Geoinformatics in Theory and Practice: An Integrated Approach to Geoinformation Systems, Remote Sensing and Digital Image Processing

Foreword
Contents
1: Introduction
1.1 Geoinformatics: Approach and Tasks
1.2 Computer Science and Geoinformatics: Ethical Challenges
References
2: Information Processing: Basic Concepts
2.1 Information, Message, Signals, Data
2.2 Machine, Computer, Program, Hardware, Software
2.3 Information Processing: IPO Principle
2.4 Computer Systems: Algorithms and Programs
2.4.1 Algorithm Concept
2.4.2 Program Flow-Charts and Structure Diagrams
2.4.3 Levels of Algorithm Execution in a Computer System
2.5 Computer System: Presentation of Information by Bit Sequences
2.5.1 Digital World, Digitalisation
2.5.2 Bit and Bit Sequences
2.5.3 Logical Values
2.5.4 Numbers
2.5.5 Text
2.5.6 Spatial Information
2.5.7 Color Information
2.5.8 Sensor Data
2.5.9 Dual Numbers Arithmetic
2.6 Structure of a Computer System: Hardware
2.7 Structure of a Computer System: Software
2.7.1 System Software and System-Related Software
2.7.2 Business, Individual and Standard Software, Apps
2.7.3 Application Software in Geoinformatics
2.7.4 Proprietary, Open Source and Free Software
2.8 Networks and Connectivity
2.8.1 Definition and Distinguishing Features
2.8.2 Internet
2.8.3 Web Technologies
2.8.4 Web 2.0
2.8.5 Cloud Computing
References
3: Basic Concepts of Computer Science
3.1 Programming Computer Systems
3.1.1 Programming Levels
3.1.2 Creating and Executing Programs
3.1.3 Programming Languages
3.1.4 Programming: Concepts
3.1.4.1 Structured Programming
3.1.4.2 Modular Programming
3.1.4.3 Object-Oriented Programming
3.1.5 Programming with Python in Geoinformation Systems
3.1.6 Graphics Languages and Libraries
3.1.7 Programming Applications for Browsers
3.1.8 Programming Applications for Mobile Devices
3.2 Data and Data Types
3.2.1 Scale Levels
3.2.2 Standard Data Types
3.2.2.1 Representation Data as Bit Sequences
3.2.2.2 Default Data Type Integer
3.2.2.3 Default Data Type Floating Point
3.2.2.4 Default Data Type Character
3.2.2.5 Default Data Type Logical Value
3.2.2.6 Data Type String and Pointer
3.2.3 Structured Data Types
3.2.4 Abstract Data Types
3.2.4.1 Stack
3.2.4.2 Queues
3.2.4.3 Chained Lists
3.2.4.4 Trees
3.2.5 Files
3.3 Algorithms
3.3.1 Definition and Characteristics
3.3.2 Sequential and Parallel Algorithms
3.3.3 Iterations and Recursions
3.3.3.1 Iterative Strategies and Approximation Methods
3.3.3.2 Recursions
3.3.4 Algorithm Complexity
3.4 Basic Algorithms of Geoinformatics
3.4.1 Algorithms of Coordinate Geometry
3.4.2 Graphs and Selected Path Algorithms
3.4.3 Algorithms for Raster Data
3.4.4 Advanced Algorithms
3.5 Software Engineering
3.5.1 Software Engineering: Tasks and Goals
3.5.2 Software Development Tools
3.5.3 Traditional Models of Software Development and Engineering
3.5.4 Object-Oriented Software Development
3.5.5 V Models and Further Developments
References
4: Geoobjects and Reference Systems
4.1 Geoobjects
4.1.1 Geoobject: Concept
4.1.2 Geoobjects: Geometry
4.1.3 Geoobjects: Topology
4.1.4 Geoobjects: Thematic Information
4.1.5 Geoobjects: Dynamics
4.1.6 Geoobjects: Dimensions
4.2 Coordinate Systems
4.2.1 Metric Spaces and Cartesian Coordinates
4.2.2 Homogeneous Coordinates
