• Journal of Korea Water Resources Association
• /
• v.40 no.10
• /
• pp.769-781
• /
• 2007

Factor analysis has been usually employed in reducing quantity of data and summarizing information on a system or phenomenon. In this analysis methodology, variables are grouped into several factors by consideration of statistic characteristics, and the results are used for dropping variables which have lower weight than others. In this study, factor analysis was applied for extracting primary factors influencing multi-dam system operation in the Han River basin, where there are two multi-purpose dams such as Soyanggang Dam and Chungju Dam, and water has been supplied by integrating two dams in water use season. In order to fulfill factor analysis, first the variables related to two dams operation were gathered and divided into five groups (Soyanggang Dam: inflow, hydropower product, storage management, storage, and operation results of the past; Chungju Dam: inflow, hydropower product, water demand, storage, and operation results of the past). And then, considering statistic properties, in the gathered variables, some variables were chosen and grouped into five factors; hydrological condition, dam operation of the past, dam operation at normal season, water demand, and downstream dam operation. In order to check the appropriateness and applicability of factors, a multiple regression equation was newly constructed using factors as description variables, and those factors were compared with terms of objective function used in operation water resources optimally in a river basin. Reviewing the results through two check processes, it was revealed that the suggested approach provided satisfactory results. And, it was expected for extracted primary factors to be useful for making dam operation schedule considering the future situation and previous results.

• Korean Journal of Environmental Biology
• /
• v.19 no.4
• /
• pp.261-269
• /
• 2001

The purpose of present study was to introduce a multimetric approach, so called the Index of Biological Integrity (IBI) as a tool for evaluations of water environments. We used 11 metric systems for the IBI to evaluate stream conditions, based on the fish community, and modified 5 original metric attributes suggested by Karr (1981). Overall IBI values in Kap Stream averaged 36 (n = 5) and ranged 17${\sim}$49, indicating a 'fair condition' according to the modified criteria of Karr (1981) and U.S. EPA (1993). However, there were distinct differences in the IBI values among 5 study sites. The IBI values at sites 1, 2, and 3 were 49, 45, and 41, which indicated 'good${\sim}$excellent', 'good', and 'fair' condition, respectively, while values at sites 4 and 5 were 17 and 29, which indicated 'very poor' and 'poor', respectively. The minimum IBI at site 4 was probably due to continuous inputs of wastewater from wastewater disposal plants. The condition at site 4 resulted in predominance of tolerant species (50%), omnivore species (50%), and high abnormalies (43%). In the mean time, the IBI value at site 5, located near 5km downstream from the site 4, increased compared to that of site 4, and this seemed to be a result of recovery of water quality as the polluted water goes downward. We believe that present bioassessment methodology of IBI applied in this study may be used as a key tool to set up specific goals for stream restoration plans and dentify recovery levels of lotic ecosystems after restoration activities(i.e., prevention of point-source pollutant input, restoration of physical habitats, construction of riparian vegetation) as well as a biological measure diagnosing current stream conditions.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.18 no.3
• /
• pp.189-206
• /
• 2015

The present study was conducted to investigate the oceanic characteristics of the northern East China Sea through identification of long-term variation patterns of oceanic environment factors, for the objective of gaining understanding of oceanic environment characteristics of the northern waters of East China Sea, which closely influence the oceanic environments of waters nearby South Korea. The study methodology included the use of oceanographic data (water temperature, salinity, dissolved oxygen, nutrients, and chlorophyll-a) on the northern East China Sea from the Korea Oceanographic Data Center (KODC), collected by season for 20 years between 1995 and 2014. Moreover, for the study on the distribution of nutrients, chlorophyll-a. The main water masses that affected the northern East China Sea during the study period were classified as Changjiang diluted water (CDW), Tiawan current warm water (TCWW), Yellow Sea cold water (YSCW), and Kuroshio source water (KW). The forces of CDW and TCWW that forms on the surface and sub-surface layers had weakened for 20 years and the force of KW that forms on the intermediate layer showed a distinctively decreasing trend. However, YSCW showed a trend of expanding its force. Phosphate and silicate exhibited a decreasing tendency and phosphate showed a pattern of being depleted on the surface layer after 2009. It is determined that one of the reasons for this is the concentration of nutrients introduced through CDW and TCWW being too low. The concentration of chlorophyll-a exhibited an increasing tendency during the study period, the reasons for which are determined to be the influences of increase in water temperature, supply of nutrients via YSCW, and increases in light transmission from decrease in suspended solid due to the construction of the Three Gorges Dam.

