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Magisterarbeit 1/??   12 International Conference on Computational Science and Its Applications      th                   ...
ICCSA Brazil 2012Magisterarbeit          2/12                       2/??     Outline     1. Preface and Motivation     2. ...
ICCSA Brazil 2012Magisterarbeit          3/12                       3/??     1. Preface and Motivation (1)      Increasin...
ICCSA Brazil 2012Magisterarbeit          4/12                       4/??     1. Preface and Motivation (2)    @gonschorek ...
ICCSA Brazil 2012Magisterarbeit          5/12                       5/??     2. Spatio-Temporal Analysis for Civil Securit...
ICCSA Brazil 2012Magisterarbeit          6/12                       6/??     2. Spatio-Temporal Analysis for Civil Securit...
ICCSA Brazil 2012Magisterarbeit          7/12                       7/??     2. Spatio-Temporal Analysis for Civil Securit...
ICCSA Brazil 2012Magisterarbeit          8/12                       8/??     2. Spatio-Temporal Analysis for Civil Securit...
ICCSA Brazil 2012Magisterarbeit                  9/12                               9/??     2. Spatio-Temporal Analysis f...
ICCSA Brazil 2012Magisterarbeit          10/12                       10/??     3. Summary and Future Plans (1)      Metho...
ICCSA Brazil 2012Magisterarbeit          11/12                       11/??     3. Summary and Future Plans (2)      Metho...
Magisterarbeit   12/??                    Thank you for your attention!                 Julia Gonschorek | julia.gonschore...
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Geovisualization and Geostatistics: A Concept for the Numerical and Visual Analysis of Geographic Mass Data Julia Gonschorek, Lucia Tyrallová, - University of Potsdam

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Geovisualization and Geostatistics: A Concept for the Numerical and Visual Analysis of Geographic Mass Data Julia Gonschorek, Lucia Tyrallová, - University of Potsdam

  1. 1. Magisterarbeit 1/?? 12 International Conference on Computational Science and Its Applications th (ICCSA2012 in Salvador da Bahia/Brazil) Session GeoAnMod-3 on Monday June 18, 2012 Geovisualization and Geostatistics: A Concept for the Numerical and Visual Analysis of Geographic Mass Data Julia Gonschorek | Geoinformation Research Group | University of Potsdam Co-Author: Lucia Tyrallová | Geoinformation Research Group | University of Potsdam
  2. 2. ICCSA Brazil 2012Magisterarbeit 2/12 2/?? Outline 1. Preface and Motivation 2. Spatio-Temporal Analysis for Civil Security 3. Summary and Future Plans @gonschorek ∙ university of potsdam
  3. 3. ICCSA Brazil 2012Magisterarbeit 3/12 3/?? 1. Preface and Motivation (1)  Increasing availability of (mass-) data and need for specific information  complex computational analysis tools and techniques  Highly dimensional data needs to be analysed rapidly to discover relationships, clusters and trends  Scientific visualization offers a wide range of methods and techniques to efficiently analyze and visualize spatial and temporal data and information @gonschorek ∙ university of potsdam
  4. 4. ICCSA Brazil 2012Magisterarbeit 4/12 4/?? 1. Preface and Motivation (2) @gonschorek ∙ university of potsdam
  5. 5. ICCSA Brazil 2012Magisterarbeit 5/12 5/?? 2. Spatio-Temporal Analysis for Civil Security (1) Simple lineplot to visualize the temporal distribution of internistic emergencies in the City of Cologne (total number of 26,475 in 2007): @gonschorek ∙ university of potsdam
  6. 6. ICCSA Brazil 2012Magisterarbeit 6/12 6/?? 2. Spatio-Temporal Analysis for Civil Security (2) Box-and-Whisker-Plots to show differences in varaiances: R-Code (without months “January” and “February”): emergency <- read.csv(“c:tempintern07.csv”,header=T, sep=“;”) chisq.test(emergency[1:7,4:13]) Pearsons Chi-squared test data: emergency[1:7, 4:13] X-squared = 409.496, df = 54, p-value < 2.2e-16 qchisq(0.95,54) 72.15322 The non-parametric χ²- Test for testing dependency validates the observation. The correlation between “Day of the Week” and “Months” is highly significant. @gonschorek ∙ university of potsdam
  7. 7. ICCSA Brazil 2012Magisterarbeit 7/12 7/?? 2. Spatio-Temporal Analysis for Civil Security (3) Heatmap to detect temporal clusters: R-Code: install.packages(“gplots”) install.packages (“RColorBrewer”) library(gplots) library(RColorBrewer) x <- read.csv(“c:temp intern07.csv”, header=T, sep=“;”, row.names=1) matrix=data.matrix(x) heatmap.2(matrix, Rowv=T, Colv=T, dendrogram=c(“none”), distfun=dist, hclustfun=hclust, key=T, keysize=1, trace=“none”, density.info=c(“none”), margins=c(10,10), col=brewer.pal(10,”PiYG”)) @gonschorek ∙ university of potsdam
  8. 8. ICCSA Brazil 2012Magisterarbeit 8/12 8/?? 2. Spatio-Temporal Analysis for Civil Security (4) Map of 17,000 surgery emergencies in the City of Cologne during July, 2007 and June 2008 with kernel density estimation using Epanechnikov kernel: Hotspots of surgery emergencies… on Friday on Saturday on Sunday @gonschorek ∙ university of potsdam
  9. 9. ICCSA Brazil 2012Magisterarbeit 9/12 9/?? 2. Spatio-Temporal Analysis for Civil Security (5) (e) (d) Surgical Emergencies > total: 300 (c) > daytime: 6.00 – 7.00 a.m. > year: 2009 > district: Altstadt Sued (b) (a) (a) Data Source: all incoming emergency calls (b) First-order circle: inhomogeneous parts for cluster or administrative information (urban districts) (c) Second-order circle: homogeneous parts for temporal information: year (d) Third-order circle: inhomogeneous parts for temporal information: month, daytime, … @gonschorek ∙ university of potsdam (e) Fourth-order circle: inhomogeneous parts; Type of emergency case
  10. 10. ICCSA Brazil 2012Magisterarbeit 10/12 10/?? 3. Summary and Future Plans (1)  Methods can be used to efficiently extract spatio-temporal information from large databases  It is shown how specific emergency services cluster in space and time  Nearly the whole city area of Cologne was an emergency scene during the analysed perid. Especially the city centre, leisure facilities and nursing homes were emergency hot spots  Combination of different explorative techniques with those from geovisualisation can check the (long-term) experience of the firefighters on different spatial scales and precision @gonschorek ∙ university of potsdam
  11. 11. ICCSA Brazil 2012Magisterarbeit 11/12 11/?? 3. Summary and Future Plans (2)  Methods and results are important for future explorative analyses and geovisual analytics  Information and a deep understanding of specific distributions and patterns as well as (ir-) regularities of intensity are absolutely necessary for prevention measurements to be well-directed and needs based.  Time-series-analysis and prognoses are suitable for the operational, strategic and tactical planning. @gonschorek ∙ university of potsdam
  12. 12. Magisterarbeit 12/?? Thank you for your attention! Julia Gonschorek | julia.gonschorek@uni-potsdam.de Department of Geography | University of Potsdam http://www.geographie.uni-potsdam.de/geoinformatik

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