This study was conducted to provide basic data for crop monitoring by comparing and analyzing changes in reflectance and vegetation index by sensor of multi-spectral sensors mounted on unmanned aerial vehicles. For four types of unmanned aerial vehicle-mounted multispectral sensors, such as RedEdge-MX, S110 NIR, Sequioa, and P4M, on September 14 and September 15, 2020, aerial images were taken, once in the morning and in the afternoon, a total of 4 times, and reflectance and vegetation index were calculated and compared. In the case of reflectance, the time-series coefficient of variation of all sensors showed an average value of about 10% or more, indicating that there is a limit to its use. The coefficient of variation of the vegetation index by sensor for the crop test group showed an average value of 1.2 to 3.6% in the crop experimental sites with high vitality due to thick vegetation, showing variability within 5%. However, this was a higher value than the coefficient of variation on a clear day, and it is estimated that the weather conditions such as clouds were different in the morning and afternoon during the experiment period. It is thought that it is necessary to establish and implement a UAV flight plan. As a result of comparing the NDVI between the multi-spectral sensors of the unmanned aerial vehicle, in this experiment, it is thought that the RedEdeg-MX sensor can be used together without special correction of the NDVI value even if several sensors of the same type are used in a stable light environment. RedEdge-MX, P4M, and Sequioa sensors showed a linear relationship with each other, but supplementary experiments are needed to evaluate joint utilization through off-set correction between vegetation indices.
Records of architectural cultural properties, in case of accidents, show who are to blame, present what evidences are to establish the cause, and also are used for checking if there were any problem in policies and regulations in preserving and caring architectural cultural properties. These records are of great importance in their roles and are of essential use regardless of time and space. Considering its significance, In that architectural cultural properties requires setting clear goals and directions and as well, criteria, for management, we need methods of systematical control and consideration for its characteristics. This research started with the sense of purpose that managing architectural cultural properties are in need of systematic and concrete control, based on the perception that they need protecting and transmitting. The goal of this thesis is to work on the current archiving status of architectural cultural properties by monitoring patterns and processes in archival administration, to diagnose problems by looking into the records creation and management, and to present the improvement plan which would lead to the architectural cultural properties' more efficient management and better use in the future. The management of architectural cultural properties begins with registering and assigning. Cultural Heritage Administration is in charge of control, supervision, and budget and local governments deal with direct management. Accordingly, records are by the hands of each local governmental body. Currently, each cultural property has its management depending on every different working environment in each governmental body. Architectural cultural properties needs managing in one body through the synthetic and unified, concrete and systematic manual and guide for management. Archiving architectural cultural properties have need of unitive management through a professional system, considering the physical characteristics and history of archiving. Unified management system will enhance efficiency and actual use of architectural cultural property records if one governmental body undertakes uniting records through standardization and professional supervision, and data-based unified search engine would enhance efficiency and actual use. Therefore, I suggest that Archives for Architectural Cultural Properties should be established as a professional Archives and wholly responsible body for the purpose of systematically and unifiedly managing architectural cultural property records with professional personnel and facility and transmitting their historical, cultural, and academic value. In Korea, studies up to the present have mainly focused on managing architectural records and records of drawing while few efforts were made to directly deal with managing architectural cultural properties themselves. The focus of this thesis is to study the current status and establish problems of the management of architectural cultural properties in administrative process, and as a result, to propose to establish Archives for Architectural Cultural Properties as a professional archives.