4.2.3 Polar Coordinates and Geographic Coordinates on the Sphere
4.2.4 Geodetic Coordinates on an Ellipsoid
4.2.5 Plane Coordinate Transformations
4.2.5.1 Georeferencing
4.2.5.2 Affine Coordinate Transformation
4.2.5.3 Projective Transformation
4.2.5.4 Polynomial Transformation
4.2.5.5 Determining the Transformation Equations
4.3 Map Projections
4.3.1 Presenting Geoobjects: General Issues
4.3.2 Projection Properties
4.3.3 Types of Map Projections
4.3.3.1 Projection Surfaces
4.3.3.2 Azimuthal Projection
4.3.3.3 Conic Projection
4.3.3.4 Cylinder Projection
4.3.3.5 Web Mercator Projection
4.4 Coordinate Reference Systems
4.4.1 Overview
4.4.2 Approximation of the Earth by Ellipsoids
4.4.3 Traditional Coordinate Reference Systems in Germany and Geodetic Datum
4.4.4 New Reference Frames: ITRF, ETRF and ETRS89
4.4.5 Datum Transformation
4.4.6 Height Reference Surfaces in Germany Until 2016
4.4.7 The Integrated (Geodetic) Spatial Reference 2016
4.5 Geodetic Projection
4.5.1 Geodetic Projection: Use
4.5.2 The Gauss-Krüger Coordinate System in Germany
4.5.3 The UTM Coordinate System
4.5.4 UTM Coordinates: Computation
4.5.5 EPSG Codes
4.6 Georeferencing in a Geoinformation System: Example
4.6.1 Georeferencing Based on Geodetic Coordinates
4.6.2 Definition of the Spatial Reference After Georeferencing
4.6.3 Multiple Reference Systems and Datum Transformation
References
5: Digital Geodata: Data Mining, Official Basic Geodata and VGI
5.1 Basic Terms
5.1.1 Primary and Secondary Data Recording, Primary and Secondary Data
5.1.2 Discretisation
5.2 Digital Recording of Geometry Data Using Secondary Techniques
5.2.1 Digital Recording of Geometry Data in Vector Format
5.2.2 Digital Recording of Geometry Data in Raster Format
5.2.3 Conversion Between Raster and Vector Data
5.3 Satellite-Based Positioning and Recording of 3D Position Coordinates
5.3.1 GPS and GNSS
5.3.2 NAVSTAR/GPS: Basic Principles Before Modernisation
5.3.3 Distance Determination: Principle
5.3.4 Error Influences and Accuracies of a GPS Location Determination
5.3.5 Differential GPS (DGPS)
5.3.6 NAVSTAR/GPS: Modernisation
5.3.7 GLONASS
5.3.8 Galileo
5.3.9 BeiDou
5.3.10 GNSS Data
5.3.11 Evaluation of Positioning Systems and Further Development of GNSS
5.4 Airborne Laser Scanning
5.5 Official Basic Geodata
5.5.1 Official Basic Geodata: Tasks and Challenges for the Surveying Authorities
5.5.2 Former ALK
5.5.3 Former ATKIS
5.5.4 AFIS - ALKIS - ATKIS
5.5.4.1 AFIS-ALKIS-ATKIS Concept: Main Features
5.5.4.2 Location Reference System in the AAA Concept
5.5.4.3 AFIS in the AAA Model
5.5.4.4 ALKIS in the AAA Model
5.5.4.5 ATKIS in the AAA Model
5.5.4.6 Obtaining Official Basic Geodata in Germany
5.6 Volunteered Geographic Information (VGI)
5.6.1 Data in the GeoWeb 2.0
5.6.2 Open Street Map (OSM) Project
5.6.3 OSM Data Quality
References
6: Standards and Interoperability of Geodata
6.1 Standardisation and Interoperability
6.1.1 Multiple Use Through Standardisation
6.1.2 Syntactic and Semantic Interoperability
6.2 Standardisation
6.2.1 Standard and Norm
6.2.2 Standardisation Institutions
6.2.3 International Organisation for Standardisation (ISO)
6.2.4 Open Geospatial Consortium
6.3 Standards for Modeling Geodata
6.3.1 Feature Geometry Model of the OGC
