• Title/Summary/Keyword: spatial distribution analysis

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Estimating the Population Size and Spatial Distribution of Three Scarites Species (Carabidae) in Sohwang Coastal Sand Dune Habitats, Boryeong, Korea

  • Do Sung Kim;Hyun Jung Kim
    • Proceedings of the National Institute of Ecology of the Republic of Korea
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    • v.4 no.1
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    • pp.1-8
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    • 2023
  • In this study, we aimed to quantify the population size and spatial distribution of three predatory Scarites species in coastal sand dunes. In June and August 2014, 252 pitfall traps were utilized to conduct a trapping web analysis at three distinct sites with varying vegetation dominance values. Scarites sulcatus had the largest estimated population in a 10 m2 area with a habitat density of 36.6 in a Vitex rotundifolia community area (site B) in the June survey. In contrast, Scarites aterrimus had the largest population size with a habitat density of 2.9 in a Calystegia soldanella community area (site A) in the August survey. Spatial distribution analysis revealed that S. sulcatus dominated the Vitex rotundifolia community without preference for a particular site, whereas S. aterrimus and Scarites terricola pacificus were primarily observed on the beach. The results indicated that the three Scarites species in the Sohwang coastal sand dune region exhibited differences in their spatial and temporal distributions in the coastal dune ecosystem in order to avoid competition and predation. In conclusion, our findings can be utilized to estimate the population density of the genus Scarites on the Korean Peninsula. The outcomes of this study will contribute to estimating insect population densities on the Korean Peninsula and developing investigative assessment methodologies.

Spatial Analysis Methods for Asbestos Exposure Research (석면노출연구를 위한 공간분석기법)

  • Kim, Ju-Young;Kang, Dong-Mug
    • Journal of Environmental Health Sciences
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    • v.38 no.5
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    • pp.369-379
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    • 2012
  • Objectives: Spatial analysis is useful for understanding complicated causal relationships. This paper focuses trends and appling methods for spatial analysis associated with environmental asbestos exposure. Methods: Literature review and reflection of experience of authors were conducted to know academic background of spatial analysis, appling methods on epidemiology and asbestos exposure. Results: Spatial analysis based on spatial autocorrelation provides a variety of methods through which to conduct mapping, cluster analysis, diffusion, interpolation, and identification. Cause of disease occurrence can be investigated through spatial analysis. Appropriate methods can be applied according to contagiousness and continuity. Spatial analysis for asbestos exposure source is needed to study asbestos related diseases. Although a great amount of research has used spatial analysis to study exposure assessment and distribution of disease occurrence, these studies tend to focus on the construction of a thematic map without different forms of analysis. Recently, spatial analysis has been advanced by merging with web tools, mobile computing, statistical packages, social network analysis, and big data. Conclusions: Because the trend in spatial analysis has evolved from simple marking into a variety of forms of analyses, environmental researchers including asbestos exposure study are required to be aware of recent trends.

Solution to Decrease Spatial Dose Rate in Laboratory of Nuclear Medicine through System Improvement (시스템 개선을 통한 핵의학 검사실의 공간 선량률 감소방안)

  • Moon, Jae-Seung;Shin, Min-Yong;Ahn, Seong-Cheol;Yoo, Mun-Gon;Kim, Su-Geun
    • Quality Improvement in Health Care
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    • v.20 no.1
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    • pp.60-73
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    • 2014
  • Objectives: This study aims at decreasing spatial dose rate through work improvement whilst spatial dose rate is the cause of increasing personal exposure dose which occurs in the process of handling radioisotope. Methods: From February 2013 until July 2013, divided into "before" and "after" the improvement, spatial dose rate in laboratory of nuclear medicine was measured in gamma image room, PET/CT-1 image room, and PET/CT-2 image room as its locations. The measurement time was 08:00, 12:00 and 17:00, and SPSS 21.0 USA was opted for its statistical analysis. Result: The spatial dose rate at distribution worktable, injection table, the entrance to the distribution room, and radioisotope storage box, which had showed high spatial dose rate, decreased by more than 43.7% a monthly average. The distribution worktable, that had showed the highest spatial dose rate in PET/CT-1 image room, dropped the rate to 42.3% as of July. The injection table and distribution worktable in the PET/CT-2 image room also showed the decline of spatial dose rate to 89% and 64.4%, respectively. Conclusion: By improving distribution process and introducing proper radiation shielding material, we were able to drop the spatial dose rate substantially at distribution worktable, injection table, and nuclide storage box. However, taking into account of steadily increasing amount of radioisotope used, strengthening radiation related regulations, and safe utilization of radioisotope, the process of system improvement needs to be maintained through continuous monitoring.

