• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.4
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• pp.101-118
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• 2023

During the COVID-19 pandemic, the utilization rate of neighborhood parks and green spaces increased significantly, and the outbreak served as an opportunity to highlight the values and functions of neighborhood parks and green spaces for urban residents. This study aims to empirically analyze how citizens' movement and the use of neighborhood parks and green spaces changed before and after COVID-19 and examine the social and spatial characteristics that affected these changes. As a research method, first, people's mobility around neighborhood parks and green spaces before and after the COVID-19 pandemic were compared using signal data from telecommunication carriers. Through the analysis of changes in residence time and movement volume, the movement characteristics of citizens after COVID-19 and changes in walking-based park visits were examined. Second, the factors affecting the mobility change in neighborhood parks and green spaces were analyzed. The social and spatial characteristics that affect citizens' visits to neighborhood parks and green spaces before and after COVID-19 were examined through correlation and multiple regression analysis. Subsequently, through cluster analysis, the types of living areas for the post-COVID era were classified from the perspective of the supply and management of neighborhood parks and green spaces services, and directions for improving neighborhood parks and green spaces by type were presented. Major research findings are as follows: First, since the outbreak of COVID-19, activities within 500m of the residence have increased. The amount of stay and walking movement increased in both 2020 and 2021, which means that the need to review the quantitative standards and attractions of neighborhood parks and green spaces has increased considering the changed scope of the walking and living area. Second, the overall number of visits to neighborhood parks and green spaces by walking has increased since the outbreak of COVID-19. The number of visits to neighborhood parks and green spaces centered on the house and the workplace increased significantly. The park green policy in the post-COVID era should be promoted by discovering underprivileged areas, focusing on areas where residential, commercial, and business facilities are concentrated, and improving neighborhood parks and green services in quantitative and qualitative terms. Third, it was found that the higher the level of park green service, the higher the amount of walking movement. It is necessary to use indicators that contribute to improving citizens' actual park green services, such as walking accessibility, rather than looking at the criteria for securing green areas. Fourth, as a result of cluster analysis, five types of neighborhood parks and green spaces were derived in response to the post-COVID era. This suggests that it is necessary to consider the socioeconomic status and characteristics of living areas and the level of park green services required in future park green policies. This study has academic and policy significance in that it has laid the basis for establishing neighborhood parks and green spaces policy in response to the post-COVID era by using various analysis methodologies such as carrier signal data analysis, GIS analysis, and statistical analysis.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1195-1207
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• 2020

With the development of GeoWeb technology, 2D/3D spatial information services through the web are also has been used increasingly in the application of disaster management. This paper is suggested to construct a web-based 3D geo-spatial information mapping platform to visualize various spatial information collected at the disaster site in a web environment. This paper is presented a web-based geo-spatial information mapping service plan for the various types of 2D/3D spatial data and large-volume LiDAR point cloud data collected at the disaster accident site using HTML5/WebGL, web development standard technology and open source. Firstly, the collected disaster site survey 2D data is constructed as a spatial DB using GeoServer's WMS service and PostGIS provided an open source and rendered in a web environment. Secondly, in order to efficiently render large-capacity 3D point cloud data in a web environment, a Potree algorithm is applied to simplifies point cloud data into 2D tiles using a multi-resolution octree structure. Lastly, OpenLayers3 based 3D web mapping pilot system is developed for web visualization of 2D/3D spatial information by implementing basic and application functions for controlling and measuring 3D maps with Graphic User Interface (GUI). For the further research, it is expected that various 2D survey data and various spatial image information of a disaster site can be used for scientific investigation and analysis of disaster accidents by overlaying and visualizing them on a built web-based 3D geo-spatial information system.