6.3.2 Simple Feature Geometry Object Model of the OGC
6.3.3 Geography Markup Language
6.3.4 GeoPackage
6.4 Geodata Services
6.4.1 Interoperability Through Standardised Geodata Services
6.4.2 OGC-Compliant Geodata Services
6.4.3 Functionality of an OGC-Compliant WMS Using the Example of the UMN-MapServer
6.4.4 Access to Geodata Via a Web Map Service
6.4.5 Access to Geodata Via a Web Feature Service
6.4.6 Access to Geodata Via Other Web Services
6.4.7 Processing Geodata by Standardised Web Processing Services
6.4.8 Processing Geodata by a Web Map Service in a Geoinformation System
6.5 Metadata
6.5.1 From Data to Information Through Metadata
6.5.2 Standards for Spatial Metadata
6.5.2.1 Dublin Core Metadata Initiative
6.5.2.2 Content Standard for Digital Geospatial Metadata
6.5.2.3 ISO 19115
6.6 Data and Geodata Quality
6.6.1 Quality Features
6.6.2 Spatial Resolution, Generalisation and Positional Accuracy
6.7 Spatial Data Infrastructures
6.7.1 Spatial Data Infrastructures: Concept and Objectives
6.7.2 INSPIRE
6.7.3 Spatial Data Infrastructure in Germany: A Trend Setting Example
6.7.4 National Geoinformation Strategy (NGIS) in Germany
6.7.5 Spatial Data Infrastructure Within the Federal States in Germany
References
7: Spatial Information: Visualisation
7.1 Interdisciplinary View of Cartography
7.1.1 Digital Graphic Presentation of Information
7.1.2 Computer-Assisted Scientific Visualisation
7.1.3 Geovisualisation
7.1.4 Digital Graphic Presentation of Geoobjects: Paradigm Shift Within Cartography
7.1.5 Geoinformatics: Presentation
7.1.6 Augmented Reality: Virtual Reality
7.1.7 Virtual Reality in Geoinformatics: 3D City Models
7.2 Graphic Presentations on the WWW
7.2.1 Web Mapping
7.2.2 Mapserver: Use Case
7.2.3 Mapping Software: Example
7.2.4 Graphic Presentations in Applications
7.2.5 Cartography on the Web 2.0: Web Mapping 2.0
7.3 Visual Communication
7.4 Graphic Semiology
7.4.1 Graphic Semiology: According to Bertin
7.4.2 Design Rules Based on Bertin´s Graphic Semiology
7.4.3 Further Development and Digital Implementations
7.5 Graphic Design Elements
7.5.1 Map or Cartographic Symbols
7.5.2 Representation of Qualitative Features
7.5.3 Representation of Quantitative Features
7.5.4 Classification
7.5.5 Diagrams
7.5.6 Cartograms
7.6 Printed Maps and Posters: Design Features
7.6.1 Printed Maps and Posters: Formal Design
7.6.2 Printed Maps and Posters: Texts and Labels
7.7 Use of Color
7.7.1 Color as a Simple but Also Disputable Tool for Presentations
7.7.2 Color Effect and Color Perception
7.7.3 Color Gradings
7.7.4 Color Mixing and Color Models
References
8: Data Organisation and Database Systems
8.1 Data Organisation
8.1.1 Data Organisation: Basic Concepts
8.1.2 File Systems
8.1.3 Database Systems
8.1.4 Data Views in a Database System
8.1.5 Data Models
8.2 Database Design with ER-Modeling
8.2.1 Modeling Concepts
8.2.2 Entity and Attribute
8.2.3 Relationship
8.2.4 Entity Relationship Models
8.2.5 Conceptual Database Design: A Case Study
8.3 Relational Data Model
8.3.1 Relational Database: Structure
8.3.2 Database Normalisation
8.3.3 Transformation of an ER-Model into a Relation Model
8.4 Relational Database Systems: Applications
8.4.1 Data Definition and Management Functions
