• Title/Summary/Keyword: Spatial Density

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The Effects of Retail Crowding on Consumer Emotions and Shopping Behaviors (점포의 혼잡성이 소비자 감정과 쇼핑행동에 미치는 영향)

  • 박경애
    • Journal of the Korean Society of Clothing and Textiles
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    • v.27 no.2
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    • pp.261-269
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    • 2003
  • This study examined the effects of store density levels on consumers'crowding perception and the effects of perceived retail crowding on consumer emotions and in turn shopping behavior. In addition, the study investigated the effects of perceived price value and store type on the segmented dimensions of perceived retail crowding. Results of an experimental test with 3 density levels and 2 store types confirmed the effects of density on social crowding and spatial crowding. While social crowding positively affected arousal, spatial crowding negatively did pleasure which in turn affected approach-avoidance behavior. Though two store types showed the same pattern in such relationships, the effect of perceived price value on retail crowding was different by store type.

A Study on the Shape Finding of Cable-Net Structures Introducing General Inverse Matrix (일반역행열(一般逆行列)을 이용(利用)한 케이블네트 구조물(構造物)의 형상결정에 관한 연구)

  • Sur, Sam-Uel;Lee, Jang-Bok
    • Journal of Korean Association for Spatial Structures
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    • v.2 no.1 s.3
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    • pp.75-84
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    • 2002
  • In this study, the 'force density method' for shape finding of cable net structures is presented. This concept is based on the force-length ratios or force densities which are defined for each branch of the net structures. This method renders a simple linear 'analytical form finding' possible. If the free choice of the force densities is restricted by further condition, the linear method is extended to a nonlinear one. The nonlinear one can be applied to the detailed computation of networks. In this paper, the general inverse matrix is introduced to solve the nonlinear equilibrium equation including Jacobian matrix which is rectangular matrix. Several examples for linear and nonlinear analysis applied additional constraints are presented. It is shown that the force density method is suitable for form finding of cable net and the general inverse matrix can be applied to solve the nonlinear equation without Lagrangian factors.

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Identification of Visitation Density and Critical Management Area Regarding Marine Spatial Planning: Applying Social Big Data (해양공간계획 수립을 위한 방문밀집도 및 중점관리지역 규명: 소셜 빅데이터를 활용하여)

  • Kim, Yoonjung;Kim, Choongki;Kim, Gangsun
    • Journal of Environmental Impact Assessment
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    • v.29 no.2
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    • pp.122-131
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    • 2020
  • Marine Spatial Planning is an emerging strategy that promoting sustainable development at coastal and marine areas based on the concept of ecosystem services. Regarding its methodology, usage rate of resources and its impact should be considered in the process of spatial planning. Particularly, considering the rapid increase of coastal tourism, visitation pattern is required to be identified across coastal areas. However, actions to quantify visitation pattern have been limited due to its required high cost and labor for conducting extensive field-study. In this regard, this study aimed to pose the usage of social big data in Marine Spatial Planning to identify spatial visitation density and critical management zone throughout coastal areas. We suggested the usage of GPS information from Flickr and Twitter, and evaluated the critical management zone by applying spatial statistics and density analysis. This study's results clearly showed the coastal areas having relatively high visitors in the southern sea of South Korea. Applied Flickr and Twitter information showed high correlation with field data, when proxy excluding over-estimation was applied and appropriate grid-scale was identified in assessment approach. Overall, this study offers insights to use social big data in Marine Spatial Planning for reflecting size and usage rate of coastal tourism, which can be used to designate conservation area and critical zones forintensive management to promote constant supply of cultural services.

