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Format: 1 Online-Ressource (viii, 325 Seiten) : , Illustrationen.

ISBN: 978-3-030-26626-4

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26625-7

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26627-1

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26628-8

Language: English

Subjects: Economics

Keywords: Wirtschaftsinformatik ; Daten ; Datenanalyse ; Visualisierung

DOI: 10.1007/978-3-030-26626-4

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Author information: Jürgens, Carsten 1961-

UID:

Format: 1 Online-Ressource (viii, 325 Seiten) : , Illustrationen.

ISBN: 978-3-030-26626-4

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26625-7

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26627-1

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26628-8

Language: English

Subjects: Economics

Keywords: Wirtschaftsinformatik ; Daten ; Datenanalyse ; Visualisierung

DOI: 10.1007/978-3-030-26626-4

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

URL: Buchcover

URL: lizenzpflichtig

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

URL: Buchcover

Author information: Jürgens, Carsten 1961-

UID:

Format: 1 Online-Ressource (viii, 325 Seiten) : , Illustrationen.

ISBN: 978-3-030-26626-4

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26625-7

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26627-1

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26628-8

Language: English

Subjects: Economics

Keywords: Wirtschaftsinformatik ; Daten ; Datenanalyse ; Visualisierung

DOI: 10.1007/978-3-030-26626-4

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

URL: Buchcover

Author information: Jürgens, Carsten 1961-

UID:

Format: 1 online resource (VIII, 325 p. 209 illus., 199 illus. in color.)

Edition: 1st ed. 2020.

ISBN: 3-030-26626-5

Content: This open access book is based on "Spationomy – Spatial Exploration of Economic Data", an interdisciplinary and international project in the frame of ERASMUS+ funded by the European Union. The project aims to exchange interdisciplinary knowledge in the fields of economics and geomatics. For the newly introduced courses, interdisciplinary learning materials have been developed by a team of lecturers from four different universities in three countries. In a first study block, students were taught methods from the two main research fields. Afterwards, the knowledge gained had to be applied in a project. For this international project, teams were formed, consisting of one student from each university participating in the project. The achieved results were presented in a summer school a few months later. At this event, more methodological knowledge was imparted to prepare students for a final simulation game about spatial and economic decision making. In a broader sense, the chapters will present the methodological background of the project, give case studies and show how visualisation and the simulation game works.

Note: 1. Part A Methodological overview (Data sources (spatial and economic data, Quantitative methods in economy, Spatial analysis in geomatics, Business informatics principles, Methods in Microeconomics and Macroeconomics, Finance and Business, Economic Geography) -- 2. Part B - Techniques of data visualization (Non-spatial visualization, Spatial visualization, Interactive visualization) -- 3. Part C - Spatial exploration of economic data (Methods of interdisciplinary analytics, Case studies and applications I - V) -- 4. Part D - Simulation game-based framework (Introduction, Simulation Game Concept, Simulation Game Rounds, Evaluation/Scoring, Experiences/Good Practices). , English

Additional Edition: ISBN 3-030-26625-7

Language: English

Subjects: Geography

DOI: 10.1007/978-3-030-26626-4

URL: https://doi.org/10.1007/978-3-030-26626-4

URL: Volltext  (kostenfrei)

URL: Cover

UID:

Format: 1 Online-Ressource (325 Seiten) , Illustrationen

ISBN: 9783030266264

Content: This open access book is based on "Spationomy – Spatial Exploration of Economic Data", an interdisciplinary and international project in the frame of ERASMUS+ funded by the European Union. The project aims to exchange interdisciplinary knowledge in the fields of economics and geomatics. For the newly introduced courses, interdisciplinary learning materials have been developed by a team of lecturers from four different universities in three countries. In a first study block, students were taught methods from the two main research fields. Afterwards, the knowledge gained had to be applied in a project. For this international project, teams were formed, consisting of one student from each university participating in the project. The achieved results were presented in a summer school a few months later. At this event, more methodological knowledge was imparted to prepare students for a final simulation game about spatial and economic decision making. In a broader sense, the chapters will present the methodological background of the project, give case studies and show how visualisation and the simulation game works.

Note: English

Additional Edition: ISBN 9783030266257

Language: English

Keywords: Aufsatzsammlung

URL: kostenfrei

URL: kostenfrei

Author information: Jürgens, Carsten 1961-

UID:

Format: 1 online resource (320 pages)

Edition: 1st ed.

