• Journal of Environmental Impact Assessment
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• v.28 no.3
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• pp.215-230
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• 2019

The objective of this research is to evaluate the water quality characteristics using the statistical analysis of major tributaries in the Han River and to provide water quality improvement plan by selecting tributaries that should be preferentially managed by river grade classification method. The major 15 tributaries in Han River watershed were monitored for discharge and water quality during January-December 2017. As a result of the correlation analysis, the river discharge has been not correlation with other water quality constituents (p>0.05) but COD and TOC were significantly correlated (r=0.957, p<0.01). The main cause of water quality fluctuation was organic pollutants and nutrients in the principal component analysis (PCA) method. The BOD, COD, TOC, TN, and TP were found to be significantly different (p<0.05) by seasonal in result of one-way ANOVA analysis. Result of river grade classification by quantitative indicators the tributaries requiring improvement of water quality were Gulpocheon, Anyangcheon, Wangsukcheon, and Tancheon which affected by wastewater treatment plant.In this research, we determined tributaries that need to improve the water quality of Han River watershed and it can be used as an important data for efficient water quality management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.293-301
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• 2004

This study analyzes the interrelationship with air pollution quality and land used patterns, and analyzes the history and optimal allocation of TMS using GIS. Seasonal air pollution map are maded of TMS data in study area, and land used patterns based on Land Cover Classification Map are reclassified as residential area, commercial area, industrial area, traffic concentrated area, and non-Polluted area. Pollution sources can be identified through analyzing the correlation of air pollution and land used patterns by GIS spatial overlaying technique. Hence, the result shows that it coincides with the characteristics of conventional air pollution. Air pollution quality measured by TMS shows similar to that of its near stations or the same land used patterns, through the history and allocation analysis of TMS. Therefore, it is need to consider these characteristics in setting TMS positions in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.106-106
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• 2015

The information of flow regimes continues to be norm in water resource and watershed management, in that stream flow regime is a crucial factor influencing water quality, geomorphology, and the community structure of stream biota. The objectives of this study were to estimate Korean stream flows from landscape variables, classify stream flow gages using hydraulic characteristics, and then apply these methods to ungaged biological monitoring sites for effective ecological assessment. Here I used a linear modeling approach (MLR, PCA, and PCR) to describe and predict seasonal flow statistics from landscape variables. MLR models were successfully built for a range of exceedance discharges and time frames (annual, January, May, July, and October), and these models explained a high degree of the observed variation with r squares ranging from 0.555 (Q95 in January) to 0.899 (Q05 in July). In validation testing, predicted and observed exceedance discharges were all significantly correlated (p<0.01) and for most models no significant difference was found between predicted and observed values (Paired samples T-test; p>0.05). I classified Korean stream flow regimes with respect to hydraulic and hydrologic regime into four categories: flashier and higher-powered (F-HP), flashier and lower-powered (F-LP), more stable and higher-powered (S-HP), and more stable and lower-powered (S-LP). These four categories of Korean streams were related to with the characteristics of environmental variables, such as catchment size, site slope, stream order, and land use patterns. I then applied the models at 684 ungaged biological sampling sites used in the National Aquatic Ecological Monitoring Program in order to classify them with respect to basic hydrologic characteristics and similarity to the government's array of hydrologic gauging stations. Flashier-lower powered sites appeared to be relatively over-represented and more stable-higher powered sites under-represented in the bioassessment data sets.

• Journal of Environmental Science International
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• v.32 no.12
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• pp.883-898
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• 2023

To investigate the occurrence characteristics and types of fog on the Korean Peninsula over the past three years (2020 to 2022), data from 96 synoptic meteorological observatories and 21 ocean buoys were collected and analyzed. We included precipitation fog, which occurs after precipitation events, and cloud-base lowering fog, which is caused by the development of lower-level clouds, with a total six subtypes of fog. In the case of cloud-base lowering fog, the occurrence frequency at 2.6% was not high at 2.6%, but the duration of low visibility below 200 m was very long at 6.9 hours. The seasonal frequency of fog is low in spring and winter, high in summer over islands and coastal areas, and high in autumn over inland areas. The frequency of inland fog, which is characterized by high radiation fog and dense fog, requires attention in terms of transportation safety, with an occurrence time of 0500 LST to 1000 LST. Therefore, systematic analysis of precipitation fog and cloud-base lowering, as well as radiation and advection fog, is required in the analysis of recognizing fog as a disaster and causing transportation disorders.

• Journal of Haehwa Medicine
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• v.12 no.2
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• pp.85-103
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• 2004

From the studies on a few specific chapters of Tibetan Medical Painting, following conclusions were obtained. 1. The doctors of Tibet had to be not only academically and morally perfect, but he must show and have respect for his religion and his religous leaders and Gods. 2 The most main causes for all the disease that Tibetan Medicine resumed were hatred, delusion and ignorance of human mind which can make the physiological bile, wind, and phlegm to turn into pathological ones. 3. There is the classification of primary cause, which would be the human mind mentioned above, and the secondary cause which include dietary, behavior, seasonal problems, etc. 4. The Tibetans thought the digestive power is very important in the improvement or degravation of the disease. 5. More chapters were held for explaining the disease of fever, its clssification, stages, and cures which can indirectly show that the Tibetans might have thought it was very serious and could be very harmful. 6. The treatments for all the kinds of disease not only include medication and external therapy but also dietary and behavior regulations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.423-430
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• 2017