Quantitative Precipitation Estimation using High Density Rain Gauge Network in Seoul Area (고밀도 지상강우관측망을 활용한 서울지역 정량적 실황강우장 산정)

  • Yoon, Seong-sim;Lee, Byongju;Choi, Youngjean
    • Atmosphere
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    • v.25 no.2
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    • pp.283-294
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    • 2015
  • For urban flash flood simulation, we need the higher resolution radar rainfall than radar rainfall of KMA, which has 10 min time and 1km spatial resolution, because the area of subbasins is almost below $1km^2$. Moreover, we have to secure the high quantitative accuracy for considering the urban hydrological model that is sensitive to rainfall input. In this study, we developed the quantitative precipitation estimation (QPE), which has 250 m spatial resolution and high accuracy using KMA AWS and SK Planet stations with Mt. Gwangdeok radar data in Seoul area. As the results, the rainfall field using KMA AWS (QPE1) is showed high smoothing effect and the rainfall field using Mt. Gwangdeok radar is lower estimated than other rainfall fields. The rainfall field using KMA AWS and SK Planet (QPE2) and conditional merged rainfall field (QPE4) has high quantitative accuracy. In addition, they have small smoothed area and well displayed the spatial variation of rainfall distribution. In particular, the quantitative accuracy of QPE4 is slightly less than QPE2, but it has been simulated well the non-homogeneity of the spatial distribution of rainfall.

Spatial Distribution of the Levels of Water Pollutants in Han River (수질오염도의 공간적 분포 변화 분석 : 한강 유역을 대상으로)

  • Kim, Kwang-Soo;Kwon, Oh-Sang
    • Environmental and Resource Economics Review
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    • v.18 no.1
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    • pp.105-138
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    • 2009
  • This study investigates the spatial distribution of the degree of water pollutants in Han River using data obtained by the water pollution observation stations. This study estimates a non -parametric kernel density function for each water pollutants, and tests a significant difference between two estimated distribution functions. Next, Generalized Entropy inequality indices are evaluated and this research tests difference of inequality indices between two years using bootstrapping method. Lastly in a dynamic of view, it is analyzed that there are significant changes in the ranking of water pollution level. Estimation results show that the degree of inequality in spatial distribution of water pollution tends to be stable or decreasing for last 15 years in a great part of water pollutants, and ranking of water pollution level hardly changes in Han River.

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Population persistence of the perennial kelp Eisenia arborea varies across local spatial scales

  • Gossard, Daniel J.;Steller, Diana L.
    • ALGAE
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    • v.37 no.1
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    • pp.63-74
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    • 2022
  • Perennial stipitate kelps are globally distributed and individual species can inhabit broad latitudinal ranges, expressing notably longevous persistence. Despite the foundational role kelps provide to their communities, little is known about the variability in persistence of the stipitate kelps at local spatial scales. We studied the population persistence of Eisenia arborea, a heat- and wave force-tolerant perennial stipitate kelp with a distributional range extending from British Columbia to south of the range limit of all other northeast Pacific kelps, in Baja California Sur, Mexico. Persistence characteristics for E. arborea among sites were compared and used to test the hypothesis that stand persistence varied at local spatial scales around Isla Natividad, a Pacific island off the Baja California peninsula with documented spatiotemporal environmental heterogeneity. Collected individuals around the island were "aged" using the previously validated age estimation technique of counting annual cortical dark rings. After detecting no significant differences among sites in the covariation between estimated ages for collected individuals and stipe length, we utilized in-situ population-level stipe length measurements to more rapidly predict age structures within six stands around the island. Predicted age structures, and associated stand densities, revealed persistence characteristics and density varied at local scales and a strong positive relationship existed between stand density and stand mean and maximum ages. We speculate that stands responded differently to deterministic influences (e.g., the 2014-2016 marine heatwave and / or competition with Macrocystis) resulting in heterogenous local persistence of this foundation species.

