• Tunnel and Underground Space
• /
• v.33 no.4
• /
• pp.281-298
• /
• 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 Intelligence and Information Systems
• /
• v.23 no.3
• /
• pp.95-118
• /
• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.3
• /
• pp.192-207
• /
• 2020

Profitability of upland crops is better than paddy crops and proportion of upland is increasing. However, there is a lack of infrastructures for upland irrigation. The object of this study were to develop water supply scenarios using individual and collective agricultural wells to evaluate economic feasibility to consider geographical analysis of upland farms and water supply facilities. Cheongyang, Dangjin, Yesan, and Goesan were selected as study areas where four different crops of red pepper, chinese cabbage, apple, and bean, respectively, were mainly produced in Chungcheong province. As a result, B/C ratio was estimated as 1.49, 1.36, 1.90, and 0.71 in using individual wells scenario, and 1.45, 1.20, 1.91, and 0.65 in using collective wells scenario for red pepper, chinese cabbage, apple, and bean. It turned out that change of price effected on economic feasibility a lot for crops with low production income. As a result of evaluating economic feasibility by number of plots for developing collective well, there was no effect of economy of scale for red pepper and chinese cabbage. In case of collectivizating more than 20 upland plots, effect of economy of scale appeared for apple and bean. In conclusion, development of water using high value crops including red pepper and apple, and effect of collective well requires additory analysis of .spatial distribution of farms.

• Horticultural Science & Technology
• /
• v.33 no.2
• /
• pp.166-176
• /
• 2015

Research was initiated to investigate root growth characteristics of major cool-season grasses (CSG) and to collect basic information useful for sports turf design, construction and maintenance. Several turfgrasses were evaluated in the USGA (United States Golf Association) soil system. Turfgrass entries were comprised 3 blends and 3 mixtures of Kentucky bluegrass (KB, Poa pratensis L.), perennial ryegrass (PR, Lolium perenne L.), and tall fescue (TF, Festuca arundinacea Schreb.). Significant differences were found in root growth, rooting potential and rooting development. These characteristics increased with time after seeding, but varied with establishment stages. In early stage, root length was highest with PR, intermediate with TF and lowest with KB. Evaluation in a middle stage indicated that root growth was similar to early-stage evaluation, but decreased by 13 to 31% compared with early-stage values. Root growth of late stage increased by 34 to 85% over middle-stage root growth. Overall, thhere was not much difference in root length among treatments, with all except Mixture I reaching 22cm in root length. Rooting potential ranking was variable with establishment stage, being PR > KB > TF in early stage, PR > TF > KB in middle stage and TF > PR > KB in late stage. At the end of the study, TF was rated best for rooting development, followed by PR and finally KB. Our results showed that TF was the best species in regard to overall rooting characteristics. TF exhibited excellent rooting development with time after establishment. Bunch-type PR showed fast root growth in the early stage, but rooting quality characteristics decreased with time, especially for rooting development. By contrast, rhizomatous-type KB was poor in early-stage root growth, but rooting characteristics improved with time after establishment. These variations in rooting characteristics among CSGs were considered to arise from differences in establishment vigor, growth habit and genetic characteristics. Information on root growth, rooting potential and rooting development by establishment stages will be useful for sports turf design, construction and maintenance.

• Journal of Environmental Policy
• /
• v.9 no.2
• /
• pp.157-184
• /
• 2010

Global climate change is destroying the water circulation balance by changing rates of precipitation, recharge and discharge, and evapotranspiration. The Intergovernmental Panel on Climate Change (IPCC 2007) makes "changes in rainfall pattern due to climate system changes and consequent shortage of available water resource" a high priority as the weakest part among the effects of human environment caused by future climate changes. Groundwater, which occupies a considerable portion of the world's water resources, is related to climate change via surface water such as rivers, lakes, and marshes, and "direct" interactions, being indirectly affected through recharge. Therefore, in order to quantify the effects of climate change on groundwater resources, it is necessary to not only predict the main variables of climate change but to also accurately predict the underground rainfall recharge quantity. In this paper, the authors selected a relevant climate change scenario, In this context, the authors selected A1B from the Special Report on Emission Scenario (SRES) which is distributed at Korea Meteorological Administration. By using data on temperature, rainfall, soil, and land use, the groundwater recharge rate for the research area was estimated by period and embodied as geographic information system (GIS). In order to calculate the groundwater recharge quantity, Visual HELP3 was used as main model for groundwater recharge, and the physical properties of weather, temperature, and soil layers were used as main input data. General changes to water circulation due to climate change have already been predicted. In order to systematically solve problems associated with how the groundwater resource circulation system should be reflected in future policies pertaining to groundwater resources, it may be urgent to recalculate the groundwater recharge quantity and consequent quantity for using via prediction of climate change in Korea in the future and then reflection of the results. The space-time calculation of changes to the groundwater recharge quantity in the study area may serve as a foundation to present additional measures for the improved management of domestic groundwater resources.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.12
• /
• pp.51-57
• /
• 2019