Recently, data analysis research has been carried out using the deep learning technique in various fields such as image interpretation and/or classification. Various types of algorithms are being developed for many applications. In this paper, we propose a precipitation prediction algorithm based on deep learning with high accuracy in order to take care of the possible severe damage caused by climate change. Since the geographical and seasonal characteristics of Korea are clearly distinct, the meteorological factors have repetitive patterns in a time series. Since the LSTM (Long Short-Term Memory) is a powerful algorithm for consecutive data, it was used to predict precipitation in this study. For the numerical test, we calculated the PWV (Precipitable Water Vapor) based on the tropospheric delay of the GNSS (Global Navigation Satellite System) signals, and then applied the deep learning technique to the precipitation prediction. The GNSS data was processed by scientific software with the troposphere model of Saastamoinen and the Niell mapping function. The RMSE (Root Mean Squared Error) of the precipitation prediction based on LSTM performs better than that of ANN (Artificial Neural Network). By adding GNSS-based PWV as a feature, the over-fitting that is a latent problem of deep learning was prevented considerably as discussed in this study.

• Journal of Environmental Science International
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• v.15 no.4
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• pp.373-378
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• 2006

The western coast of South Korea is famous for its large and broad tidal lands. Nevertheless, land reclamation, which has been conducted on a large scale, such as Sihwa embankment construction project has accelerated coastal environmental changes in the embankment inland. For monitoring of environmental change, vegetation change detecting of the embankment inland were carried out and field survey data compared with Landsat TM, ETM+, IKONOS, and EOC satellite remotely sensed data. In order to utilize multi-temporal remotely sensed images effectively, all data set with pixel size were analyzed by same geometric correction method. To detect the tidal land vegetation change, the spectral characteristics and spatial resolution of Landsat TM and ETM+ images were analyzed by SMA(spectral mixture analysis). We obtained the 78.96% classification accuracy and Kappa index 0.2376 using March 2000 Landsat data. The SMA(spectral mixture analysis) results were considered with comparing of vegetation seasonal change detection method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.383-390
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• 2016

Remote sensing data has been widely used in the estimation of crop yields by employing statistical methods such as regression model. Machine learning, which is an efficient empirical method for classification and prediction, is another approach to crop yield estimation. This paper described the corn yield estimation in Iowa State using four machine learning approaches such as SVM (Support Vector Machine), RF (Random Forest), ERT (Extremely Randomized Trees) and DL (Deep Learning). Also, comparisons of the validation statistics among them were presented. To examine the seasonal sensitivities of the corn yields, three period groups were set up: (1) MJJAS (May to September), (2) JA (July and August) and (3) OC (optimal combination of month). In overall, the DL method showed the highest accuracies in terms of the correlation coefficient for the three period groups. The accuracies were relatively favorable in the OC group, which indicates the optimal combination of month can be significant in statistical modeling of crop yields. The differences between our predictions and USDA (United States Department of Agriculture) statistics were about 6-8 %, which shows the machine learning approaches can be a viable option for crop yield modeling. In particular, the DL showed more stable results by overcoming the overfitting problem of generic machine learning methods.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.4
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• pp.3-15
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• 2008

North Korea is one of the most vulnerable countries of the world for drought but still it is difficult to find scientific researches for understanding of the drought characteristics. This study analyzed the temporal and spatial distribution of meterological drought severity and classified the drought development types in North Korea. All eleven drought indices were tested such as seasonal rainfall, PDS, SPI and so on, and then drew the drought risk map by each indicator using frequency analysis and GIS(Geographic Information Systems) for twenty one meteorological stations. In addition meteorological drought characteristics in North Korea was classified to six patterns on Si/Gun administrative units using cluster analysis on the drought indicators. The cluster III has the strongly drought-resistant area due to sufficient rainfall and the cluster V was considered as the most drought-vulnerable area, Pungsan and Sinpo, because of the severest drought condition for eight drought indicators. The results of this study are expected to be provided for the basic understanding of regionalized drought severity and characteristics confronting the risk of drought from climate variations in North Korea.

• ALGAE
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• v.21 no.2
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• pp.217-228
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• 2006

Seasonal compositions, standing crops and trophic status of phytoplankton were investigated at 13 sites of Suwon-si, Gyeonggi-do from June, 2004 to March, 2005. Total of 304 taxa were found, and classified as 4 phylums 4 classes 13 orders 36 families 93 genera 246 species 47 varieties 8 forms and 3 unidentified species by Engler’s classification system. Judged by standing crops of phytoplakton, algal blooming was observed at every sampling sites except Pajang reservoir, Hagwanggyo reservoir, Suwon-cheon and Woncheon-cheon throughtout the whole study periods. While Hagwanggyo reservoir appeared to be in mesotrophic or oligomesotrophic status, most of the remaining sampling sites in Suwon-si were in eutrophic status according to trophic status index. In this study, the most abundant taxa revealed in eutrophic status were Anabaena circinalis, Pandorina morum, Scenedesmus acuminatus, and S. quadricauda as previously reported as the most abundant taxa in eutrophic status. But Navicula cryptocephala and Cyclotella stelligera, reported as the abundant taxa of mesotrophic and oligomesotrophic status, respectively, occurred in eutrophic status in this study.