• Journal of Korean Society of Transportation
• /
• v.23 no.3 s.81
• /
• pp.95-108
• /
• 2005

The purpose of this study is to develop the ITS evaluation model using the Probabilistic Risk Analysis (PRA) methodology and to demonstrate the goodness-of-fit of the large ITS projects through the comparative analysis between DEA and PRA model. The results of this study are summarized below. First, the evaluation mode] using PRA with Monte-Carlo Simulation(MCS) and Latin-Hypercube Sampling(LHS) is developed and applied to one of ITS projects initiated by local government. The risk factors are categorized with cost, benefit and social-economic factors. Then, PDF(Probability Density Function) parameters of these factors are estimated. The log-normal distribution, beta distribution and triangular distribution are well fitted with the market and delivered price. The triangular and uniform distributions are valid in benefit data from the simulation analysis based on the several deployment scenarios. Second, the decision making rules for the risk analysis of projects for cost and economic feasibility study are suggested. The developed PRA model is applied for the Daejeon metropolitan ITS model deployment project to validate the model. The results of cost analysis shows that Deterministic Project Cost(DPC), Deterministic Total Project Cost(DTPC) is the biased percentile values of CDF produced by PRA model and this project need Contingency Budget(CB) because these values are turned out to be less than Target Value(TV;85% value), Also, this project has high risk of DTPC and DPC because the coefficient of variation(C.V) of DTPC and DPC are 4 and 15 which are less than that of DTPC(19-28) and DPC(22-107) in construction and transportation projects. The results of economic analysis shows that total system and subsystem of this project is in type II, which means the project is economically feasible with high risk. Third, the goodness-of-fit of PRA model is verified by comparing the differences of the results between PRA and DEA model. The difference of evaluation indices is up to 68% in maximum. Because of this, the deployment priority of ITS subsystems are changed in each mode1. In results. ITS evaluation model using PRA considering the project risk with the probability distribution is superior to DEA. It makes proper decision making and the risk factors estimated by PRA model can be controlled by risk management program suggested in this paper. Further research not only to build the database of deployment data but also to develop the methodologies estimating the ITS effects with PRA model is needed to broaden the usage of PRA model for the evaluation of ITS projects.

• Journal of Bio-Environment Control
• /
• v.29 no.2
• /
• pp.161-170
• /
• 2020

There is systematic spatial variations in environmental properties due to sensitive reaction to external conditions at plastic greenhouse occupied 99.2% of domestic agricultural facilities. In order to construct 3 dimensional distribution of temperature, relative humidity, CO₂ and illuminance, measurement matrix as 3 by 3 by 5 in direction of width, height and length, respectively, dividing indoor space of greenhouse was designed and tested at experimental site. Linear regression analysis was conducted to evaluate optimal estimation method in terms with horizontal and vertical variations. Even though sole measurement point for temperature and relative humidity could be feasible to assess indoor condition, multiple measurement matrix is inevitably required to improve spatial precision at certain time domain such as period of sunrise and sunset. In case with CO₂, multiple measurement matrix could not successfully improve the spatial predictability during a whole experimental period. In case with illuminance, prediction performance was getting smaller after a time period of sunrise due to systematic interference such as indoor structure. Thus, multiple sensing methodology was proposed in direction of length at higher height than growing bed, which could compensate estimation error in spatial domain. Appropriate measurement matrix could be constructed considering the transition of stability in indoor environmental properties due to external variations. As a result, optimal measurement matrix should be carefully designed considering flexibility of construction relevant with the type of property, indoor structure, the purpose of crop and the period of growth. For an instance, partial cooling and heating system to save a consumption of energy supplement could be successfully accomplished by the deployment of multiple measurement matrix.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.48 no.4
• /
• pp.19-28
• /
• 2020

The Urban Heat Island (UHI) Effect has intensified due to urbanization and heat management at the urban level is treated as an important issue. Green space improvement projects and environmental policies are being implemented as a way to alleviate Urban Heat Islands. Several studies have been conducted to analyze the correlation between urban green areas and heat with linear regression models. However, linear regression models have limitations explaining the correlation between heat and the multitude of variables as heat is a result of a combination of non-linear factors. This study evaluated the Heat Island alleviating effects in Seoul during the summer by using a deep neural network model methodology, which has strengths in areas where it is difficult to analyze data with existing statistical analysis methods due to variable factors and a large amount of data. Wide-area data was acquired using Landsat 8. Seoul was divided into a grid (30m × 30m) and the heat island reduction variables were enter in each grid space to create a data structure that is needed for the construction of a deep neural network using ArcGIS 10.7 and Python3.7 with Keras. This deep neural network was used to analyze the correlation between land surface temperature and the variables. We confirmed that the deep neural network model has high explanatory accuracy. It was found that the cooling effect by NDVI was the greatest, and cooling effects due to the park size and green space proximity were also shown. Previous studies showed that the cooling effects related to park size was 2℃-3℃, and the proximity effect was found to lower the temperature 0.3℃-2.3℃. There is a possibility of overestimation of the results of previous studies. The results of this study can provide objective information for the justification and more effective formation of new urban green areas to alleviate the Urban Heat Island phenomenon in the future.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.8 no.2
• /
• pp.86-96
• /
• 2006

Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.39 no.3
• /
• pp.42-55
• /
• 2021

