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

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

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Bibliographic Details
:
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
Online Access:
Physical Description:1 online resource (320 pages)
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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.

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