• Asian-Australasian Journal of Animal Sciences
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• v.32 no.8
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• pp.1172-1185
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• 2019

Objective: Meat quality attributes in postmortem muscle tissues depend on skeletal muscle metabolites. The objective of this study was to determine the key metabolic compounds and pathways that are associated with postmortem aging and beef quality in Japanese Black cattle (JB; a Japanese Wagyu breed with highly marbled beef). Methods: Lean portions of Longissimus thoracis (LT: loin) muscle in 3 JB steers were collected at 0, 1, and 14 days after slaughter. The metabolomic profiles of the samples were analyzed by capillary electrophoresis time-of-flight mass spectrometry, followed by statistical and multivariate analyses with bioinformatics resources. Results: Among the total 171 annotated compounds, the contents of gluconic acid, gluconolactone, spermidine, and the nutritionally vital substances (choline, thiamine, and nicotinamide) were elevated through the course of postmortem aging. The contents of glycolytic compounds increased along with the generation of lactic acid as the beef aging progressed. Moreover, the contents of several dipeptides and 16 amino acids, including glutamate and aromatic and branched-chain amino acids, were elevated over time, suggesting postmortem protein degradation in the muscle. Adenosine triphosphate degradation also progressed, resulting in the generation of inosine, xanthine, and hypoxanthine via the temporal increase in inosine 5'-monophosphate. Cysteine-glutathione disulfide, thiamine, and choline increased over time during the postmortem muscle aging. In the Kyoto encyclopedia of genes and genomes database, a bioinformatics resource, the postmortem metabolomic changes in LT muscle were characterized as pathways mainly related to protein digestion, glycolysis, citric acid cycle, pyruvate metabolism, pentose phosphate metabolism, nicotinamide metabolism, glycerophospholipid metabolism, purine metabolism, and glutathione metabolism. Conclusion: The compounds accumulating in aged beef were shown to be nutritionally vital substances and flavor components, as well as potential useful biomarkers of aging. The present metabolomic data during postmortem aging contribute to further understanding of the beef quality of JB and other breeds.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2013.11a
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• pp.30-31
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• 2013

Land use and land cover change (LULCC) due to human activities directly affects natural systems and contributes to changes in carbon exchange and climate through a range of feedbacks. How land use and land cover changes affect carbon exchanges can be assessed using multiyear measurement data from micrometeorological flux towers. The objective of the research is to assess the impact of land use and land cover change on carbon exchange in a heterogeneous cropland area. The heterogeneous cropland area in Haenam, South Korea is also subjected to a land conversion due to rural development. Therefore, the impact of the change in land utilization in this area on carbon exchange should be assessed to monitor the cycle of energy, water, and carbon dioxide between this key agricultural ecosystem and the atmosphere. We are currently conducting the research based on 10 years flux measurement data from Haenam Koflux site and examining the LULCC patterns in the same temporal scale to evaluate whether the LULCC in the surrounding site and the resulting heterogeneity (or diversity) have a significant impact on carbon exchange. Haenam cropland is located near the southwestern coast of the Korean Peninsula with land cover types consisting of scattered rice paddies and various croplands (seasonally cultivated crops). The LULCC will be identified and quantified using remote sensing satellite data and then analyzing the relationships between LULCC and flux footprint of $CO_2$ from tower flux measurement. We plan to calculate annual flux footprint climatology map from 2003 to 2012 from the 10 years flux observation database. Eventually, these results will be used to quantify how the system's effective performance and reserve capacity contribute to moving the system towards more sustainable configuration. Broader significance of this research is to understand the co-evolution of the Haenam agricultural ecosystem and its societal counterpart which are assumed to be self-organizing hierarchical open systems.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.321-327
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• 2017

