• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.785-799
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• 2023

In this study, we proposed a new concept termed the Secondary Peak Constant (SPC) and discerned the temporal characteristics of independent rainstorm events based on unit time and SPC about 24 observation stations in Seoul. Utilizing rainfall observations from 2000 to 2022, independent rainstorm events discreted from rainfall data per unit time. The temporal characteristics of these events were derived according to unit time, and temporal characteristics of the peak rainfall were identified through the SPC. Finally, the temporal characteristics of independent rainstorm events were examined distinctively when analyzed by unit time and SPC. Independent rainstorm events with smaller unit time showed significantly larger total rainfall, rainfall duration, and rainfall intensity. The temporal characteristics of the largest peak rainfall (1^st Peak) within independent rainstorm events followed a sequence of Q4>Q2>Q3>Q1. Additionally, the 2^nd Peak rainfall predominantly occurred the location where the 1^st Peak appeared. The proportion of independent rainstorm events with multiple peak rainfalls exceeded 50.0% when the SPC was 0.7 or lower. The average number of peak rainfalls within independent rainstorm events ranged from 1.5 to 3.4. This study identified the temporal characteristics of independent rainstorm events based on unit time. Then, the peak rainfall of temporal characteristics was quantified by SPC on this study. Hence, it is evident that the temporal characteristics of independent rainstorm events for specific area can be anlayzed and quantified based on unit time and SPC.

• Journal of Positioning, Navigation, and Timing
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• v.2 no.2
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• pp.109-114
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• 2013

The vulnerability of GPS to interference signals was reported in the early 2000s, and an eLORAN system has been suggested as a backup navigation system for replacing the existing GPS. Thus, relevant studies have been carried out in the United States, Europe, Korea, etc., and especially, in Korea, the research and development is being conducted for the FOC of the eLORAN system by 2018. The required performance of the eLORAN system is to meet the HEA performance, and to achieve this, it is essential to perform ASF correction based on a dLORAN system. ASF can be divided into temporal ASF, nominal ASF, and spatial ASF. Spatial ASF is the variation due to spatial characteristics, and is stored in an eLORAN receiver in the form of a premeasured map. Temporal ASF is the variations due to temporal characteristics, and are transmitted from a dLORAN site to a receiver via LDC. Unlike nominal ASF that is obtained by long-term measurement (over 1 year), temporal ASF changes in a short period of time, and ideally, real-time correction needs to be performed. However, it is difficult to perform real-time correction due to the limit of the transmission rate of the LDC for transmitting correction values. In this paper, to determine temporal ASF correction frequency that shows satisfactory performance within the range of the limit of data transmission rates, relative variations of temporal ASF in summer and winter were measured, and the stability of correction values was analyzed using the average of temporal ASF for a certain period.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.13-20
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• 2011

The spatio-temporal pattern in precipitation is a significant element in defining characteristics of precipitation. In this study, a new scheme on regionalization utilizing temporal information was introduced on the basis of existing approaches that is mainly based on simple moments of data and geographical information. Given the identified spatio-temporal pattern, this study was extended to characterize regional pattern of annual maximum rainfall over Korea. We have used circular statistics to characterize the temporal distribution on the precipitation, and the circular statistics allow us to effectively assess changes in timing of the extreme rainfall in detail. In this study, a modified K-means method was incorporated with derived temporal characteristics of extreme rainfall in order to better characterize hydrologic pattern for regional frequency analysis. The extreme rainfall was reasonably separated into five categories that considered most attributes in both quantitative and temporal changes in extremes. The results showed that the proposed approach is a promising approach for regionalization in term of physical understanding of extreme rainfall.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.719-731
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• 2021

This study proposes a two-stage hybrid classification model for crop classification using multi-temporal remote sensing images; the model combines feature embedding by using an autoencoder (AE) with a convolutional neural network (CNN) classifier to fully utilize features including informative temporal and spatial signatures. Long short-term memory (LSTM)-based AE (LAE) is fine-tuned using class label information to extract latent features that contain less noise and useful temporal signatures. The CNN classifier is then applied to effectively account for the spatial characteristics of the extracted latent features. A crop classification experiment with multi-temporal unmanned aerial vehicle images is conducted to illustrate the potential application of the proposed hybrid model. The classification performance of the proposed model is compared with various combinations of conventional deep learning models (CNN, LSTM, and convolutional LSTM) and different inputs (original multi-temporal images and features from stacked AE). From the crop classification experiment, the best classification accuracy was achieved by the proposed model that utilized the latent features by fine-tuned LAE as input for the CNN classifier. The latent features that contain useful temporal signatures and are less noisy could increase the class separability between crops with similar spectral signatures, thereby leading to superior classification accuracy. The experimental results demonstrate the importance of effective feature extraction and the potential of the proposed classification model for crop classification using multi-temporal remote sensing images.