Target Market Determination for Information Distribution and Student Recruitment Using an Extended RFM Model with Spatial Analysis

  • ERNAWATI, ERNAWATI;BAHARIN, Safiza Suhana Kamal;KASMIN, Fauziah
    • Journal of Distribution Science
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    • v.20 no.6
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    • pp.1-10
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    • 2022
  • Purpose: This research proposes a new modified Recency-Frequency-Monetary (RFM) model by extending the model with spatial analysis for supporting decision-makers in discovering the promotional target market. Research design, data and methodology: This quantitative research utilizes data-mining techniques and the RFM model to cluster a university's provider schools. The RFM model was modified by adapting its variables to the university's marketing context and adding a district's potential (D) variable based on heatmap analysis using Geographic Information System (GIS) and K-means clustering. The K-prototype algorithm and the Elbow method were applied to find provider school clusters using the proposed RFM-D model. After profiling the clusters, the target segment was assigned. The model was validated using empirical data from an Indonesian university, and its performance was compared to the Customer Lifetime Value (CLV)-based RFM utilizing accuracy, precision, recall, and F1-score metrics. Results: This research identified five clusters. The target segment was chosen from the highest-value and high-value clusters that comprised 17.80% of provider schools but can contribute 75.77% of students. Conclusions: The proposed model recommended more targeted schools in higher-potential districts and predicted the target segment with 0.99 accuracies, outperforming the CLV-based model. The empirical findings help university management determine the promotion location and allocate resources for promotional information distribution and student recruitment.

A Spatial Distribution Analysis and Time Series Change of PM10 in Seoul City (서울시 PM10 공간분포 분석과 시계열 변화)

  • Jeong, Jong-Chul
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.1
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    • pp.61-69
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    • 2014
  • In this study spatial analysis of PM10 was performed to Particulate Materials(PM) less than $10{\mu}m$ in diameter in Seoul city. Because PM10 are responsible for the increasing mortality rate of lung cancer and cardiovascular diseases, spatial distribution of PM10 are special interest in air pollution of Seoul. In this study, spatial analysis of Particulate Materials were monitored by monthly averaged PM10 concentration of 2010, 2011. The monthly spatial patterns of PM10 showed the west area of Seoul(Youngdungpo) higher PM10 concentration than northern part of Seoul in early spring and winter seasons. In the comparison of PM10 concentration distribution patterns in 2010 and 2011, the PM10 concentration of 2011 at Gangnam and Songpa-gu were more increased than yearly averaged patterns of 2010. The distribution patterns of PM10 in Seoul city showed the high concentration PM10 of several areas with Youngdungpo-gu, Gangnam-gu and Cheongnyangni. Therefore we need to establish PM10 management strategy for these area.

Cluster and information entropy analysis of acoustic emission during rock failure process

  • Zhang, Zhenghu;Hu, Lihua;Liu, Tiexin;Zheng, Hongchun;Tang, Chun'an
    • Geomechanics and Engineering
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    • v.25 no.2
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    • pp.135-142
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    • 2021
  • This study provided a new research perspective for processing and analyzing AE data to evaluate rock failure. Cluster method and information entropy theory were introduced to investigate temporal and spatial correlation of acoustic emission (AE) events during the rock failure process. Laboratory experiments of granite subjected to compression were carried out, accompanied by real-time acoustic emission monitoring. The cumulative length and dip angle curves of single links were fitted by different distribution models and distribution functions of link length and directionality were determined. Spatial scale and directionality of AE event distribution, which are characterized by two parameters, i.e., spatial correlation length and spatial correlation directionality, were studied with the normalized applied stress. The entropies of link length and link directionality were also discussed. The results show that the distribution of accumulative link length and directionality obeys Weibull distribution. Spatial correlation length shows an upward trend preceding rock failure, while there are no remarkable upward or downward trends in spatial correlation directionality. There are obvious downward trends in entropies of link length and directionality. This research could enrich mathematical methods for processing AE data and facilitate the early-warning of rock failure-related geological disasters.