China is experiencing the urbanization at an unprecedented speed and scale in human history. The continuing growth of China's big cities, both in city land and population, has already led to great challenges in China's urban planning and construction activities, such as the continuous increase of construction and demolition (C&D) waste. Therefore, how to characterize cities' construction activities, particularly dynamically quantify the flows of building materials and construction debris, has become a pressing problem to alleviate the current shortage of resources and realize urban sustainable development. Accordingly, this study is designed to employ 4D-GIS (four dimensions-Geographic Information System) and Internet Plus to offer new approach for accurate but dynamic C&D waste management. The present study established a spatio-temporal pattern and material metabolism evolution model to characterize the geo-distribution of C&D waste by combing material flow analysis (MFA) and 4D-GIS. In addition, this study developed a mobile application (APP) for C&D waste trading and information management, which could be more effective for stakeholders to obtain useful information. Moreover, a cloud database was built in the APP to disclose the flows of C&D waste by the monitoring information from vehicles at regional level. To summarize, these findings could provide basic data and management methods for the supply and reverse supply of building materials. Meanwhile, the methodologies are practical to C&D waste management and beyond.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.1
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• pp.21-28
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• 2009

Detailed information on soil characteristics is of great importance for the use and conservation of soil resources that are essential for human welfare and ecosystem sustainability. This paper introduces soil inventory of Korea focusing on national soil database establishment, information systems, use, and future direction for natural resources management. Different scales of soil maps surveyed and soil test data collected by RDA (Rural Development Administration) were computerized to construct digital soil maps and database. Soil chemical properties and heavy metal concentrations in agricultural soils including vulnerable agricultural soils were investigated regularly at fixed sampling points. Internet-based information systems for soil and agro-environmental resources were developed based on 'National Soil Survey Projects' for managing soil resources and for providing soil information to the public, and 'Agroenvironmental Change Monitoring Project' to monitor spatial and temporal changes of agricultural environment will be opened soon. Soils data has a great potential of further application in estimation of soil carbon storage, water capacity, and soil loss. Digital mapping of soil and environment using state-of-the-art and emerging technologies with a pedometrics concept will lead to future direction.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.632-645
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• 2021

Satellite sea surface temperature (SST) composites provide important data for numerical forecasting models and for research on global warming and climate change. In this study, six types of representative SST composite database were collected from 2007 to 2018 and the characteristics of spatial structures of SSTs were analyzed in seas around the Korean Peninsula. The SST composite data were compared with time series of in-situ measurements from ocean meteorological buoys of the Korea Meteorological Administration by analyzing the maximum value of the errors and its occurrence time at each buoy station. High differences between the SST data and in-situ measurements were detected in the western coastal stations, in particular Deokjeokdo and Chilbaldo, with a dominant annual or semi-annual cycle. In Pohang buoy, a high SST difference was observed in the summer of 2013, when cold water appeared in the surface layer due to strong upwelling. As a result of spectrum analysis of the time series SST data, daily satellite SSTs showed similar spectral energy from in-situ measurements at periods longer than one month approximately. On the other hand, the difference of spectral energy between the satellite SSTs and in-situ temperature tended to magnify as the temporal frequency increased. This suggests a possibility that satellite SST composite data may not adequately express the temporal variability of SST in the near-coastal area. The fronts from satellite SST images revealed the differences among the SST databases in terms of spatial structure and magnitude of the oceanic fronts. The spatial scale expressed by the SST composite field was investigated through spatial spectral analysis. As a result, the high-resolution SST composite images expressed the spatial structures of mesoscale ocean phenomena better than other low-resolution SST images. Therefore, in order to express the actual mesoscale ocean phenomenon in more detail, it is necessary to develop more advanced techniques for producing the SST composites.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.128-136
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• 2011

