• Title/Summary/Keyword: urban classification

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Development of Mapping Method for Liquefaction Hazard in Moderate Seismic Region Considering the Uncertainty of Big Site Investigation Data (빅데이터 지반정보의 불확실성을 고려한 중진지역에서의 액상화 위험도 작성기법 개발)

  • Kwak, Minjung;Ku, Taijin;Choi, Jaesoon
    • Journal of the Korean GEO-environmental Society
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    • v.16 no.1
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    • pp.17-27
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    • 2015
  • Recently, Korean government has tried out to set up earthquake hazards prevention system. In the system, several geotechnical hazard maps including liquefaction hazard map and landslide hazard map for the whole country have drawn to consider the domestic seismic characteristics. To draw the macro liquefaction hazard map, big data of site investigations in metropolitan areas and provincial areas has to be verified for its application. In this research, we carried out site response analyses using 522 borehole site investigation data in S city during a desirable earthquake. The soil classification was separately compared to shear wave velocity considering the uncertainty of site investigation data. Probability distribution and statistical analysis for the results of site response analyses was applied to the feasibility study. Finally, we suggest a new site amplification coefficient, hereby presented with the similar results of liquefaction hazard mapping using the calculated liquefaction potential index by the site response analyses. Above-mentioned study will be expected to help to follow research and draw liquefaction hazard map in moderate seismic region.

Regional Variation and Discharge Characteristics of Stream Water Quality and Heavy Metals Around the Shihwa Lake Basin (시화호 유역 하천수 일반수질 및 중금속의 변화 및 유출 특성 연구)

  • Jeong, Hyeryeong;Kim, Kyung-Tae;Kim, Eun-Soo;Lee, Seung-Yong;Ra, Kongtae
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.20 no.2
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    • pp.76-83
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    • 2017
  • In order to investigate the characteristics of water quality and heavy metals in Shihwa Lake, concentration comparisons according to land use types and mass discharge through streams were carried out. Based on classification for streams according to land use types, the concentration of DO, SS, POC, $NO_3$ and Chl-a showed higher concentrations in agricultural areas than in industrial and urban areas. However, COD, DIN, DIP, TN, TP, DOC, TOC and heavy metal concentrations showed relatively high values in industrial areas. The concentrations of water qualities and heavy metals were relatively high in March to May and the concentration decreased in summer seasons (July-August). The averages of stream discharges of water qualities were 1,172 kg/d for SS, 151 kg/d for TN, 11.1 kg/d for TP and 389 kg/d for TOC, respectively. The agricultural area, Jangjunbo(S8), accounted for 47.5%(TP)~75.1%(SS) in the total stream discharges. Cu, Zn and Cd in stream waters were found to be more than 92% of the total discharges in industrial area, showing descending order of Zn>Cu>Ni>Pb>Co>Cd.

A Study on the Classification of Transportation Connections in Seoul Subway Adjacent Area Using Portfolio Analysis (Portfolio분석을 이용한 서울시 역세권 지하철 연계수단간 유형분류 연구 - 서울시 25개 행정구역을 중심으로 -)

  • Kim, Tae-Ho;Park, Jun-Tae;Son, Sang-Ho;Park, Je-Jin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.35 no.6
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    • pp.1329-1338
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    • 2015
  • This article aims to develop model for the right policy Tools available from the cause analysis regarding the regional differences of subway modal split in Seoul metropolitan area. This allows two major factors of the most influential subway modal split to be proved and Portfolio Analysis is conducted. The results are as follows. Firstly, the two primary factors affecting subway modal split were shown as subway adjacent area and local line bus. It signifies that expansion of subway adjacent area, establishing the number of the subway stations and increase of local line bus are required in order to improve a diminishing subway modal split. Following that, pattern of the improvement to strengthen better subway connections are classified according to the two areas which are Concentration Area of Improvement in Subway Station Area (CAISSA) and Concentration Area of Improvement in Local Bus (CAILB). Our study revealed that Ganbukgu, Seodaemungu, Geumcheongu, and Gwanakgu were selected as the area of CAILB and Songpagu, and Junggu were selected as the area of CAISSA. As all things are considered, transportation policy makers should be taken into account in the two main factors driven by our study according to types in order to enhance the future subway share proportion.

