• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.30-39
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• 2023

Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.80-92
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• 2007

Forest fire is the dominant large-scale disturbance mechanism in the Korean temperate forest, and it strongly influences forest structure and function. Moreover burn severity incorporates both short- and long-term post-fire effects on the local and regional environment. Burn severity is defined by the degree to which an ecosystem has changed owing to the fire. Vegetation rehabilitation may specifically vary according to burn severity after fire. To understand burn severity and process of vegetation rehabilitation at the damaged area after large-fire is required a lot of man powers and budgets. However the analysis of burn severity in the forest area using satellite imagery can acquire rapidly information and more objective results remotely in the large-fire area. Space and airbone sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. For classifying fire damaged area and analyzing burn severity of Samcheok fire area occurred in 2000, Cheongyang fire in 2002, and Yangyang fire in 2005 we utilized Normalized Burn Ratio(NBR) technique. The NBR is temporally differenced between pre- and post-fire datasets to determine the extent and degree of change detected from burning. In this paper we use pre- and post-fire imagery from the Landsat TM and ETM+ imagery to compute the NBR and evaluate large-scale patterns of burn severity at 30m spatial resolution. 65% in the Samcheok fire area, 91% in the Cheongyang fire area and 65% in the Yangyang fire area were corresponded to burn severity class above 'High'. Therefore the use of a remotely sensed Differenced Normalized Burn Ratio(${\Delta}NBR$) by RS and GIS allows for the burn severity to be quantified spatially by mapping damaged domain and burn severity across large-fire area.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.2
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• pp.11-21
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• 2000

Tunnelling has been created as a great extent in view of less land space available because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities. In tunnelling, it is often faced that measures are obliged to be taken without confirmation for such abnormality as diverged movement of surrounding rock mass, growing crack of shotcrete and yielding of rockbolts. In this case, it is usually said that the judgments of experienced engineers for the selection of measure are importance and allowed us to get over the situations in many construction sites. But decrease of such experienced engineers need us to develop the new system to assist the selection of measures for the abnormality without any experiences of similar tunnelling sites. In this study, After a lot of tunnelling reinforcement methods were surveyed and the detail application were studied, an expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The expert system developed in this study have two main parts named pre-module and post-module. Pre-module decides tunnel information imput items based on the tunnel face mapping information which can be easily obtained in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• Investigative Magnetic Resonance Imaging
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• v.6 no.2
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• pp.120-128
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• 2002

Purpose : To demonstrate that the relaxographic method provides additional information such as the distribution of relaxation times and water content which are poentially applicable to clinical medicine. Materials and Methods : First, the computer simulation was performed with the generated relaxation data to verify the accuracy and reliabilility of the relaxographic method (CONTINI). Secondly, in or der to see how well the CONTIN quantifies and resolves the two different ${T_1}$ environments, we calculated the oil to water peak area ratios and identified peak positions of ${T_1}-distribution$ curve of the phantom solutions, which consist of four centrifugal tubes (10 ml) filled with the compounds of 0, 10, 20, 30% of corn oil and distilled water, using CONTIN. Finally, inversion recovery MR images for a volunteer are acquired for each TI ranged from 40 to 1160 msec with TR/TE=2200/20 msec. From the 3 different ROIs (GM, WM, CSF), CONTIN analysis was performed to obtain the ${T_1}$-distribution curves, which gave peak positions and peak area of each ROI location. Results : The simulation result shows that the errors of peak positions were less in the higher peak (centered ${T_1}=600$ msec) than in the lower peak (centered ${T_1}=150$ msec) for all SNR but the errors of peak areas were larger in the higher peak than in the lower peak. The CONTIN analysis of the measured relaxation data of phantoms revealed two peaks between 20 and 60 msec and between 500 and 700 msec. The analysis gives the peak area ratio as oil 10%: oil 20%: oil 30% = 1:1.3:1.9, which is different from the exact ratio, 1:2:3. For human brain, in ROI 3 (CSF), only one component of -distributions was observed whereas in ROI 1(GM) and in ROI 2 (WM) we observed two components of ${T_1}-distribution$. For the WM and CSF there was great agreement between the observed ${T_1}-relaxation$ times and the reported values. Conclusion : we demonstrated that the relaxographic method provided additional information such as the distribution of relaxation times and water content, which were not available in the routine relaxometry and ${T_1}/{T_2}$ mapping techniques. In addition, these additional information provided by relaxographic analysis may have clinical importance.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.867-878
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• 2017

