• 한국수자원학회논문집
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• 제56권10호
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• pp.619-629
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• 2023

최근 기후변화가 심화됨에 따라 가뭄으로 유발되는 피해가 증가하고 있다. 현재 국내의 가뭄 강도를 결정하기 위해 표준강수지수(Standardized Precipitation Index, SPI)를 기준으로 분류를 수행하고 있다. 현재 국내에서는 최근 6개월 동안의 누적강수량을 기준(SPI-6)으로 관심, 주의, 경계, 심각의 기상학적 가뭄의 강도를 분류하고 있다. 그러나 강수량만을 기초자료로 활용하기 때문에 가뭄 강도를 분류하는 데 한계가 있다는 문제점이 있다. 따라서 본 연구에서는 SPI에 따른 국내 기상학적 가뭄 예･경보 기준의 한계점을 극복하고자 국가가뭄정보포털(National Drought Information Portal, NDIP)에서 제공하는 비상급수 피해자료를 수집하여 가뭄의 강도를 분류하였다. 그리고 SPI의 인자인 강수량과 증발산량 산정에 사용되는 인자인 온도, 습도 등을 min-max 정규화로 지수화한 후 유전 알고리즘(Genetic Algorithm, GA) 기반으로 각 인자들에 대한 계수를 산정하였다. 비상급수에 따른 가뭄의 강도를 분류하여 종속변수로 활용하고, GA에 의한 각 기상인자들의 계수를 활용하여 새로운 가뭄 강도 분류 지수(Drought Severity Classification Index, DSCI)를 도출하고자 하였다. DSCI를 도출한 후 누적분포함수를 활용하여 분위별 경계를 강도 단계 분류 기준으로 제시하였다. 본 연구에서 제시한 DSCI를 활용하면 기존 SPI보다 가뭄 강도를 정확하게 분류할 수 있어, 재난 담당자들의 의사결정을 지원할 수 있을 것으로 판단된다.

• 농촌계획
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• 제26권2호
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• pp.51-59
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• 2020

In this study, we analyzed the characteristics of 511 agricultural districts through statistical data, and classify these districts as the vulnerable area to drought through correlation and cluster analysis. The criteria for classification was related to ground-water recharge, irrigation water demand, and water supply. As a result, 8 types of agricultural districts were extracted. For example, the type 1 indicated the high priority area for ground-water development, thus the districts which were classified as type 1 showed ground-water use was less than 80 % of maximum capacity, and irrigation water supply was only 37.5 % and 76.5 % of irrigation water demand in upland and paddy field, respectively. As a result, 44 of 511 districts were classified as type 1.36 districts (types 5-8) were areas where groundwater development is limited. The results of this study are expected to provide useful information for establishing the direction of the rural area development project in connection with the revitalization of policy of people return to rural area.

• 한국물환경학회지
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• 제22권5호
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• pp.737-747
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• 2006

Ministry of Environment (MOE) of Korea has been implementing the water quality management policy to focus on the control of organic matters (BOD and COD) for 28 years since 1978 when the water quality standards had been established. However, the government and the public have begun to recognize the necessity of creating the best water environment for people and aquatic life, and also formulating the various measures of water pollution, Consequently, MOE of Korea is establishing the basic plan of water environment management, with the vision of "Clean Water, Eco River 2015." The major targets of water environment management plan are to maintain ecosystem health and to protect water quality from various hazardous substances in water bodies. In order to achieve the major targets, it is essential to amend the water quality standards, which bring about the systematic management of various pollutants and healthy ecosystem. Introduction of the new techniques of water environment assessment is also prerequisite to maintain sustainable water environment. These can be accomplished under the consideration of following suggestions in environmental quality standards. First, several criteria should be complemented in water quality standards; they include the improvement of the current water quality classification system, the strengthening and supplement of relevant parameters considering human health in the standards, the introduction of biotic indices, and management standards on eutrophication. Secondly, it should be considered to introduce the biological water quality standards using biotic indices and the management standards for sediments. Lastly, it needs to introduce or develop an ecological status classification which could be used in the assessment of the water environment as a whole.

