• Title/Summary/Keyword: urban engineering

Search Result 5,977, Processing Time 0.036 seconds

Structural damage distribution induced by Wenchuan Earthquake on 12th May, 2008

  • Jia, Junfeng;Song, Nianhua;Xu, Zigang;He, Zizhao;Bai, Yulei
    • Earthquakes and Structures
    • /
    • v.9 no.1
    • /
    • pp.93-109
    • /
    • 2015
  • Based on the reconnaissance of buildings in Dujiangyan City during 2008 Wenchuan earthquake, China, structural damage characteristics and the spatial distribution of structural damage are investigated, and the possible reasons for the extraordinary features are discussed with consideration of the influence of urban historical evolution and spatial variation of earthquake motions. Firstly, the urban plan and typical characteristics of structural seismic damage are briefly presented and summarized. Spatial distribution of structural damage is then comparatively analyzed by classifying all surveyed buildings in accordance with different construction age, considering the influence of seismic design code on urban buildings. Finally, the influences of evolution of seismic design code, topographic condition, local site and distance from fault rupture on spatial distribution of structural damage are comprehensively discussed. It is concluded that spatial variation of earthquake motions, resulting from topography, local site effect and fault rupture, are very important factor leading to the extraordinary spatial distribution of building damage except the evolution of seismic design codes. It is necessary that the spatial distribution of earthquake motions should be considered in seismic design of structures located in complicated topography area and near active faults.

Deep learning model in water-environment field (수 환경 분야에서의 딥러닝 모델 적용사례)

  • Pyo, Jongcheol;Park, Sanghun;Cho, Kyung-Hwa;Baek, Sang-Soo
    • Journal of Korean Society of Water and Wastewater
    • /
    • v.34 no.6
    • /
    • pp.481-493
    • /
    • 2020
  • Deep learning models, which imitate the function of human brain, have drawn attention from many engineering fields (mechanical, agricultural, and computer engineering etc). The major advantages of deep learning in engineering fields can be summarized by objects detection, classification, and time-series prediction. As well, it has been applied into environmental science and engineering fields. Here, we compiled our previous attempts to apply deep learning models in water-environment field and presented the future opportunities.

Analyzing the correlation between urban forestry and surface temperature using Landsat TM data

  • Jo, Myung-Hee;Kim, Sung-Jae;Lee, Kwang-Jae
    • Proceedings of the KSRS Conference
    • /
    • 2003.11a
    • /
    • pp.905-907
    • /
    • 2003
  • In this study, the correlation between the heat island effect and the vegetation in Deagu Korea was performed through using Landsat TM data. the island effect, presents high temperature on air like island, is connected with correlation between the surface temperature and the temperature on the air. In this study, surface temperature was analyzed by detecting the change of urban forestry with remote sensing using the vegetation vitality statistics reference (ratio change of the Park greens in Daegu) the heat island effect not only brings the environment pollution but also brings serious problem such as the destruction of ecosystem to city as a whole. Jeff Luvall has studied to restrain the heat island effect by making urban forestry. Even though Daegu had been the serious high temperature urban area the current temperature of Daegu has been dropped. The correlation between the heat island effect and the vegetation index was analyzed by using satellite images.

  • PDF

Regional Traffic Accident Model of Elderly Drivers based on Urban Decline Index (도시쇠퇴 지표를 적용한 지역별 고령운전자 교통사고 영향 분석)

  • Park, Na Young;Park, Byung Ho
    • Journal of the Korean Society of Safety
    • /
    • v.32 no.6
    • /
    • pp.137-142
    • /
    • 2017
  • This study deals with the relation between traffic accident and urban decline. The purpose of this study is to develop the regional accident models of elderly drivers. In order to develop the count data models, 2009-2015 traffic accident data from TAAS(traffic accident analysis system) and urban decline data from urban regeneration information system are collected. The main results are as follows. First, the null hypothesis that there is no difference in the accident number between elderly and non-elderly drivers is rejected. Second, 8 accident models which are all statistically significant have been developed. Finally, common variables between elderly and non-elderly are ratio of elderly people, elderly person living alone/1,000 persons and wholesale/retail employments/1,000 persons. This study could be expected to give many implications to making regional accident reduction policy.

Problem Analysis Considering Property of Urban Redevelopment (도시재생사업의 특성을 고려한 문제점 분석)

  • Kang, Hyun-Koo;Yu, Jung-Ho;Kim, Chang-Duk
    • Proceedings of the Korean Institute Of Construction Engineering and Management
    • /
    • 2008.11a
    • /
    • pp.531-535
    • /
    • 2008
  • Project management of Urban Redevelopment that including a various projects is widely different with general project management. For that purpose, this research would offer to contribute the properties of urban redevelopment the solution for successful urban redevelopment. For offering this solution, this research analyzed the properties of urban redevelopment. The study is to analyze the problem of current urban redevelopment that be discrepant the changing paradigm.

  • PDF

Monitoring urban growth in Metro Manila using multitemporal satellite images

  • Vinluan, Randy John N.;Quiblat, Carla;Batadlan, Beata;Asilo, Sonia;Sontillanosa, Rosalyn;Pereira, Rosalyn;Macapinlac, Oliver;Menguito, Mon Pierre
    • Proceedings of the KSRS Conference
    • /
    • 2003.11a
    • /
    • pp.378-380
    • /
    • 2003
  • One of the most common forms of land use change is urbanization. Fortunately, the temporal revisit capacity of remote sensing satellites and their multispectral imaging capability make it possible to monitor this process. Using two Landsat images taken in 1972 and 1989, and one SPOT image taken in 2000, urban growth in Metro Manila is monitored. The extent of urbanization in Metro Manila increased from about 39 percent in 1972 to about 74 percent in 2000, although a slowing of growth was observed in the last decade due to decreasing areas for development. Most cities and municipalities in Metro Manila exhibited urban growth rates higher than the metropolitan average. The drivers and environmental consequences of urban growth were determined as well as the relationship of the extent of urbanization with some socio-economic and environmental variables.

  • PDF