Spationomy : : Spatial Exploration of Economic Data and Methods of Interdisciplinary Analytics.

• Author: Pászto, Vít.
• TeilnehmendeR: Jürgens, Carsten.; Tominc, Polona.; Burian, Jaroslav.
• Place / Publishing House: Cham : : Springer International Publishing AG,, 2019.; {copy}2020.
• Year of Publication: 2019
• Edition: 1st ed.
• Language: English
• Physical Description: 1 online resource (320 pages)

Table of Contents

Intro -- Preface -- Contents -- Part I: Methodological Overview -- Chapter 1: Data Sources -- 1.1 Data Models -- 1.1.1 Basic Tabular and Attribute Data Formats (by Vít Pszto) -- 1.1.1.1 TXT -- 1.1.1.2 CSV -- 1.1.1.3 XLS/XLSX -- 1.1.1.4 XML -- 1.1.2 Spatial Data Models (by Andreas Redecker) -- 1.1.2.1 Raster Data -- 1.1.2.2 Vector Data -- 1.1.2.3 Tabular Data -- 1.1.2.4 Topology -- 1.1.2.5 The Shape-Format -- 1.1.2.6 Geodatabases -- 1.1.2.7 Spatial Reference Systems (SRS) -- 1.1.2.8 Geographical Coordinate Systems -- 1.1.2.9 Projected Coordinate Systems -- 1.1.2.10 Application of Geodata Models and Formats -- 1.1.2.11 Imagery -- 1.1.2.12 Digital Elevation Models -- 1.1.2.13 Network Datasets -- 1.1.3 Geodata Interoperability (by Andreas Redecker) -- 1.1.3.1 WFS -- 1.1.3.2 WCS -- 1.1.3.3 WMS -- 1.1.3.4 GML -- 1.1.3.5 WKT/WKB -- 1.1.3.6 KML/KMZ -- 1.1.3.7 GPX -- 1.1.4 Metadata (by Andreas Redecker) -- 1.2 International Data Sources (by Vít Pszto, Karel Macku, Andreas Redecker, and Nicolai Moos) -- 1.2.1 Eurostat -- 1.2.1.1 Eurostat Spatial Data -- 1.2.1.2 Eurostat Statistical Data -- 1.2.2 OECD -- 1.2.3 UN -- 1.2.4 WTO -- 1.2.5 World Bank -- 1.2.6 GADM -- 1.2.7 Esri Open Data -- 1.2.8 OpenStreetMap -- 1.2.9 Urban Atlas -- 1.3 National Data Sources -- 1.3.1 Czechia -- 1.3.1.1 Czech Statistical Office -- 1.3.1.2 Czech Office for Surveying, Mapping and Cadastre -- 1.3.2 Slovenia -- 1.3.2.1 Statistical Office of the Republic of Slovenia -- 1.3.2.2 The Surveying and Mapping Authority of the Republic of Slovenia -- 1.3.3 Germany -- 1.3.3.1 The Federal Statistical Office -- 1.3.3.2 Federal Agency for Cartography and Geodesy (BKG) -- 1.4 Other Statistical Data Sources -- 1.4.1 Eurostat Microdata -- 1.4.1.1 Community Innovation Survey -- 1.4.1.2 Eurostat Microdata - Other Sources -- 1.4.2 Global Entrepreneurship Monitor -- 1.4.3 Amadeus - Bureau Van Dijk.