Factors influencing the spatial distribution of soil organic carbon storage in South Korea

  • May Thi Tuyet Do;Min Ho Yeon;Young Hun Kim;Gi Ha Lee
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.167-167
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    • 2023
  • Soil organic carbon (SOC) is a critical component of soil health and is crucial in mitigating climate change by sequestering carbon from the atmosphere. Accurate estimation of SOC storage is essential for understanding SOC dynamics and developing effective soil management strategies. This study aimed to investigate the factors influencing the spatial distribution of SOC storage in South Korea, using bulk density (BD) prediction to estimate SOC stock. The study utilized data from 393 soil series collected from various land uses across South Korea established by Korea Rural Development Administration from 1968-1999. The samples were analyzed for soil properties such as soil texture, pH, and BD, and SOC stock was estimated using a predictive model based on BD. The average SOC stock in South Korea at 30 cm topsoil was 49.1 Mg/ha. The study results revealed that soil texture and land use were the most significant factors influencing the spatial distribution of SOC storage in South Korea. Forested areas had significantly higher SOC storage than other land use types. Climate variables such as temperature and precipitation had a relative influence on SOC storage. The findings of this study provide valuable insights into the factors influencing the spatial distribution of SOC storage in South Korea.

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Defining of Trade Area using Spatial Data Mining Technique in Business GIS (비지니스 GIS에서 공간 데이터마이닝(Spatial Data Mining)기법을 이용한 상권추출)

  • 이병길
    • Spatial Information Research
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    • v.11 no.2
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    • pp.171-184
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    • 2003
  • Lots of application systems are developed for applying business GIS in marketing or strategic planning of the company, recently. Almost of the systems require statistics for some areas(trade areas or sales areas) as the important information of decision support. As far as now, trade areas are defined for individual stores using know-how of the specialists, but there is no well-defined method for defining of trade areas of the specific business domains or trade areas of the customers. In this study, we have applied the spatial data mining methods to the point features in GIS, evaluated the results of each methods, and discussed the feasibility of defining of trade areas. From the results of this study, we have concluded that the defining of trade areas from point features, such as franchisees of credit card company or memberships of retail chain store, and that the DENCLUE(DENsity-based CLUstEring) method is the best suitable spatial data mining algorithm for this purpose.

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A probabilistic nearest neighbor filter incorporating numbers of validated measurements

  • Sang J. Shin;Song, Taek-Lyul;Ahn, Jo-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.82.1-82
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    • 2002
  • $\textbullet$ Nearest neighbor filter $\textbullet$ Probabilistic nearest neighbor filter $\textbullet$ Probabilistic nearest neighbor filter incorporating numbers of validated measurements $\textbullet$ Probability density function of the NDS $\textbullet$ Simulation results in a clutter environment to verify the performances $\textbullet$ Sensitivity analysis for the unknown spatial clutter density

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Geographically Weighted Regression on the Characteristics of Land Use and Spatial Patterns of Floating Population in Seoul City (서울시 유동인구 분포의 공간 패턴과 토지이용 특성에 관한 지리가중 회귀분석)

  • Yun, Jeong Mi;Choi, Don Jeong
    • Journal of Korean Society for Geospatial Information Science
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    • v.23 no.3
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    • pp.77-84
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    • 2015
  • The key objective of this research is to review the effectiveness of spatial regression to identify the influencing factors of spatial distribution patterns of floating population. To this end, global and local spatial autocorrelation test were performed using seoul floating population survey(2014) data. The result of Moran's I and Getis-Ord $Gi^*$ as used in the analysis derived spatial heterogeneity and spatial similarities of floating population patterns in a statistically significant range. Accordingly, Geographically Weighted Regression was applied to identify the relationship between land use attributes and population floating. Urbanization area, green tract of land of micro land cover data were aggregated in to $400m{\times}400m$ grid boundary of Seoul. Additionally public transportation variables such as intersection density transit accessibility, road density and pedestrian passage density were adopted as transit environmental factors. As a result, the GWR model derived more improved results than Ordinary Least Square(OLS) regression model. Furthermore, the spatial variation of applied local effect of independent variables for the floating population distributions.