Development of Thermal Comfort Evaluation Map by the Land Cover in Yeongnam Region (영남지역의 토지피복에 따른 열쾌적성평가도 구축)

  • Kang, Dong-Hyun;Choi, Chul-Hyun;Jung, Sung-Gwan
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.2
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    • pp.136-155
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    • 2014
  • The purpose of this study is to analyze the thermal comfort in Yeongnam area using climatic data and GIS data in order to determine regions necessary to improve thermal environment policies. The results of the calculated PET show that Daegu city is high and Bonghwa-gun is low compared to other regions. PET was compared with the typical classification according to regional characteristics. As a result, PET value of rural areas such as Changnyeong-gun, Haman-gun and Goryeong-gun was high but Green space was too low compared to other rural areas. Yeongnam area was classified according to the value of PET using cluster analysis. As a result, more low grade areas show that green space ratio was low and facility area was high. It is determined that there is a relationship between thermal comfort and land cover. The thermal comfort evaluation map in Yeongnam area will be useful for urban planning in order to establish a sustainable city in climate change.

Development of Landslide-Risk Prediction Model thorough Database Construction (데이터베이스 구축을 통한 산사태 위험도 예측식 개발)

  • Lee, Seung-Woo;Kim, Gi-Hong;Yune, Chan-Young;Ryu, Han-Joong;Hong, Seong-Jae
    • Journal of the Korean Geotechnical Society
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    • v.28 no.4
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    • pp.23-33
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    • 2012
  • Recently, landslide disasters caused by severe rain storms and typhoons have been frequently reported. Due to the geomorphologic characteristics of Korea, considerable portion of urban area and infrastructures such as road and railway have been constructed near mountains. These infrastructures may encounter the risk of landslide and debris flow. It is important to evaluate the highly risky locations of landslide and to prepare measures for the protection of landslide in the process of construction planning. In this study, a landslide-risk prediction equation is proposed based on the statistical analysis of 423 landslide data set obtained from field surveys, disaster reports on national road, and digital maps of landslide area. Each dataset includes geomorphologic characteristics, soil properties, rainfall information, forest properties and hazard history. The comparison between the result of proposed equation and actual occurrence of landslide shows 92 percent in the accuracy of classification. Since the input for the equation can be provided within short period and low cost, and the results of equation can be easily incorporated with hazard map, the proposed equation can be effectively utilized in the analysis of landslide-risk for large mountainous area.

A Study on the Applicability of Deep Learning Algorithm for Detection and Resolving of Occlusion Area (영상 폐색영역 검출 및 해결을 위한 딥러닝 알고리즘 적용 가능성 연구)

  • Bae, Kyoung-Ho;Park, Hong-Gi
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.11
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    • pp.305-313
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    • 2019
  • Recently, spatial information is being constructed actively based on the images obtained by drones. Because occlusion areas occur due to buildings as well as many obstacles, such as trees, pedestrians, and banners in the urban areas, an efficient way to resolve the problem is necessary. Instead of the traditional way, which replaces the occlusion area with other images obtained at different positions, various models based on deep learning were examined and compared. A comparison of a type of feature descriptor, HOG, to the machine learning-based SVM, deep learning-based DNN, CNN, and RNN showed that the CNN is used broadly to detect and classify objects. Until now, many studies have focused on the development and application of models so that it is impossible to select an optimal model. On the other hand, the upgrade of a deep learning-based detection and classification technique is expected because many researchers have attempted to upgrade the accuracy of the model as well as reduce the computation time. In that case, the procedures for generating spatial information will be changed to detect the occlusion area and replace it with simulated images automatically, and the efficiency of time, cost, and workforce will also be improved.

Characteristics of MODIS land-cover data sets over Northeast Asia for the recent 12 years(2001-2012) (동북아시아 지역에서의 최근 12년간 (2001-2012) MODIS 토지피복 분류 자료의 특성)

  • Park, Ji-Yeol;Suh, Myoung-Seok
    • Korean Journal of Remote Sensing
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    • v.30 no.4
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    • pp.511-524
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    • 2014
  • In this study, we investigated the statistical occupations and interannual variations of land cover types over Northeast Asian region using the 12 years (2001-2012) MODerate Resolution Imaging Spectroradiometer(MODIS) land cover data sets. The spatial resolution and land cover types of MODIS land cover data sets are 500 m and 17, respectively. The 12-year average shows that more than 80% of the analysis region is covered by only 3 types of land cover, cropland (36.96%), grasslands (23.14%) and mixed forests (22.97%). Whereas, only minor portion is covered by cropland/natural vegetation mosaics (6.09%), deciduous broadleaf forests (4.26%), urban and built-up (2.46%) and savannas (1.54%). Although sampling period is small, the regression analysis showed that the occupations of evergreen needleleaf forests, deciduous broadleaf forests and mixed forests are increasing but the occupations of woody savannas and savannas are decreasing. In general, the pixels where the land cover types are classified differently with year are amount to more than 10%. And the interannual variations in the occupations of land cover types are most prominent in cropland (1.41%), mixed forests (0.82%) and grasslands (0.73%). In addition, the percentage of pixels classified as 1 type for 12 years is only 57% and the other pixels are classified as more than 2 types, even 9 types. The annual changes in the classification of land cover types are mainly occurred at the almost entire region, except for the eastern and northwestern parts of China, where the single type of land cover located. When we take into consider the time scale needed for the land cover changes, the results indicate that the MODIS land cover data sets over the Northeast Asian region should be used with caution.