Kim, Junhwan;Sang, Wangyu;Shin, Pyeong;Cho, Hyeounsuk;Seo, Myungchul
Korean Journal of Agricultural and Forest Meteorology
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v.20
no.4
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pp.277-283
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2018
The crop growth model has been widely used for climate change impact assessment. Crop growth model require genetic coefficients for simulating growth and yield. In order to determine the genetic coefficients, regional growth monitoring data or yield trial data of crops has been used to calibrate crop growth model. The aim of this study is to verify that yield trial data of corn is appropriate to calibrate genetic coefficients of CERES-MAIZE. Field experiment sites were Suwon, Jinju, Daegu and Changwon. The distance from the weather station to the experimental field were from 1.3km to 27km. Genetic coefficients calibrated by yield trial data showed good performance in silking day. The genetic coefficients associated with silking are determined only by temperature. In CERES-MAIZE model, precipitation or irrigation does not have a significant effect on phenology related genetic coefficients. Although the effective distance of the temperature could vary depending on the terrain, reliable genetic coefficients were obtained in this study even when a weather observation site was within a maximum of 27 km. Therefore, it is possible to estimate the genetic coefficients by yield trial data in study area. However, the yield-related genetic coefficients did not show good results. These results were caused by simulating the water stress without accurate information on irrigation or rainfall. The yield trial reports have not had accurate information on irrigation timing and volume. In order to obtain significant precipitation data, the distance between experimental field and weather station should be closer to that of the temperature measurement. However, the experimental fields in this study was not close enough to the weather station. Therefore, When determining the genetic coefficients of regional corn yield trial data, it may be appropriate to calibrate only genetic coefficients related to phenology.
Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.
With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.
Kim, Yongwon;Lee, Jiwan;Woo, Soyoung;Kim, Soohong;Lee, Jongjin;Kim, Seongjoon
Journal of Korea Water Resources Association
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v.55
no.12
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pp.1041-1052
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2022
This study is to estimate the optimal ecological flow and analysis the spatial distribution of fish habitat for Andong dam downstream reach (4,565.7 km2) using PHABSIM (Physical Habiat Simulation System) and River2D. To establish habitat models, the cross-section informations and hydraulic input data were collected uisng the Nakdong river basic plan report. The establishment range of PHABSIM was set up about 410.0 m from Gudam streamflow gauging station (GD) and about 6.0 km including GD for River2D. To select representative fish species and construct HSI (Habitat Suitability Index), the fish survey was performed at Pungji bridge where showed well the physical characteristics of target stream located downstream of GD. As a result of the fish survey, Zacco platypus was showed highly relative abundance resulting in selecting as the representative fish species, and HSI was constructed using physical habitat characteristics of the Zacco platypus. The optimal range of HSI was 0.3~0.5 m/s at the velocity suitability index, 0.4~0.6 m at the depth suitability index, and the substrate was sand to fine gravel. As a result of estimating the optimal ecological flow by applying HSI to PHABSIM, the optimal ecological flow for target stream was 20.0 m3/sec. As a result of analysis two-dimensional spatial analysis of fish habitat using River2D, WUA (Weighted Usable Area) was estimated 107,392.0 m2/1000 m under the ecological flow condition and it showed the fish habitat was secured throughout the target stream compared with Q355 condition.
This study set up 49 survey areas with an area of about 400 square meters in Abies koreana natural habitat to identify the species composition and vegetation structure of the A. koreana forest in the Mt. Jiri Nation Park, conducted field surveys using phytosociological methods, and performed the cluster analysis using the Two-Way Indicator Species Analysis (TWINSPAN) and Table manipulation. Subsequently, species composition analysis using the importance value, species diversity analysis, DBH analysis, sapling analysis, and similarity analysis was conducted by each cluster type. The cluster analysis classified the A. koreana forest in Mt. Jiri into five clusters, A, B, C, D, and E. The forest was divided into two clusters, Magnolia sieboldii-Dryopteris crassirhizoma-Sasa borealis and Betula ermanii-Solidago virgaurea-Calamagrostis arundinacea. The former was classified as type A and B by Cornus controversa-Hydrangea macrophylla, and the latter was classified as type E, a typical community, and a Sorbus commixta-Rhododendron mucronulatum cluster. And the S. commixta-R. mucronulatum cluster was divided into C type and D type by Picea jezoensis-Ligularia fischeri and Ainsliaea acerifolia. Through vegetation analysis, the importance value of A. koreana, Quercus mongolica, Acer pseudosieboldianum, Fraxinus sieboldiana, and B. ermanii was highly expressed in the A. koreana forest in Mt. Jiri. Regarding species diversity, the results were similar to those reported in other studies of A. koreana forests in Mt. Jiri. The analysis of diameter at breast height (DBH) showed that A. koreana dominated all layers, and the growth of saplings was also good, indicating that the dominance of A. koreana is expected to continue for a while. However, when considering the value of biodiversity that is expected to increase and threats caused by climate change, systematic preservation and management are required to respond to various threats based on continuous monitoring.
