• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.417-426
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• 2019

Conventional visualization of PM (Particulate Matter)10 flows applies superimposition of concentration distribution maps and wind field maps. This method is efficient for small scale maps where only macro flow trends are of interest. However, in the case of urban areas, local flows are difficult to model at micro level using wind fields, and therefore different methods of flow extraction is deemed necessary. In this study, flow information is extracted and visualized directly from the PM10 density data by using the gravity model. This method has the advantage that additional information such as wind field is not necessary for estimating the intensity and direction of PM10 flow. The extracted spatio-temporal flow patterns of PM10 are analyzed with relation to traffic information.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.299-303
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• 2008

In this study, an uncertainty assessment for surface air temperature(T2m) and precipitation(PCP) over East Asia is carried out. The data simulated by the intergovermental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) Atmosphere-Ocean coupled general circulation Model (AOGCM) are used to assess the uncertainty. Examination of the seasonal uncertainty of T2m and PCP variabilities shows that spring-summer cold bias and fall warm bias of T2m are found over both East Asia and the Korea peninsula. In contrast, distinctly summer dry bias and winter-spring wet bias of PCP over the Korea peninsula is found. To investigate the PCP seasonal variability over East Asia, the cyclostationary empirical orthogonal function(CSEOF) analysis is employed. The CSEOF analysis can extract physical modes (spatio-temporal patterns) and their undulation (PC time series) of PCP, showing the evolution of PCP. A comparison between spatio-temporal patterns of observed and modeled PCP anomalies shows that positive PCP anomalies located in northeastern China (north of Korea) of the multi-model ensemble(MME) cannot explain properly the contribution to summer monsoon rainfalls across Korea and Japan. The uncertainty of modeled PCP indicates that there is disagreement between observed and MME anomalies. The spatio-temporal deviation of the PCP is significantly associated with lower- and upper-level circulations. In particular, lower-level moisture transports from the warm pool of the western Pacific and corresponding moisture convergence significantly contribute to summer rainfalls. These lower- and upper-level circulations physically consistent with PCP give a insight of the reason why differences between modeled and observed PCP occur.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.473-478
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• 2015

Recently, automatic video monitoring of individual pigs is emerging as an important issue in the management of group-housed pigs. Although a rich variety of studies have been reported on video monitoring techniques in intensive pig farming, it still requires further elaboration. In particular, when there exist adjoining pigs in a crowd pig room, it is necessary to have a way of separating adjoining pigs from the perspective of an image processing technique. In this paper, we propose an efficient image segmentation solution using both spatio-temporal information and region growing method for the identification of individual pigs in video surveillance systems. The experimental results with the videos obtained from a pig farm located in Sejong illustrated the efficiency of the proposed method.

• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.277-288
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• 1999

The aim of this review is to provide perspectives on the application of remote sensing techniques for observation of marine environmental changes on various spatio-temporal scales. Currently available remote sensing technologies are reviewed and future direction is suggested. For better utilization of remote sensing, a comprehensive plan should be developed by a demand-side and problem-solving approach. Marine environmental changes should be observed on proper spatio-temporal scales where the processes occur. For appropriate observation and monitoring of various environmental changes in coastal regions, more sensors must be utilized. Platforms other than satellites should also be utilized to expand the spatio-temporal scales of observation. Calibration/validation activities, required for accurate interpretation of remotely sensed data, could utilize buoys and ship-of-opportunity sensors. It is desirable that such systems by developed as a part of an integrated monitoring network.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.2
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• pp.62-72
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• 2017

Spatio-temporal projection of evapotranspiration over croplands would be useful for assessment of climate change impact and development of adaptation strategies in agriculture. Potential evapotranspiration (PET) and dryness index (DI) during rice growing seasons were calculated using climate change scenario data provided by the National Institute of Meteorological Research (NIMR). A data processing tool for gridded climate data files, readGrADSWrapper, was used to calculate PET and DI during the current (1986-2005) and future (2006-2100) periods. Scripts were written to implement the formulas of PET and DI in R, which is an open source statistical data analysis tool. Evapotranspiration in rice fields ($PET_{Rice}$) was also determined using R scripts. The Spatio-temporal patterns of PET differed by regions in Korean Peninsula under current and future climate conditions. Overall, PET and $PET_{Rice}$ tended to increase throughout the $21^{st}$ century. Those results suggested that region-specific water resource managements would be needed to minimize the risk of water loss in the regions where considerable increases in PET would occur under the future climate conditions. For example, a number of provinces classified as a humid region were projected to become a sub-humid region in the future. The Spatio-temporal assessment of water resources based on PET and DI would help the development of climate change adaptation strategies for rice production in the 21st century. In addition, the studies on climate change impact would be facilitated using specialized data tools, e.g., readGrADSWrapper, for geospatial analysis of climate data.