In this paper, we analyzed the performance of IoT based smart wearable mine detection device. There are various mine detection methods currently used by the military. Still, in the general field, mine detection is performed by visual detection, probe detection, detector detection, and other detection methods. The detection method by the detector is using a GPR sensor on the detector, which is possible to detect metals, but it is difficult to identify non-metals. It is hard to distinguish whether the area where the detection was performed or not. Also, there is a problem that a lot of human resources and time are wasted, and if the user does not move the sensor at a constant speed or moves too fast, it is difficult to detect landmines accurately. Therefore, we studied the smart wearable mine detection device composed of human body antenna, main microprocessor, smart glasses, body-mounted LCD monitor, wireless data transmission, belt type power supply, black box camera, which is to improve the problem of the error of mine detection using unidirectional ultrasonic sensing signal. Based on the results of this study, we will conduct an experiment to confirm the possibility of detecting underground mines based on the Internet of Things (IoT). This paper consists of an introduction, experimental environment composition, simulation analysis, and conclusion. Introduction introduces the research contents such as mines, mine detectors, and research progress. It consists of large anti-personnel mine, M16A1 fragmented anti-mine, M15 and M19 antitank mines, plastic bottles similar to mines and aluminum cans. Simulation analysis is conducted by using MATLAB to analyze the mine detection device implementation performance, generating and transmitting IoT signals, and analyzing each received signal to verify the detection performance of landmines. Then we will measure the performance through the simulation of IoT-based mine detection algorithm so that we will prove the possibility of IoT-based detection landmine.

• Journal of the Korean association of regional geographers
• /
• v.3 no.1
• /
• pp.63-80
• /
• 1997

This study attempts to establish the criteria of site selection for establishing solid waste disposal facility, to determine optimal solid waste disposal sites with the criteria, and to examine the suitability of the selected sites. The Multi-Criteria Evaluation(MCE) module in Idrisi is used to determine optimal sites for solid waste disposal. The MCE combines the information from several criteria in interval and/or ratio scale to form a single index of evaluation without leveling down the data scale into ordinal scale. The summary of this study is as follows: First, the considerable criteria are selected through reviewing the literature and the availability of data: namely, percent of slope, fault lines, bedrock characteristics, major residential areas, reservoirs of water supply, rivers, inundated area, roads, and tourist resorts. Second, the criteria maps of nine factors have been developed. Each factor map is standardized and multiplies by its weight, and then the results are summed. After all of the factors have been incorporated, the resulting suitability map is multiplied by each of the constraint in turn to "zero out" unsuitable area. The unsuitable areas are discovered in urban district and its adjacencies, and mountain region as well as river, roads, resort area and their adjacency districts. Third, the potential sites for establishing waste disposal facilities are twenty five districts in Youngyang-gun. Five districts are located in Subi-myun Sinam-ri, nine districts in Chunggi-myun Haehwa-ri and Moojin-ri, and eleven districts in Sukbo-myun Posan-ri. The first highest score of suitability for waste disposal sites is shown at number eleven district in Chunggi-myun Moojin-ri and the second highest one is discovered at number twenty one district in Sukbo-myun Posan-ri that is followed by number nine district in Chunggi-myun Haehwa-ri, number seventeen and twenty three in Sukbo-myun Posan-ri, and number two in Subi-myun Sinam-ri. The first lowest score is found in number six district in Chunggi-myun Haehwa-ri, and the second lowest one is number five district in Subi-myun Sinam-ri. Finally, the Geographic Information System (GIS) helps to select optimal sites with more objectively and to minimize conflict in the determination of waste disposal sites. It is important to present several potential sites with objective criteria for establishing waste disposal facilities and to discover characteristics of each potential site as a result of that final sites of waste disposal are determined through considering thought of residents. This study has a limitation of criteria as a result of the restriction of availability of data such as underground water, soil texture and mineralogy, and thought of residents. To improve selection of optimal sites for a waste disposal facility, more wide rage of spatial and non-spatial data base should be constructed.