• 대한의용생체공학회:의공학회지
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• 제44권2호
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• pp.147-156
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• 2023

Efforts to employ smart home sensors to monitor the indoor activities of elderly single residents have been made to assess the feasibility of a safe and healthy lifestyle. However, the bathroom remains an area of blind spot. In this study, we have developed and evaluated a new edge computer device that can automatically detect water usage activities in the bathroom and record the activity log on a cloud server. Three kinds of sound as flushing, showering, and washing using wash basin generated during water usage were recorded and cut into 1-second scenes. These sound clips were then converted into a 2-dimensional image using MEL-spectrogram. Sound data augmentation techniques were adopted to obtain better learning effect from smaller number of data sets. These techniques, some of which are applied in time domain and others in frequency domain, increased the number of training data set by 30 times. A deep learning model, called CRNN, combining Convolutional Neural Network and Recurrent Neural Network was employed. The edge device was implemented using Raspberry Pi 4 and was equipped with a condenser microphone and amplifier to run the pre-trained model in real-time. The detected activities were recorded as text-based activity logs on a Firebase server. Performance was evaluated in two bathrooms for the three water usage activities, resulting in an accuracy of 96.1% and 88.2%, and F1 Score of 96.1% and 87.8%, respectively. Most of the classification errors were observed in the water sound from washing. In conclusion, this system demonstrates the potential for use in recording the activities as a lifelog of elderly single residents to a cloud server over the long-term.

• 한국물환경학회지
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• 제35권3호
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• pp.248-256
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• 2019

Most of the lakes in Korea are artificial, and their limnological characteristics are significantly different from those of natural lakes in other countries. In this study, the relationship between trophic state parameters was investigated, based on summer average data of the upper layer, in 81 lakes in Korea, 2013-2017. Compared with trends of foreign natural lakes, chlorophyll a (Chl.a) concentration was slightly lower at the same total phosphorus (TP) concentration, and transparency (Secchi depth, SD) was noticeably lower at the same Chl.a concentration. This is because of excessive allochthonous loading of non-algal material during the monsoon period, and the reduction in phosphorus availability to algal growth, by light limitation and short hydraulic residence time. Considering these characteristics, we suggested site-specific thresholds of trophic state classification for Chl.a, TP and SD, based on annual average data at the upper layer of lakes ($3-10{\mu}g\;L^{-1}$ of Chl.a measured by UNESCO method; $13-33{\mu}g\;L^{-1}$ of TP; 1.6-3.2 m of SD for mesotrophic state class, respectively). The threshold value of TP for each trophic state class, corresponded to the upper value of previously reported range, and that of SD was out of the range. We suggested applying only TP and Chl.a in assessment of trophic state of lakes in Korea, excluding SD.

• 대한원격탐사학회지
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• 제20권3호
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• pp.197-205
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• 2004

Wetlands are lands with a mixture of water, herbaceous or woody vegetation and wet soil. And linear spectral mixture analysis (LSMA) is one of the most often used methods in handling the spectral mixture problem. This study aims to test LSMA is an enhanced routine for classification of wetland land-covers in Paldang reservoir and vicinity (paldang Reservoir) using Landsat TM and ETM+ imagery. In the LSMA process, reference endmembers were driven from scatter-plots of Landsat bands 3, 4 and 5, and a series of endmember models were developed based on green vegetation (GV), soil and water endmembers which are the main indicators of wetlands. To consider phenological characteristics of Paldang Reservoir, a soil endmember was subdivided into bright and dark soil endmembers in spring and a green vegetation (GV) endmember was subdivided into GV tree and GV herbaceous endmembers in fall. We found that LSMA fractions improved the classification accuracy of the wetland land-cover. Four endmember models provided better GV and soil discrimination and the root mean squared (RMS) errors were 0.011 and 0.0039, in spring and fall respectively. Phenologically, a fall image is more appropriate to classify wetland land-cover than spring's. The classification result using 4 endmember fractions of a fall image reached 85.2 and 74.2 percent of the producer's and user's accuracy respectively. This study shows that this routine will be an useful tool for identifying and monitoring the status of wetlands in Paldang Reservoir.