ISBN: 9783030266264

Content: 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.

Note: Description based on publisher supplied metadata and other sources

Additional Edition: ISBN 9783030266257

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030266257

Language: English

URL: lizenzpflichtig

UID:

Format: 1 online resource (320 pages)

Edition: 1st ed.

ISBN: 9783030266264

Note: 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.

Additional Edition: Print version: Pászto, Vít Spationomy Cham : Springer International Publishing AG,c2019 ISBN 9783030266257

Language: English

Keywords: Electronic books.

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UID:

Format: 1 online resource (320 pages)

Edition: 1st ed.

ISBN: 9783030266264

Note: 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

Additional Edition: Print version Pászto, Vít Spationomy Cham : Springer International Publishing AG,c2019 ISBN 9783030266257

Language: English

Keywords: Electronic books

URL: Full-text  ((OIS Credentials Required))

UID:

Format: 1 online resource (VIII, 325 p. 209 illus., 199 illus. in color.)

Edition: 1st ed. 2020.

ISBN: 3-030-26626-5

Content: This open access book is based on "Spationomy – Spatial Exploration of Economic Data", an interdisciplinary and international project in the frame of ERASMUS+ funded by the European Union. The project aims to exchange interdisciplinary knowledge in the fields of economics and geomatics. For the newly introduced courses, interdisciplinary learning materials have been developed by a team of lecturers from four different universities in three countries. In a first study block, students were taught methods from the two main research fields. Afterwards, the knowledge gained had to be applied in a project. For this international project, teams were formed, consisting of one student from each university participating in the project. The achieved results were presented in a summer school a few months later. At this event, more methodological knowledge was imparted to prepare students for a final simulation game about spatial and economic decision making. In a broader sense, the chapters will present the methodological background of the project, give case studies and show how visualisation and the simulation game works.

Note: 1. Part A Methodological overview (Data sources (spatial and economic data, Quantitative methods in economy, Spatial analysis in geomatics, Business informatics principles, Methods in Microeconomics and Macroeconomics, Finance and Business, Economic Geography) -- 2. Part B - Techniques of data visualization (Non-spatial visualization, Spatial visualization, Interactive visualization) -- 3. Part C - Spatial exploration of economic data (Methods of interdisciplinary analytics, Case studies and applications I - V) -- 4. Part D - Simulation game-based framework (Introduction, Simulation Game Concept, Simulation Game Rounds, Evaluation/Scoring, Experiences/Good Practices). , English

Additional Edition: ISBN 3-030-26625-7

Language: English

DOI: 10.1007/978-3-030-26626-4

UID:

Format: 1 online resource (VIII, 325 p. 209 illus., 199 illus. in color.)

Edition: 1st ed. 2020.

ISBN: 3-030-26626-5

Content: This open access book is based on "Spationomy – Spatial Exploration of Economic Data", an interdisciplinary and international project in the frame of ERASMUS+ funded by the European Union. The project aims to exchange interdisciplinary knowledge in the fields of economics and geomatics. For the newly introduced courses, interdisciplinary learning materials have been developed by a team of lecturers from four different universities in three countries. In a first study block, students were taught methods from the two main research fields. Afterwards, the knowledge gained had to be applied in a project. For this international project, teams were formed, consisting of one student from each university participating in the project. The achieved results were presented in a summer school a few months later. At this event, more methodological knowledge was imparted to prepare students for a final simulation game about spatial and economic decision making. In a broader sense, the chapters will present the methodological background of the project, give case studies and show how visualisation and the simulation game works.

Note: 1. Part A Methodological overview (Data sources (spatial and economic data, Quantitative methods in economy, Spatial analysis in geomatics, Business informatics principles, Methods in Microeconomics and Macroeconomics, Finance and Business, Economic Geography) -- 2. Part B - Techniques of data visualization (Non-spatial visualization, Spatial visualization, Interactive visualization) -- 3. Part C - Spatial exploration of economic data (Methods of interdisciplinary analytics, Case studies and applications I - V) -- 4. Part D - Simulation game-based framework (Introduction, Simulation Game Concept, Simulation Game Rounds, Evaluation/Scoring, Experiences/Good Practices). , English

Additional Edition: ISBN 3-030-26625-7

Language: English

DOI: 10.1007/978-3-030-26626-4