• Journal of Environmental Policy
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• v.8 no.2
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• pp.1-23
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• 2009

This study applied satellite radar imagery to identify flooded areas and examined post-flooding conditions using time-series satellite radar imagery for the development of flood damage mitigation strategies. Using time-series satellite radar images, this study constructed a map delineating areas vulnerable to frequent flood damage. The extracted flooded areas were combined with reference land use maps to examine flood damage by land use type. Major landuse types with severe flood damage were agricultural and forested areas. The analysis of the damage conditions, in terms of land use, served as the basis for developing flood damage mitigation policies, in conjunction with land use planning. The policies for flood damage mitigation can be summarized as land use regulations, land use planning, and flood damage mapping. A preventive measure to minimize flood damage of properties, which regulates developing areas with high flooding potential, is highly recommended. Although this study suggested a number of policies for flood damage mitigation, they represent only a small number of possible policies useful for mitigating flood damage and other environmental problems. Based upon the results of this study, it may be concluded that satellite radar imagery has great potential in providing basic data for large-scale environmental problems such as flooding and oil spills. Nevertheless, further examinations should be conducted and the application of satellite radar imagery should be used to examine other environmental problems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.203-209
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• 2016

Digital tourism is the digital support of the tourist experience before, during and after the tourist activity[1]. The GPS-enabled mobile phones provide location-based mobile applications such as tour guide and storytelling services. In this paper, we propose the smart tour guide service platform based on GIS and develop the mobile application to provide the smart tour guide service. The proposed smart tour guide service platform consists of CMS, the multi-modal navigation system, the tour attraction content creation and management system, the tour commodity creation and management system, the smart search system, and the user terminal. The smart tour guide application supports digital tourism in the pre-tour, during tour, and post-tour using the proposed smart tour guide service platform in the popular tourist attractions in Jeju.

• Journal of the Korean Geographical Society
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• v.32 no.4
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• pp.463-478
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• 1997

This paper examines the impact of large-scale tidal flat reclamations on environment by analyzing land use change, ocean cultivation, water quality, sea biota and climate in Shiwha, Sosan and Saemankeum districts. The data used in this paper include Landsat TM images and documents related to population, industry, water quality, sea biota and climate at the time of the pre- and post-reclamation. Many times of field reclamations contribute to the creatation of newly available land for urban and industrial development, but cause environmental degradation significantly. The increase of pollution load and the change of coastal ecology, also cause some changes of climatic element such as relative humidity. As tidal flats were reduced, the area of ocean cultivation and the population of fishing industries were decreased. Conceming the sustainable development. it is necessary to carry out a careful environmental impact assessment accumulating monitoring environmental data continuously by using GIS techniques.

• Atmosphere
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• v.29 no.4
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• pp.417-427
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• 2019

The purpose of this study is to build urban canopy model (Met Office Reading Urban Surface Exchange Scheme, MORUSES) based to Unified Model (UM) by using urban building information data in Seoul, and then to compare the improving urban canopy model simulation result with that of Seoul Automatic Weather Station (AWS) observation site data. UM-MORUSES is based on building information database in London, we performed a sensitivity experiment of UM-MOURSES model using urban building information database in Seoul. Geographic Information System (GIS) analysis of 1.5 km resolution Seoul building data is applied instead of London building information data. Frontal-area index and planar-area index of Seoul are used to calculate building height. The height of the highest building in Seoul is 40m, showing high in Yeoido-gu, Gangnam-gu and Jamsil-gu areas. The street aspect ratio is high in Gangnam-gu, and the repetition rate of buildings is lower in Eunpyeong-gu and Gangbuk-gu. UM-MORUSES model is improved to consider the building geometry parameter in Seoul. It is noticed that the Root Mean Square Error (RMSE) of wind speed is decreases from 0.8 to 0.6 m s^-1 by 25 number AWS in Seoul. The surface air temperature forecast tends to underestimate in pre-improvement model, while it is improved at night time by UM-MORUSES model. This study shows that the post-improvement UM-MORUSES model can provide detailed Seoul building information data and accurate surface air temperature and wind speed in urban region.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.423-436
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• 2017