Determinants of Economic Segregation and Spatial Distribution of Poverty

  • Park, Yoonhwan
    • Journal of Distribution Science
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    • v.17 no.3
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    • pp.21-30
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    • 2019
  • Purpose - While many related prior studies have focused on the segregation by race and ethnicity, the academic interest in the separation of residence by income and social class is gradually increasing. This study aims to not only investigate spatial pattern of economic segregation and poverty rate in South Korea, but also shed light on what affect residential distribution of the poor. Research design, data, and methodology - The unit of analysis is Si-Gun-Gu municipal level entities of South Korea. Most demographic, socioeconomic, and residential variables were derived from Korean Census Data in 2015. In order to examine spatial patterns of economic segregation and poverty rate in South Korea, a series of measurements and visualization was conducted through the Geo-Segregation Analyzer and ArcGIS programs. Determinants of economic segregation and local poverty rates were investigated by regression analyses using STATA. Results - The spatial patterns of areas with high poverty rates were extremely clustered, while the distribution of areas with high economic segregation was relatively evenly distributed. Demographic, residential, and local factors appeared to affect whether the poor live in particular area or spread evenly. Conclusions - The factors that raise the poverty rate result in lower level of economic segregation, while factors that reduce the poverty rate lead to severe level of economic segregation.

A Study on the Spatial Distribution Patterns of Urban Green Spaces Using Local Spatial Autocorrelation Statistics (국지적 공간자기상관통계를 이용한 도시녹지의 공간적 분포패턴에 관한 연구)

  • Kim, Yun-Ki
    • Journal of Cadastre & Land InformatiX
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    • v.50 no.1
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    • pp.25-45
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    • 2020
  • The primary purpose of this study is to compare and analyze the performance of local spatial autocorrelation techniques in identifying spatial distribution patterns of green spaces. To achieve the objective, this researcher uses satellite image analysis and spatial autocorrelation techniques. The result of the study shows that the LISA cluster map with the spatial outlier cluster is superior to other analytical methods in identifying the spatial distribution pattern of urban green space. This study can contribute to the related fields in that it uses several different research methods than the existing ones. Despite this differentiation and usefulness, this study has limitations in using low-resolution satellite imagery and NDVI among vegetation indices in identifying spatial distribution patterns of green areas. These limitations may be overcome in future studies by using UAV images or by simultaneously using several vegetation indices.

Spatial Characteristics of the Provision of and Demand for Private Tutoring Service Industries in the Metropolitan Seoul Area (사교육 시설의 수요와 공급에 나타나는 공간적 특성: 수도권 지역 사설학원을 중심으로)

  • Park, So-Hyun;Lee, Keum-Sook
    • Journal of the Economic Geographical Society of Korea
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    • v.14 no.1
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    • pp.33-51
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    • 2011
  • This study investigates the spatial characteristics of the provision of and demand for the private tutoring service industries and the consumer groups. For the purpose, we analyze the spatial characteristics of various types of tutoring institutes in the Seoul Metropolitan area. In particular, we exam the spatial distribution patterns of attendants of tutoring institutes by institution type as well as the resident population by attendant age group. By applying spatial autocorrelation analysis, we examine the spatial clustering patterns of tutoring institutes and attendants by type. The results show distinct differences in the spatial distribution patterns by tutoring institute type as well as by attendant age group. We found significant socio-economic variables which influence on the spatial distribution of tutoring institutes. Finally, we propose private tutoring service provision models constructed with these variables through multiple regression analysis.

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Selection of Spatial Regression Model Using Point Pattern Analysis

  • Shin, Hyun Su;Lee, Sang-Kyeong;Lee, Byoungkil
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.3
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    • pp.225-231
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    • 2014
  • When a spatial regression model that uses kernel density values as a dependent variable is applied to retail business data, a unique model cannot be selected because kernel density values change following kernel bandwidths. To overcome this problem, this paper suggests how to use the point pattern analysis, especially the L-index to select a unique spatial regression model. In this study, kernel density values of retail business are computed by the bandwidth, the distance of the maximum L-index and used as the dependent variable of spatial regression model. To test this procedure, we apply it to meeting room business data in Seoul, Korea. As a result, a spatial error model (SEM) is selected between two popular spatial regression models, a spatial lag model and a spatial error model. Also, a unique SEM based on the real distribution of retail business is selected. We confirm that there is a trade-off between the goodness of fit of the SEM and the real distribution of meeting room business over the bandwidth of maximum L-index.