• Korean Journal of Environment and Ecology
• /
• v.33 no.3
• /
• pp.303-320
• /
• 2019

Plants interact with various biotic and abiotic environmental factors. It requires much information to understand the traits of a plant species. A shortage of information would restrict the assessment, especially in the evaluation of what kind of factors influence a plant species to face extinction. Polygonatum stenophyllum Maxim. is one of the northern plants of which Korea is the southern distribution edge. The Korean Ministry of Environment had designated it to be the endangered species until December 2015. Although it is comparatively widespread, and a large population has recently been reported, it is assessed to be vulnerable due to the low population genetic diversity. This study evaluated the current distribution of Polygonatum stenophyllum Maxim. We investigated the vegetational environment, population structures, phenology, soil environment, and self-incompatibility based on the results. Lastly, we evaluated the current threats observed in the habitats. The habitats tended to be located in the areas where the masses at the edge of the stream accumulated except for those that were located on slopes of some mountainous areas. Most of them showed a stable population structure and had re-established or recruited seedlings. Polygonatum stenophyllum Maxim. had the difference in time when the shoots appeared above the ground depending on the depth of the rhizome located in the underground. In particular, the seedlings and juveniles had their rhizome located shallow in the soil. Visits by pollinator insects and success in pollination were crucial factors for bearing of fruits by Polygonatum stenophyllum Maxim. The threats observed in the habitat of Polygonatum stenophyllum Maxim. included the expansion of cultivated land, construction of new buildings, and construction of river banks and roads. Despite such observed risk factors, it is not likely that there would be rapid population reduction or extinction because of its widespread distribution with the total population of more than 2.7 million individuals and the new populations established by the re-colonization.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.131-145
• /
• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Korean Journal of Remote Sensing
• /
• v.36 no.2_2
• /
• pp.351-363
• /
• 2020

It is well known that alluvial sediment located in coastal region has been easily affected by geohazard like ground subsidence, marine or meteorological disasters which threaten invaluable lives and properties. The subsidence is a sinking of the ground due to underground material movement that mostly related to soil compaction by water extraction. Thus, continuous monitoring is essential to protect possible damage from the ground subsidence in the coastal region. Radar interferometric application has been widely used to estimate surface displacement from phase information of synthetic aperture radar (SAR). Thanks to advanced SAR technique like the Small BAseline Subset (SBAS), a time-series of surface displacement could be successfully calculated with a large amount of SAR observations (>20). Because the ALOS-2 PALSAR-2 L-band observations maintain higher coherence compared with other shorter wavelength like X- or C-band, it has been regarded as one of the best resources for Earth science. However, the number of ALOS-2 PALSAR-2 observations might be not enough for the SBAS application due to its global monitoring observation scenario. Unfortunately, the number of the ALOS-2 PALSAR-2 Stripmap images in area of our interest, Busan which located in the Southeastern Korea, is only 11 which is insufficient to apply the SBAS time-series analysis. Although it is common that the radar interferometry utilizes multiple SAR images collected from same acquisition mode, it has been reported that the ALOS-2 PALSAR-2 Stripmap-ScanSAR interferometric application could be possible under specific acquisition mode. In case that we can apply the Stripmap-ScanSAR interferometry with the other 18 ScanSAR observations over Busan, an enhanced time-series surface displacement with better temporal resolution could be estimated. In this study, we evaluated feasibility of the ALOS-2 PALSAR-2 Stripmap-ScanSAR interferometric application using Gamma software considering differences of chirp bandwidth and pulse repetition frequency (PRF) between two acquisition modes. In addition, we analyzed the interferograms with respect to spectral shift of radar carrier frequency and common band filtering. Even though it shows similar level of coherence regardless of spectral shift in the radar carrier frequency, we found periodic spectral noises in azimuth direction and significant degradation of coherence in azimuth direction after common band filtering. Therefore, the characteristics of spectral bandwidth in the range and azimuth direction should be considered cautiously for the ALOS-2 PALSAR-2 Stripmap-ScanSAR interferometry.