This paper presents a deep learning-based road segmentation framework from very high-resolution orthophotos. The proposed method uses Deep Convolutional Autoencoders for end-to-end mapping of orthophotos to road segmentations. In addition, a set of post-processing steps were applied to make the model outputs GIS-ready data that could be useful for various applications. The optimization of the model's parameters is explained which was conducted via grid search method. The model was trained and implemented in Keras, a high-level deep learning framework run on top of Tensorflow. The results show that the proposed model with the best-obtained hyperparameters could segment road objects from orthophotos at an average accuracy of 88.5%. The results of optimization revealed that the best optimization algorithm and activation function for the studied task are Stochastic Gradient Descent (SGD) and Exponential Linear Unit (ELU), respectively. In addition, the best numbers of convolutional filters were found to be 8 for the first and second layers and 128 for the third and fourth layers of the proposed network architecture. Moreover, the analysis on the time complexity of the model showed that the model could be trained in 4 hours and 50 minutes on 1024 high-resolution images of size $106{\times}106pixels$, and segment road objects from similar size and resolution images in around 14 minutes. The results show that the deep learning models such as Convolutional Autoencoders could be a best alternative to traditional machine learning models for road segmentation from aerial photographs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.14 no.1
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• pp.97-110
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• 1996

The purpose of this study is to evaluate the urban land used by the Urban Land Use Information System (ULIS) which can supply the micro-level land usc information for the understanding of micro-level urban spatial structure and district-level planning and managements(such as urban design, redevelopment planning and district-level transportation planning, etc.). The study evaluates the current situation of urban land use database and suggests the prototype of urban land use database using GIS. The planning and management of post-modern city which has characterized by diversity and the mixture of land use, need more detail and quantitative information about land use. Recent redevelopment and reconstruction of existing physical condition are increasing the density of activity. It raises urban problems such as the shortage of infrastructure and traffic congestion, etc. In this process we need to construct information system which monitors current land use situation.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.4
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• pp.41-48
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• 2008

Currently used 3D models, which are mostly focused on visualization of 3D objects and lack topological structure, have limitation in being used for 3D spatial analyses and applications. However, implementing a full topology for the indoor spatial objects is less practical due to the increase of complexity and computation time. This study suggests an alternative method to build a 3D indoor model with less complexity using a spatial DBMS. Storing spatial and nonspatial information of indoor spaces in DB tables enables faster queries, computation and analyses. Also it is possible to display them in 2D or 3D using the queried information. This study suggests a 2D-3D hybrid data model, which combines the 2D topology constructed from CAD floor plans and stored in a spatial DBMS and the 3D visualization functionality. This study showed the process to build the proposed model in a spatial DBMS and use spatial functions and queries to visualize in 2D and 3D. And, then, as an example application, it illustrated the process to build an indoor evacuation simulator.

• Journal of the Korean Society of School Health
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• v.29 no.3
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• pp.286-298
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• 2016

Purpose: The aim of this study was to identify the effects of community mapping based on volunteered Geographic Information System on smoking prevention among female middle school students. Methods: This study used a triangulation method which integrated quantitative data from a "pre-post" study on a nonequivalent control group and qualitative data from focus group interviews. Data was collected from 4 August 2015 to 10 January 2016. The experimental group (n=24) participated in community mapping along with education on smoking prevention and the control group (n=28) participated only in routine education. Both groups were measured on their knowledge and attitude related to smoking prevention through self-report questionnaires. The quantitative data was analyzed by descriptive statistics, $x^2$ analysis, and t-test using SPSS 23.0. The qualitative data was collected through focus group interviews to investigate the social-environmental effect of smoking prevention. Results: Knowledge related to smoking prevention was significantly higher (t=2.591, p=.013) in the experimental group than the control group. But attitude related to smoking prevention did not show significant differences between the two groups. When asked about their experiences of the community mapping program, it turned out to be a process where they could learn practical knowledge related to smoking prevention and experience their individual practices manifested as collective intelligence while working together with community members. The study found that community mapping had an effect on smoking prevention from a social and environmental aspect. Conclusion: To be more effective, school education on smoking prevention should be provided in connection with the community. It is also desirable to provide an opportunity where adolescents can experience discovering and solving practical problems along with their own community.