• MALSORI
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• no.53
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• pp.93-102
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• 2005

The performance of a speech recognition system is generally degraded in telephone environment because of distortions caused by background noise and various channel characteristics. In this paper, data-driven temporal filters are investigated to improve the performance of a specific recognition task such as telephone speech. Three different temporal filtering methods are presented with recognition results for Korean connected-digit telephone speech. Filter coefficients are derived from the cepstral domain feature vectors using the principal component analysis. According to experimental results, the proposed temporal filtering method has shown slightly better performance than the previous ones.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.381-392
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• 2003

Multi-temporal approaches using sequential data acquired over multiple years are essential for satisfactory discrimination between many land-cover classes whose signatures exhibit seasonal trends. At any particular time, the response of several classes may be indistinguishable. A harmonic model that can represent seasonal variability is characterized by four components: mean level, frequency, phase and amplitude. The trigonometric components of the harmonic function inherently contain temporal information about changes in land-cover characteristics. Using the estimates which are obtained from sequential images through spectral analysis, seasonal periodicity can be incorporates into multi-temporal classification. The Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 ～ 2000 using a dynamic technique. Land-cover types were then classified both with the estimated harmonic components using an unsupervised classification approach based on a hierarchical clustering algorithm. The results of the classification using the harmonic components show that the new approach is potentially very effective for identifying land-cover types by the analysis of its multi-temporal behavior.

• Journal of Environmental Science International
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• v.13 no.1
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• pp.27-36
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• 2004

Present study analyzed the temporal and spatial characteristics of PM10 pollution in Metropolitan Daegu area based on air pollution monitoring station data and measurements of PM10 concentrations in background area in order to provide essential data for efficient PM10 pollution management. The significant variation of spatial and temporal PM10 concentrations in Daegu area was observed during the study years. The highest maximum PM10 concentration(332 $\mu\textrm{g}$/㎥), average concentration(88 $\mu\textrm{g}$/㎥) and frequency exceeding PM10 daily standard(150 $\mu\textrm{g}$/㎥) were all observed in Namsandong located near a major roadway. The hourly and weekly variations of PM10 concentrations had different pattern for the measurement sites. The monthly and seasonal concentrations exhibited a notable characteristic： the maximum concentration was obtained in spring season, most likely due to Yellow sand effects. Furthermore, this temporal variation of PM10 pollution varied with study site. Meanwhile, the PM10 values measured at the monitoring site, Manchondong, were comparable with those of a control site. The average PM10 concentration ranged from 23 $\mu\textrm{g}$/㎥ to 115 $\mu\textrm{g}$/㎥ with a mean value of 53 $\mu\textrm{g}$/㎥ in the former site and from 22 $\mu\textrm{g}$/㎥ to 91 $\mu\textrm{g}$/㎥ with a mean value of 45 $\mu\textrm{g}$/㎥ in the latter site.

• ETRI Journal
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• v.31 no.1
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• pp.1-9
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• 2009

Frequency domain analysis is a fundamental procedure for understanding the characteristics of visual data. Several studies have been conducted with 2D videos, but analysis of stereoscopic 3D videos is rarely carried out. In this paper, we derive the Fourier transform of a simplified 3D video signal and analyze how a 3D video is influenced by disparity and motion in terms of temporal aliasing. It is already known that object motion affects temporal frequency characteristics of a time-varying image sequence. In our analysis, we show that a 3D video is influenced not only by motion but also by disparity. Based on this conclusion, we present a temporal anti-aliasing filter for a 3D video. Since the human process of depth perception mainly determines the quality of a reproduced 3D image, 2D image processing techniques are not directly applicable to 3D images. The analysis presented in this paper will be useful for reducing undesirable visual artifacts in 3D video as well as for assisting the development of relevant technologies.

• Current Research on Agriculture and Life Sciences
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• v.32 no.4
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• pp.203-209
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• 2014

This study investigated characteristics of rainfall and water quality in Saemangeum area with attention to temporal and spatial distributions. A high variability in rainfall was noted during July and August. The temporal analysis of water quality data indicated that DO and TN as well as BOD, COD and SS were within national standards except for increased concentrations during spring and summer, unlike TP values that indicated poor water quality. Standard deviation showed a high variability in SS among the seasons most especially during summer. The high dispersion indicated variability in the chemical composition of pollutants where the temporal and spatial variations caused by polluting sources and/or seasonal changes were most evident for BOD and COD during winter and spring. The box plots and bar charts showed steadily low concentrations of BOD, COD, TN and TP except within Iksan and notable significant variations in SS concentrations among the monitoring stations. Thus, high pollution levels requiring intervention were identified in Mangyeong river basin with particular concern for areas represented by Iksan station. It was noted that Iksan received a considerable amount of rainfall which meant high runoff which could explain the significant pollution levels revealed in the water quality spatial distribution. Major pollution contributing pollutants within Saemangeum area were identified as SS, BOD, COD and TN. Therefore the present results could be used as a guideline for the temporal and spatial distributions analysis of both rainfall and water quality in Saemangeum watershed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.209-215
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• 2020

In order to understand the characteristics of natural droughts, it is very important to interpret the spatio-temporal relationship between different types of droughts. In this study, meteorological and hydrological drought events were defined to account for the overlap between drought duration and spatial extent in three dimensions (i.e., latitude, longitude, and timing). In other words, the spatio-temporal drought propagation characteristics were analyzed based on the drought characteristic factors (duration, area, depth, center). The drought map considering the characteristics of spatio-temporal drought propagation can be used to find the fundamental cause of the hydrological drought which is expected to frequently occur in the future. In addition, the drought map is expected to be useful in preparing an effective drought response plan.