This study aims to investigate changes in the demand for ship officers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships (MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in the skill of ship officer. It also analyzes and proposes a plan for nurturing ship officers accordingly. As a result of the degree of recognition and AHP analysis, this study suggests that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but tasks such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore-based control. By evaluating the importance of change factors in the duties of ship officers in Maritime Autonomous Surface Ships, this study provides information on ship officer educational institutions' response strategies for nurturing ship officers and prioritization of resource allocation, etc. The importance of these factors was compared and evaluated to suggest changes in the duties of ship officers and methods of nurturing ship officers according to the introduction of Maritime Autonomous Surface Ships. It is expected that the findings of this study will be meaningful as it systematically derives the duties and competency factors of ship officers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.
Soon Jik Kwon;Yung Chul Jun;Hyeok Yeong Kwon;In Chul Hwang;Chang Su Lee;Tae Geun Kim
Journal of Wetlands Research
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v.25
no.4
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pp.335-344
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2023
Brachydiplax chalybea flavovittata, a climate-sensitive biological indicator species, was first observed and recorded at Jeju Island in Korea in 2010. Overwintering was recently confirmed in the Yeongsan River area. This study was aimed to predict the potential distribution patterns for the larvae of B. chalybea flavovittata and to understand its ecological characteristics as well as changes of population under global climate change circumstances. Data was collected both from the Global Biodiversity Information Facility (GBIF) and by field surveys from May 2019 to May 2023. We used for the distribution model among downloaded 19 variables from the WorldClim database. MaxEnt model was adopted for the prediction of potential and future distribution for B. chalybea flavovittata. Larval distribution ranged within a region delimited by northern latitude from Jeju-si, Jeju Special Self-Governing Province (33.318096°) to Yeoju-si, Gyeonggi-do (37.366734°) and eastern longitude from Jindo-gun, Jeollanam-do (126.054925°) to Yangsan-si, Gyeongsangnam-do (129.016472°). M type (permanent rivers, streams and creeks) wetlands were the most common habitat based on the Ramsar's wetland classification system, followed by Tp type (permanent freshwater marshes and pools) (45.8%) and F type (estuarine waters) (4.2%). MaxEnt model presented that potential distribution with high inhabiting probability included Ulsan and Daegu Metropolitan City in addition to the currently discovered habitats. Applying to the future scenarios by Intergovernmental Panel on Climate Change (IPCC), it was predicted that the possible distribution area would expand in the 2050s and 2090s, covering the southern and western coastal regions, the southern Daegu metropolitan area and the eastern coastal regions in the near future. This study suggests that B. chalybea flavovittata can be used as an effective indicator species for climate changes with a monitoring of their distribution ranges. Our findings will also help to provide basic information on the conservation and management of co-existing native species.
The physical properties of the ocean interior are determined by temperature and salinity. To observe them, we rely on satellite observations for broad regions of oceans. However, the satellite for salinity measurement, Soil Moisture Active Passive (SMAP), has low temporal and spatial resolutions; thus, more is needed to resolve the fast-changing coastal environment. To overcome these limitations, the algorithm to use the Geostationary Ocean Color Imager-II (GOCI-II) of the Geo-Kompsat-2B (GK-2B) was developed as the inputs for a Multi-layer Perceptron Neural Network (MPNN). The result shows that coefficient of determination (R2), root mean square error (RMSE), and relative root mean square error (RRMSE) between GOCI-II based sea surface salinity (SSS) (GOCI-II SSS) and SMAP was 0.94, 0.58 psu, and 1.87%, respectively. Furthermore, the spatial variation of GOCI-II SSS was also very uniform, with over 0.8 of R2 and less than 1 psu of RMSE. In addition, GOCI-II SSS was also compared with SSS of Ieodo Ocean Research Station (I-ORS), suggesting that the result was slightly low, which was further analyzed for the following reasons. We further illustrated the valuable information of high spatial and temporal variation of GOCI-II SSS to analyze SSS variation by the 11th typhoon, Hinnamnor, in 2022. We used the mean and standard deviation (STD) of one day of GOCI-II SSS, revealing the high spatial and temporal changes. Thus, this study will shed light on the research for monitoring the highly changing marine environment.
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