, flooding maps can be effective for evacuation.
Since the 1970s, Korea has achieved exponential economic growth over a short period of time, with a huge amount of infrastructure built. However, 30 years on, this infrastructure is now deteriorating at a rapid pace due to extensive use and climatic factors, raising safety issues in recent years. The current task force faces limitations in monitoring and maintenance due to various reasons: Insufficient budget, increasing number of infrastructure facilities requiring maintenance, shortage of manpower, and a rapidly increasing number of aging infrastructure facilities. To overcome these limitations, a new approach is required that is different from the manual inspection methods under the existing rules and regulations. In this context, this study aimed to explore the efficiency of bridge inspection for cracks by an Unmanned Aerial Vehicle (UAV) that could observe inaccessible areas, could be conveniently and easily controlled, and could offer high economic benefits. A case study of UAV-based crack detection for Wonjudaegyo Bridge, Korea was performed. The results show more effective detection of cracks in the structure than traditional methods.
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