1.5 Earth Observation Data (by Carsten Jürgens) -- 1.5.1 Platforms -- 1.5.2 Sensor Types -- 1.5.3 Types of Resolution -- 1.5.4 Orthoimage Products -- 1.5.5 Use of Earth Observation Image Data -- 1.5.6 Available Earth Observation Satellites -- 1.5.6.1 Sentinel Satellite Fleet -- 1.5.6.2 Landsat Satellites -- 1.5.6.3 European Space Imaging -- 1.5.6.4 Additional Resources -- 1.5.6.5 ESA -- 1.5.6.6 ESA EOPORTAL -- 1.5.6.7 ESA EDUSPACE -- 1.5.6.8 SATIMAGINGCORP -- 1.5.6.9 Satellite Image Archives -- References -- Chapter 2: Quantitative Methods -- 2.1 Introduction -- 2.2 Multivariate and Univariate Statistics -- 2.3 Descriptive and Inferential Statistics -- 2.4 Statistical Inference: Estimation -- 2.4.1 The t-distribution -- 2.5 Multivariate Statistical Methods: Binary Logistic Regression -- 2.6 Multi-criteria Decision Making -- 2.7 Use of Multi-criteria Decision Making in Land-Use Evaluation and Management -- 2.8 The Development of the Multi-criteria Model for the Protection of Agricultural Land for Food Self-Sufficiency -- 2.8.1 Problem Definition and Structuring -- 2.8.2 Criteria Weighting and Measuring Local Alternatives ́Values -- 2.8.3 Synthesis, Ranking and Sensitivity Analysis -- 2.9 Conclusions -- References -- Chapter 3: Spatial Analysis in Geomatics -- 3.1 Simple Spatial Analysis (by Andreas Redecker) -- 3.1.1 Selections -- 3.1.1.1 Select by Attribute -- 3.1.1.2 Linking Tabular Data -- 3.1.1.3 Select by Location -- 3.1.2 Single Feature Class Operations -- 3.1.2.1 Buffer -- 3.1.2.2 Dissolve -- 3.1.3 Overlay Operations -- 3.1.3.1 Clip -- 3.1.3.2 Difference -- 3.1.3.3 Union -- 3.1.3.4 Intersect -- 3.1.3.5 Symmetrical Difference -- 3.2 Raster Analysis (by Jaroslav Burian) -- 3.2.1 Raster Data -- 3.2.2 Map Algebra -- 3.2.3 Raster Operators -- 3.2.4 Raster Functions -- 3.2.4.1 Local -- 3.2.4.2 Focal -- 3.2.4.3 Zonal -- 3.2.4.4 Global.

3.2.5 Selected Raster Analysis -- 3.2.5.1 Resampling -- 3.2.5.2 Reclassification -- 3.2.5.3 Surface Analysis -- 3.2.5.4 Slope -- 3.2.5.5 Aspect -- 3.2.5.6 Hillshade (Illumination) -- 3.2.5.7 Viewshed (Visibility Analysis) -- 3.2.5.8 Cost Distance Analysis (Least-Cost Path) -- 3.2.5.9 Solar Radiation (Insolation) Analysis -- 3.2.5.10 Multi-Criteria Analysis -- 3.3 Network Analysis (by Nicolai Moos) -- 3.3.1 Introduction -- 3.3.2 Optimal Routes -- 3.3.3 Traveling Salesman Problem -- 3.3.4 Service Areas -- 3.3.5 Location-Allocation Analysis -- 3.3.6 Origin-Destination Matrices -- 3.4 Spatial Statistics (by Karel Macku) -- 3.4.1 Pattern Analysis -- 3.4.2 Point Patterns -- 3.4.2.1 Ripleyś K Function -- 3.4.2.2 Kernel Density -- 3.4.3 Spatial Autocorrelation -- 3.4.4 Geostatistics -- References -- Chapter 4: Business Informatics Principles -- 4.1 Introduction -- 4.2 Enterprise Information Systems for Operational Support -- 4.2.1 Enterprise Resource Planning (ERP) Information Systems and Customer Relationship Management (CRM) Information Systems -- 4.2.2 Enterprise Information Systems and GIS Integration -- 4.3 Information Systems for Management Support -- 4.3.1 Business Intelligence Systems -- 4.3.2 Business Intelligence and Spatial Analytics -- 4.4 Bibliometric Analysis of Research Publishing on Spatial Data Issues in Business Information Systems -- 4.4.1 Background, Aims and Scope of the Bibliometric Analysis -- 4.4.2 Research Publishing on Enterprise Resource Planning (ERP) and Geographical Information Systems (GIS) -- 4.4.3 Research Publishing on Business Intelligence (BI) and Geographical Information Systems (GIS) Integration -- 4.5 Conclusion -- References -- Chapter 5: Methods in Microeconomic and Macroeconomic Issues -- 5.1 Methods in Microeconomics -- 5.1.1 Microeconomics and Relationships Between Variables -- 5.1.1.1 Microeconomic Issues.