• Atmosphere
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• v.21 no.4
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• pp.337-347
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• 2011

In this paper, we developed a detection and correction method of noisy pixels embedded in the time series of normalized difference vegetation index (NDVI) data based on the spatio-temporal continuity of vegetation conditions. For the application of the method, 25-year (1982-2006) GIMMS (Global Inventory Modeling and Mapping Study) NDVI dataset over the Korean peninsula were used. The spatial resolution and temporal frequency of this dataset are $8{\times}8km^2$ and 15-day, respectively. Also the land cover map over East Asia is used. The noisy pixels are detected by the temporal continuity check with the reference values and dynamic threshold values according to season and location. In general, the number of noisy pixels are especially larger during summer than other seasons. And the detected noisy pixels are corrected by the iterative method until the noisy pixels are completely corrected. At first, the noisy pixels are replaced by the arithmetic weighted mean of two adjacent NDVIs when the two NDVI are normal. After that the remnant noisy pixels are corrected by the weighted average of NDVI of the same land cover according to the distance. After correction, the NDVI values and their variances are increased and decreased by 5% and 50%, respectively. Comparing to the other correction method, this correction method shows a better result especially when the noisy pixels are occurred more than 2 times consistently and the temporal change rates of NDVI are very high. It means that the correction method developed in this study is superior in the reconstruction of maximum NDVI and NDVI at the starting and falling season.

• Wind and Structures
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• v.21 no.4
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• pp.425-442
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• 2015

This paper discusses the processing of the wind loads measured in wind tunnel tests by means of multi-channel pressure scanners, in order to compute the response of 3D structures to atmospheric turbulence in the time domain. Data compression and the resulting computational savings are still a challenge in industrial contexts due to the multiple trial configurations during the construction stages. The advantage and robustness of the bi-orthogonal decomposition (BOD) is demonstrated through an example, a sail glass of the Fondation Louis Vuitton, independently from any tentative physical interpretation of the spatio-temporal decomposition terms. We show however that the energy criterion for the BOD has to be more rigorous than commonly admitted. We find a level of 99.95 % to be necessary in order to recover the extreme values of the loads. Moreover, frequency limitations of wind tunnel experiments are sometimes encountered in passing from the scaled model to the full scale structure. These can be alleviated using a spectral extension of the temporal function terms of the BOD.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.131-140
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• 2020

The purpose of this study is to analyze the possibility of future droughts by calculating the Standardized Groundwater level Index(SGI) after predicting groundwater level using Long Short Term Memory (LSTM) model. The groundwater level of the Kumho River basin was predicted for the next three years by using the LSTM model, and it was validated through RMSE after learning with observation data except the last three years. The temporal SGI was calculated by using the prediction data and the observation data. The calculated SGI was interpolated within the study area, and the spatial SGI was calculated as the average value for each catchment using the interpolated SGI. The possibility of spatio-temporal drought was analyzed using calculated spatio-temporal SGI. It is confirmed that there is a spatio-temporal difference in the possibility of drought. Through the improvement of deep learning model and diversification of validation method, it is expected to obtain more reliable prediction results and the expansion of study area can be used to respond to drought nationwide, and furthermore it can provide important information for future water resource management.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.377-393
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• 2016

Vehicle emissions have been known as a critical factor to give a negative impact on the public health. In particular, particulate matters(PM) and NOx are highly related with respiratory diseases such as asthma. This study aimed at analyzing spatio-temporal patterns of PM and NOx generated from urban freeway traffic. MOVES, which is a well-known emission analysis tool presented by US Environmental Protection Agency(EPA), was applied to estimate PM and NOx based on traffic volume and speed data obtained from Seoul Outer Ring Expressway during January~June, 2012. K-means clustering analysis was used for categorizing the Level of Vehicle Emissions(LOVE) to support more systematical identification of the significance of emissions. Then, spatio-temporal analyses of estimated emissions were conducted by LOVE. Finally, this study proposed a set of strategies to reduce both PM and NOx to enhance public health based on analysis results.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.4
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• pp.57-65
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• 2015

This study investigates characteristics of time series spatial distribution on climate factors in Andong Dam basin by estimating precise spatio-temporal distribution of hydro-meteorological information. A spatio-temporal distribution by estimating Semi-Variogram based on spatial autocorrelation was examined using the data from ASOS and 7 hydro-meteorological observatories in Andong Dam basin of upper Nakdonggang River, which were installed and observed by NIMR(National Institute of Meterological Research). Also, temperature and humidity as climate variables were analyzed and it was recognized that there is a variability in watershed area by time and months. Regardless of season, an equal spatial distribution of temperature at 14 o'clock and humidity at 10 o'clock was identified, and nonequal distribution was noticed for both variables at 18 o'clock. From monthly spatial analysis, the most unequal distribution of temperature was seen in January, and the most equal distribution was detected in September. The most unequal distribution of humidity was identified in May, and the most equal distribution was seen in January. Unlike in forest, seasonal spatial distribution characteristics were less apparent;but temperature and humidity had respective characteristics in hydro-meteorology.