This study investigated the memories of the natives and the migrants who had been living with the 760-year-old Zelkova serrata located in the Keangnam Apartment Complex in Dogok 1-dong. Place memory is a newly illuminated concept since the 1980s, and is also used as a new research methodology for studying and recording multi-layered memories left in a place based on feelings and traces of vivid memories. The urban development of Gangnam, which began in the 1970s, quickly changed rural to apartment complexes. The natives of Yeokmal were scattered throughout the country, and new migrants moved in. In the process, zelkova serrata was managed in different ways from time to time, and residents also establish relationship in different ways. Natives used to take a rest in the tree or swing at Dan-o, and recognized it as a place to receive the god during the village ritual. In other words, they shared the entire process of life and death and were given various roles depending on the lives of the residents. It is also a direct experience that was experienced in detail and a place where collective memories of residents are melted. On the other hand, with the construction of Keangnam Apartment, the management of zelkova tree has become stricter, making it impossible for migrants to access. Migrants have come to enjoy zelkova serrata visually, and the annual Yeokmal Traditional Festival makes common memories in the city. In addition, many people personified trees and received mental comfort. In addition, the nature of the old big tree was highlighted in the background of the city, and the symbol of "uniqueness and speciality" was newly formed, which led to the formation of pride and attachment. Through the memories of the two subjects' zelkova tree, we were able to examine the memories of the tree value, and management of protected tree in the city.

• Korean Journal of Environmental Biology
• /
• v.38 no.4
• /
• pp.634-649
• /
• 2020

Recently, stream longitudinal connectivity has been a topic of investigation due to the frequent disconnections and the impact of aquatic ecosystems caused by the construction of small and medium-sized weirs and various artificial structures (fishways) directly influencing the stream ecosystem health. In this study, the international and domestic research trends of the longitudinal connectivity in aquatic ecosystems were evaluated and the applicability of fish-based longitudinal connectivity models used in developed countries was analyzed. For these purposes, we analyzed the current status of research on longitudinal connectivity and structural problems, fish monitoring methodology, monitoring approaches, longitudinal disconnectivity of fish movement, and biodiversity. In addition, we analyzed the current status and some technical limitations of physical habitat suitability evaluation, ecology-based water flow, eco-hydrological modeling for fish habitat connectivity, and the s/w program development for agent-based model. Numerous references, data, and various reports were examined to identify worldwide longitudinal stream connectivity evaluation models in European and non-European countries. The international approaches to longitudinal connectivity evaluations were categorized into five phases including 1) an approach integrating fish community and artificial structure surveys (two types input variables), 2) field monitoring approaches, 3) a stream geomorphological approach, 4) an artificial structure-based DB analytical approach, and 5) other approaches. the overall evaluation of survey methodologies and applicability for longitudinal stream connectivity suggested that the ICE model (Information sur la Continuite Ecologique) and the ICF model (Index de Connectivitat Fluvial), widely used in European countries, were appropriate for the application of longitudinal connectivity evaluations in Korean streams.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_1
• /
• pp.1421-1434
• /
• 2020

The frequency and intensity of heatwaves have been increasing due to climate change. Since urban areas are more severely damaged by heatwaves as they act in combination with the urban heat island phenomenon, every possible preparation for such heat threats is required. Many overseas local governments build heat maps using a variety of spatial information to prepare for and counteract heatwaves, and prepare heatwave measures suitable for each region with different spatial characteristics within a relevant city. Building a heat map is a first and important step to prepare for heatwaves. The cases of heat map construction and thermal environment analysis involve various area distributions from urban units with a large area to local units with a small area. The method of constructing a heat map varies from a method utilizing remote sensing to a method using simulation, but there is no standard for using differentiated spatial information according to spatial scale, so each researcher constructs a heat map and analyzes the thermal environment based on different methods. For the above reason, spatial information standards required for building a heat map according to the analysis scale should be established. To this end, this study examined spatial information, analysis methodology, and final findings related to Korean and oversea analysis studies of heatwaves and urban thermal environments to suggest ways to improve the utilization efficiency of spatial information used to build urban heat maps. As a result of the analysis, it was found that spatial, temporal, and spectral resolutions, as basic resolutions, are necessary to construct a heat map using remote sensing in the use of spatial information. In the use of simulations, it was found that the type of weather data and spatial resolution, which are input condition information for simulation implementation, differ according to the size of analysis target areas. Therefore, when constructing a heat map using remote sensing, spatial, spectral, and temporal resolution should be considered; and in the case of using simulations, the spatial resolution, which is an input condition for simulation implementation, and the conditions of weather information to be inputted, should be considered in advance. As a result of understanding the types of monitoring elements for heatwave analysis, 19 types of elements were identified such as land cover, urban spatial characteristics, buildings, topography, vegetation, and shadows, and it was found that there are differences in the types of the elements by spatial scale. This study is expected to help give direction to relevant studies in terms of the use of spatial information suitable for the size of target areas, and setting monitoring elements, when analyzing heatwaves.