• 지질공학
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• 제26권2호
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• pp.207-221
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• 2016

최근 국내 필댐 및 저수지의 노후화가 급속도로 진행되고 있으며, 이에 따른 제체의 손상이나 붕괴사고가 잇따르고 있다. 그러나 필댐의 핵심적인 차수기능을 담당하는 코어층에 대한 열화와 잠재 위해성 분류에 대한 연구는 거의 미진한 실정이다. 본 연구에서는 노후화가 진행 중인 13개 기존 코어형 필댐에 대해(준공 후 경과년수 9-52년, 댐 높이 22-67 m), 무수보링에 의한 코어층 시추 지반조사와 표준관입시험, 2D 및 3D 전기비저항탐사, 물성·역학시험을 수행하여 공학적 기반의 잠재적 위해성 유형을 국내 최초로 분류, 제시하였다. 중심코어층에 대한 무수보링 시추 지반조사 결과, 코어재 잠재 위해성 유형을 국부적 포화대, 신속한 공내수 유입, 조립질 혼재 코어재, 상대적 저 강성의 네 종류로 분류하였다. 코어형 필댐의 잠재 위해성 유형 중국부적 포화대 유형은 코어존 내 유로의 성장 및 발달에 의한 내적침식의 가능성이 존재하므로 가장 위험한 위해성으로 분류 되었으며, 코어재의 열화 등급에 따라 적절한 차수능 회복을 위한 보수보강이 필요한 것으로 판단되었다. 그 외 세 가지 위해성 유형은 즉각적인 조치보다는 지속적인 모니터링과 정기 검사의 강화가 필요할 것으로 검토되었다. 본 연구대상 댐의 분석 결과, 준공 후 경과년수와 댐 코어재의 열화 양상과는 상관성이 크게 없는 것으로 나타났다. 본 연구 결과는 코어형 필댐의 노후화에 따른 댐의 안전관리와 성능개선에 있어 유용한 자료로 활용 가능할 것으로 판단된다.

• 대한원격탐사학회지
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• 제34권4호
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• pp.671-680
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• 2018

Compared to the imagery produced by traditional satellites, PlanetScope satellite imagery has made it possible to easily capture remotely-sensed imagery every day through dozens or even hundreds of satellites on a relatively small budget. This study aimed to detect changed areas and update a land cover map using a PlanetScope image. To generate a classification map, pixel-based Random Forest (RF) classification was performed by using additional features, such as the Normalized Difference Water Index (NDWI) and the Normalized Difference Vegetation Index (NDVI). The classification result was converted to vector data and compared with the existing land cover map to estimate the changed area. To estimate the accuracy and trends of the changed area, the quantitative quality of the supervised classification result using the PlanetScope image was evaluated first. In addition, the patterns of the changed area that corresponded to the classification result were analyzed using the PlanetScope satellite image. Experimental results found that the PlanetScope image can be used to effectively to detect changed areas on large-scale land cover maps, and supervised classification results can update the changed areas.

• 한국환경과학회지
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• 제15권4호
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• pp.349-357
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• 2006

The purpose of this study is to evaluate the water pollution degree in the Mid-Nakdong River watershed regarding to landcover types using GIS method. As a result of landcover classification, rate of urban appeared highly on Daegu Metropolitan city. Also, rate of agriculture showed highly in the riparian zones of the Nakdong and Guemho River and rate of forest appeared highly in the borders of the study area. To identify the groups of watershed with similar landcover patterns using the Cluster Analysis. According to the cluster analysis, the fifty sub-watersheds were grouped in three clusters, 'Urban watershed', 'Agriculture watershed', 'Forest watershed'. The proportion of urban area in each cluster had a positive correlation with water pollution degree. Otherwise, the proportion of agriculture in the Agriculture watershed had a high positive correlation with water pollution degree. Therefore, it is necessary to estimate environmental capacity of water duality considering ecological and environmental characteristics of watershed ecosystem and expand water duality monitoring systems to small stream.

• 한국측량학회지
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• 제31권6_2호
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• pp.521-527
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• 2013

Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.