5.1.1.2 Economic Circle, Economic Entities, Different Kinds of Markets -- 5.1.1.3 Resources, Scarcity -- 5.1.1.4 Why Are Marginal Variables Important? -- 5.1.1.5 Market Equilibrium - Product Markets, Factor Markets -- 5.1.1.6 Competition -- 5.1.2 Decision-Making Issues -- 5.1.2.1 Decision-Making of Consumer -- 5.1.2.2 Decision Making of Producer -- 5.1.2.3 Costs Overview -- 5.1.3 Market Failures -- 5.2 Macroeconomics and Relationships Between Variables -- 5.2.1 Macroeconomic Issues -- 5.2.1.1 General Macroeconomic Model -- 5.2.1.2 Macroeconomic Indicators -- 5.2.1.3 State Budget Indicators and Public Finance -- 5.2.1.4 Monetary Indicators and Monetary Policy Instruments -- 5.2.1.5 Aggregate Demand and Supply -- 5.3 Economic Modelling -- 5.3.1 Overview of Applied Economic Models -- 5.3.1.1 Possibilities of Economic Models -- 5.3.1.2 Agent-Based Modelling -- 5.3.1.3 Input - Output Models -- 5.3.1.4 General Equilibrium Models - CGE -- 5.3.1.5 Long-Term Models -- References -- Chapter 6: Business and Finance -- 6.1 What Is the Goal of a Business? -- Example 6.1: TILAK -- 6.1.1 What Is Profit? -- Example 6.2: Basic Accounting Categories -- 6.1.2 Profit or Money? -- Example 6.3: Money and Time -- 6.2 Spatial Business -- Example 6.4: TomTom -- Example 6.5: Waze -- Example 6.6 -- Example 6.7 -- Example 6.8 -- Example 6.9 -- Example 6.10 -- 6.3 Business and Spatial issues -- 6.3.1 Case 1 - Cyclone Kyrill -- 6.3.2 Case 2 - Urban Planner -- Example 6.11: Multidimensional Decision in Sport -- 6.4 Summary -- References -- Chapter 7: Economic Geography -- 7.1 Definitions and History in Brief -- 7.1.1 Definitions -- 7.1.2 Historical Overview -- 7.1.2.1 Positivism -- 7.1.2.2 Structuralism -- 7.1.2.3 Post-structuralism -- 7.1.2.4 Future Directions -- 7.2 Location Theories -- 7.2.1 Von Thünen Location Theory -- 7.2.2 Weber Location Theory.

7.2.3 Christaller Theory of Central Places -- 7.2.4 Lösch Location Theory -- 7.2.5 Other Location Theories and Concepts -- References -- Part II: Techniques of Data Visualisation -- Chapter 8: Non-spatial Visualisation -- 8.1 Software -- 8.1.1 Tableau Software -- 8.1.2 HTML, Javascript and CSS -- 8.1.3 R -- 8.1.4 Datawrapper -- 8.2 Charts Classification -- 8.2.1 Trend Over the Time -- 8.2.1.1 Bar Chart -- 8.2.1.2 Point Chart -- 8.2.1.3 Line Chart -- 8.2.1.4 Step Chart -- 8.2.1.5 Gantt Chart -- 8.2.2 Proportions -- 8.2.2.1 Pie Chart -- 8.2.2.2 Doughnut Chart (Fig. 8.7) -- 8.2.2.3 Stacked Bar Chart -- 8.2.2.4 Tree Map/Area Chart -- 8.2.3 Relations and Correlation -- 8.2.3.1 Scatterplot -- 8.2.3.2 Bubble Plot -- 8.2.3.3 Scatterplot Matrix -- 8.2.4 Differences and Comparison -- 8.2.4.1 Heatmap -- 8.2.4.2 Paralel Coordinates -- 8.2.5 Statistical Charts -- 8.2.5.1 Histogram -- 8.2.5.2 Distribution Plot -- 8.2.5.3 Boxplot -- 8.3 A Good Design -- References -- Chapter 9: Spatial Visualisation -- 9.1 Introduction -- 9.2 Creation of the Choropleth Map -- 9.2.1 Creating the Choropleth Map in QGIS -- 9.2.1.1 Graduated Choropleth Map -- 9.2.1.2 Categorized Choropleth Map -- 9.3 Raster Fill Options -- 9.4 Proportional Symbols -- 9.5 Method of Graduate Symbols -- 9.6 Using Charts to Visualise Proportions -- 9.7 Cartograms -- 9.8 Map Composition -- References -- Chapter 10: Online Visualisation -- 10.1 Introduction -- 10.2 ArcGIS Online -- 10.3 Collector for ArcGIS -- 10.4 Esri Story Maps -- 10.5 Google Fusion Tables -- 10.6 Google Maps API -- 10.7 QGIS Cloud -- 10.8 Leaflet -- 10.9 Mapbox -- 10.10 Carto -- 10.11 OpenLayers -- 10.12 Advanced Mapping Tools -- References -- Part III: Spatial Exploration of Economic Data -- Chapter 11: Introduction to Spatial Exploration of Economic Data -- 11.1 Introduction -- 11.1.1 Level 1 - (Geo)Visual Analysis.

11.1.2 Level 2 - Statistics, Exploratory Data Analysis and Its (Geo)Visualisation.