To monitor and predict the change of coastal environment according to the construction of Saemangeum sea dyke and the development of land reclamation, we have done real-time and periodic ocean observation and numerical simulation since 2002. Saemangeum coastal environmental data can be largely classified to marine meteorology, ocean physics and circulation, water quality, marine geology and marine ecosystem and each part of data has been generated continuously and accumulated over about 10 years. The collected coastal environmental data are huge amounts of heterogeneous dataset and have some characteristics of multi-dimension, multivariate and spatio-temporal distribution. Thus the implementation of information system possible to data collection, processing, management and service is necessary. In this study, through the implementation of Saemangeum coastal environmental information system using geographic information system, it enables the integral data collection and management and the data querying and analysis of enormous and high-complexity data through the design of intuitive and effective web user interface and scientific data visualization using statistical graphs and thematic cartography. Furthermore, through the quantitative analysis of trend changed over long-term by the geo-spatial analysis with geo- processing, it's being used as a tool for provide a scientific basis for sustainable development and decision support in Saemangeum coast. Moreover, for the effective web-based information service, multi-level map cache, multi-layer architecture and geospatial database were implemented together.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.21-28
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• 2016

Numeric weather prediction is important to prevent meteorological disasters such as heavy rain, heat wave, and cold wave. The Korea meteorological administration provides a realtime special weather report and the rural development administration demonstrates information about 2-day warning of agricultural disasters for farms in a few regions. To improve the early warning systems for meteorological hazards, a nation-wide high-resolution dataset for weather prediction should be combined with web-based GIS. This study aims to develop a web service prototype for early warning of meteorological hazards, which integrates web GIS technologies with a weather prediction database in a temporal resolution of 1 hour and a spatial resolution of 1 km. The spatially and temporally high-resolution dataset for meteorological hazards produced by downscaling of GME was serviced via a web GIS. In addition to the information about current status of meteorological hazards, the proposed system provides the hourly dong-level forecasting of meteorologic hazards for upcoming seven days, such as heavy rain, heat wave, and cold wave. This system can be utilized as an operational information service for municipal governments in Korea by achieving the future work to improve the accuracy of numeric weather predictions and the preprocessing time for raster and vector dataset.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.119-132
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• 2009

Owing to the GIS technology, a vast volume of spatial data has been accumulated, thereby incurring the necessity of spatial data mining techniques. In this paper, we propose a new spatial data mining system named SD-Miner. SD-Miner consists of three parts: a graphical user interface for inputs and outputs, a data mining module that processes spatial mining functionalities, a data storage model that stores and manages spatial as well as non-spatial data by using a DBMS. In particular, the data mining module provides major data mining functionalities such as spatial clustering, spatial classification, spatial characterization, and spatio-temporal association rule mining. SD-Miner has own characteristics: (1) It supports users to perform non-spatial data mining functionalities as well as spatial data mining functionalities intuitively and effectively; (2) It provides users with spatial data mining functions as a form of libraries, thereby making applications conveniently use those functions. (3) It inputs parameters for mining as a form of database tables to increase flexibility. In order to verify the practicality of our SD-Miner developed, we present meaningful results obtained by performing spatial data mining with real-world spatial data.

• Journal of the Korean earth science society
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• v.21 no.1
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• pp.51-58
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• 2000

This study was performed to accumulate database for natural sulfur emissions in the Yellow Sea region of Korea. The atmospheric concentrations of dimethylsulfide(DMS) were measured during two intensive field experiments (April and September 1999) from Duk-Juk Island located in the Yellow Sea. Ship-measurement of DMS was made additionally between Chungdo(China) and Inchun(Korea) across the Yellow Sea during June 1999. The mean(and ISD) of DMS concentrations in Duk-Juk Island during two field campaigns was $24.0{\pm}40.5$(n=40, April) and $61.1{\pm}37.9$ pptv(n=35, September), respectively. The atmospheric DMS measured from ship experiments was generally low and close to the background concentrations in the open sea area. The temporal distributions of DMS concentration were complicated in some sense but comparable to those of ambient meteorological parameters. On the basis of our measurements of atmospheric DMS(and evidence found from previous studies), the sea-to-air flux of DMS in the Yellow Sea is estimated to be about 4Gg S/yr. This amount of natural S emissions is relatively lower than the estimates derived for Cheju Island. Therefore, additional experiments may be desperate to derive more reliable figures for natural sulfur emissions in the Yellow Sea region.