Sewer CCTV Inspection Prioritization Based on Risk Assessment (위험도 기반의 하수관로 CCTV 조사 우선순위 결정 연구)

  • Son, Jooyoung;Lee, Jaehyun;Oh, Jeill
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.37 no.3
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    • pp.585-592
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    • 2017
  • Most sewer lines buried in the city are likely to be collapsed due to serious aging. Also, due to the high concentration of development and high population density and traffic, the collapse of the sewer will cause enormous social and economic damage. Therefore, proactive maintenance is required to prevent accidents caused by deteriorated sewer pipe. In order to utilize limited budget effectively, risk-based prioritization methods should be proposed that simultaneously consider the consequence of failure and the probability of failure. In this study, the method of risk-based prioritization of sewer was examined by reviewing various cases of overseas studies and applied to the urban sub-catchment. First, the impact factors that can be secured through the sewer GIS DB in Seoul were derived, and the weight, sub-criteria, and impact score of each impact factor were determined and the consequence of failure was calculated by weight sum method. In addition, the probability of failure was calculated by dividing the service life by the estimated useful life, and the consequence of failure and the probability of failure were classified into five grades by the Jenks natural breaks classification method. The prioritization method was applied to sub-catchment in the Seoul to derive a risk matrix and a risk grade. As a result, 26% of all subjects were selected as the inspection priority subjects with 4-5 risk grade. Therefore, using the risk-based CCTV prioritization methodology, it will be possible to systematically determine the objects that need investigation first.

Development of Vehicle Queue Length Estimation Model Using Deep Learning (딥러닝을 활용한 차량대기길이 추정모형 개발)

  • Lee, Yong-Ju;Hwang, Jae-Seong;Kim, Soo-Hee;Lee, Choul-Ki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.2
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    • pp.39-57
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    • 2018
  • The purpose of this study was to construct an artificial intelligence model that learns and estimates the relationship between vehicle queue length and link travel time in urban areas. The vehicle queue length estimation model is modeled by three models. First of all, classify whether vehicle queue is a link overflow and estimate the vehicle queue length in the link overflow and non-overflow situations. Deep learning model is implemented as Tensorflow. All models are based DNN structure, and network structure which shows minimum error after learning and testing is selected by diversifying hidden layer and node number. The accuracy of the vehicle queue link overflow classification model was 98%, and the error of the vehicle queue estimation model in case of non-overflow and overflow situation was less than 15% and less than 5%, respectively. The average error per link was about 12%. Compared with the detecting data-based method, the error was reduced by about 39%.

Temporal and Spatial Analysis of Non-biodegradable Organic Pollutants in the Geumho River System (금호강 수계 난분해성 유기오염물질에 대한 시·공간적 특성 분석)

  • Jung, Kang-Young;Ahn, Jung-Min;Lee, Kyung-Lak;Lee, In-Jung;Yu, Jae-Jeong;Cheon, Se-Uk;Kim, Kyo-Sik;Han, Kun-Yeun
    • Journal of Environmental Science International
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    • v.24 no.11
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    • pp.1343-1362
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    • 2015
  • As a result of analysis based on the observed data for BOD, COD and TOC in order to manage non-biodegradable organics in the Geumho River, COD/BOD ratio was analyzed as the occupying predominance proportion. In this study, the classification(changes in water quality measurement : increase, equal, decrease) and measurement of BOD and COD were analyzed for trends over the past 10 years from 2005 to 2014 in the Geumho River. The Geumho River is expected to need non-biodegradable organics management because BOD was found to be reduced 61.1% and COD was found to be increased 50%. As a result of the analysis of land use, the Geumho-A is a unit watershed area of $921.13km^2$, which is the most common area that is occupied by forests. The Geumho-B is a unit watershed area of $436.8km^2$, which is the area that is highest occupied by agriculture and grass of 24.84%. The Geumho-C is a unit watershed area of $704.56km^2$ accounted for 40.29% of the entire watershed, which is the area that is occupied by urban of 15.12%. Load of non-biodegradable organics, which is not easy biodegradable according to the discharge, appeared to be increased because flow coefficient of COD and TOC at the Geumho-B were estimated larger than 1 value. The management of non-point sources of agricultural land is required because the Geumho-B watershed area occupied by the high proportion of agriculture and field. In this segment it showed to increase the organics that biodegradation is difficult because the ratio of BOD and TOC was decreased rapidly from GR7 to GR8. Thus, countermeasures will be required for this.