Recent interest in geological heritage has been increased in that it can be used as a basic data onto predicting the global environmental change of its containing information about past global environment. In addition, due to the characteristics of the geological heritage, it is easy to damage and difficult to recover without continuous preservation and management. However, there are more damages occurring because of the sporadic spatial distribution and ambiguous management authority of geological heritage. Therefore, an integrated management system is needed by determining the spatial distribution of geological heritage preferentially. In this study, the detailed criteria for assessment of value from the preliminary studies were applied and the geological heritage grade distribution map was generated by using geospatial data in Seoul metropolitan area. For this purpose, the list of geological heritage sites in the Seoul metropolitan area, which is the study area, were complied through a literature review. The geospatial database was designed and constructed by applying the detailed criteria for assessment of value from the preliminary studies. After the construction of the spatial database, a grade map of the geological heritage was created. As a result of the geological heritage grade map in the Seoul metropolitan area, there were more than 35% of the geological heritage in northern Gyeonggi provinces such as Yeoncheon city (18.8%), Pocheon city (10.6%) and Paju city (6.3%). It is followed by 18.1% in Incheon and 8.1% in Ansan, which is approximately 26.2% in western Gyeonggi Province. The geological age of the geological heritage was the highest at in the fourth stage of the Cenozoic era of 16.9%. Through the results of this study, the geological heritage data of the Seoul metropolitan area were extracted from existing literature data and converted into spatial information. It enables comparing the geological features with the spatial distribution of geological heritage. In addition, a management system has been established based on spatial information of constantly building geological heritage data. This provides the integrated management system of the geological heritage to manage authority so that it can be used as a basis for the development of the geological park. Based on the results of this study, it is considered to be possible to systematically construct and utilize the geological heritage across the country.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.86-96
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• 2006

Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.21-36
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• 2019

Dead fuel moisture content is a key variable in fire danger rating as it affects fire ignition and behavior. This study evaluates simple regression models estimating the moisture content of standardized 10-h fuel stick (10-h FMC) at three sites with different characteristics(urban and outside/inside the forest). Equilibrium moisture content (EMC) was used as an independent variable, and in-situ measured 10-h FMC was used as a dependent variable and validation data. 10-h FMC spatial distribution maps were created for dates with the most frequent fire occurrence during 2013-2018. Also, 10-h FMC values of the dates were analyzed to investigate under which 10-h FMC condition forest fire is likely to occur. As the results, fitted equations could explain considerable part of the variance in 10-h FMC (62~78%). Compared to the validation data, the models performed well with R2 ranged from 0.53 to 0.68, root mean squared error (RMSE) ranged from 2.52% to 3.43%, and bias ranged from -0.41% to 1.10%. When the 10-h FMC model fitted for one site was applied to the other sites, $R^2$ was maintained as the same while RMSE and bias increased up to 5.13% and 3.68%, respectively. The major deficiency of the 10-h FMC model was that it poorly caught the difference in the drying process after rainfall between 10-h FMC and EMC. From the analysis of 10-h FMC during the dates fire occurred, more than 70% of the fires occurred under a 10-h FMC condition of less than 10.5%. Overall, the present study suggested a simple model estimating 10-h FMC with acceptable performance. Applying the 10-h FMC model to the automatic mountain weather observation system was successfully tested to produce a national-scale 10-h FMC spatial distribution map. This data will be fundamental information for forest fire research, and will support the policy maker.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.281-298
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• 2023

Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.61-74
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• 2016

The purpose of this paper is to analyze the relationship between the location of the epicenter of a medium-sized earthquake(magnitude 4.8) that occurred on January 20, 2007 in the Odaesan area with lineament features using a shaded relief map(1/25,000 scale) and satellite images from LANDSAT-8 and KOMPSAT-2. Previous studies have analyzed lineament features in tectonic settings primarily by examining two-dimensional satellite images and shaded relief maps. These methods, however, limit the application of the visual interpretation of relief features long considered as the major component of lineament extraction. To overcome some existing limitations of two-dimensional images, this study examined three-dimensional images, produced from a Digital Elevation Model and drainage network map, for lineament extraction. This approach reduces mapping errors introduced by visual interpretation. In addition, spline interpolation was conducted to produce density maps of lineament frequency, intersection, and length required to estimate the density of lineament at the epicenter of the earthquake. An algorithm was developed to compute the Value of the Relative Density(VRD) representing the relative density of lineament from the map. The VRD is the lineament density of each map grid divided by the maximum density value from the map. As such, it is a quantified value that indicates the concentration level of the lineament density across the area impacted by the earthquake. Using this algorithm, the VRD calculated at the earthquake epicenter using the lineament's frequency, intersection, and length density maps ranged from approximately 0.60(min) to 0.90(max). However, because there were differences in mapped images such as those for solar altitude and azimuth, the mean of VRD was used rather than those categorized by the images. The results show that the average frequency of VRD was approximately 0.85, which was 21% higher than the intersection and length of VRD, demonstrating the close relationship that exists between lineament and the epicenter. Therefore, it is concluded that the density map analysis described in this study, based on lineament extraction, is valid and can be used as a primary data analysis tool for earthquake research in the future.