8.4.2 Data Manipulation and Data Analysis
8.4.3 The SQL Language Standard of a Data Manipulation Language for Relational Database Systems
8.4.4 Analysis of a Database with SQL
8.4.5 Relational Data Structures in a Geoinformation Systems
8.5 Data Consistency
8.5.1 Data Consistency: Concept and Meaning
8.5.2 Referential Integrity
8.5.3 Trigger
8.5.4 Transactions
8.6 Extension
8.6.1 Dependent Entity Types
8.6.2 The Is-a Relationship
8.6.3 EER Model
8.6.4 Object-Oriented and Object-Relational Database Systems
8.7 Spatial Database
8.7.1 Managing and Processing Geodata in Relational Databases
8.7.2 Spatial Database: Operating Principle
8.7.3 PostgreSQL/PostGIS
8.7.4 PostgreSQL/PostGIS: A Sample Application
References
9: Geoinformation Systems
9.1 Concepts of Digital Information Systems and Geoinformation Systems
9.1.1 Information Systems
9.1.2 Four-Component Models of an Information System
9.1.3 Geoinformation System: Notion
9.1.4 Four Component Models of a Geoinformation System
9.1.5 GIS Software
9.1.6 Geoinformation Systems and Similar Systems
9.2 Web-GIS
9.2.1 Web-GIS: Concept and Functionality
9.2.2 Web-GIS in Practice
9.2.3 Web Mapping as a Substitute for a Web-GIS?
9.3 Modeling Geoobjects in a Geoinformation System
9.3.1 Geoinformation System as a Model of the Real World
9.3.2 Geometric-Topological Modeling of Geoobjects in the Vector Model
9.3.3 Geometric-Topological Modeling in the Vector Model: Application
9.3.4 Geometric-Topological Modeling of Geoobjects in the Raster Model
9.3.5 Storing Geometries in the Raster Model
9.3.6 Topic of Geoobjects
9.3.7 Vector and Raster Model: Comparison
9.4 Vector Model: Spatial Analysis of Geoobjects
9.4.1 Vector Model: Recording and Editing Geoobjects
9.4.2 Managing Geoobjects in the Vector Model: Data Queries
9.4.3 Updating Geoobjects in the Vector Model
9.4.4 Spatial Analyses of Vector Data
9.4.5 Spatial Analyses of Vector Data in Planning: An Example
9.5 Raster Model: Spatial Analysis of Geoobjects
9.5.1 Raster Model: Recording and Editing Geoobjects
9.5.2 Exchange Thematic Data Between Vector and Raster Model
9.5.3 Spatial Analyses of Raster Data
9.5.4 Map Algebra
9.6 Network Analyses
9.6.1 Network Data Model
9.6.2 Analysis of Optimal Paths in a Network
9.6.3 Generating Service Areas
9.6.4 Further Analysis Options in a Network
9.7 Spatial Interpolation and Modeling of Surfaces
9.7.1 Initial Issues
9.7.2 Spatial Approximation and Trend Surface Analysis
9.7.3 Spatial Interpolation: Weighted Average
9.7.4 Thiessen Polygons
9.7.5 Triangulated Irregular Network
9.7.5.1 Creating Triangular 3D-Surfaces
9.7.5.2 Delauny Triangulation
9.7.6 Parameterisation of Surfaces
References
10: Remote Sensing and Digital Image Processing
10.1 Remote Sensing: Definition and Use
10.2 Remote Sensing and Digital Image Processing: General Approach
10.2.1 Remote Sensing: Principles
10.2.2 Sensor Systems and Platforms
10.2.3 Digital Image Processing
10.2.4 Photogrammetry
10.3 Electromagnetic Radiation Principles
10.3.1 The Electromagnetic Spectrum
10.3.2 Solar Radiation and Atmospheric Influences
10.3.3 Reflection of the Earth´s Surface
10.4 Major Satellite-Based Imaging Systems
10.4.1 Remote Sensing Instruments: Characteristics
10.4.2 Orbit Parameters of Remote Sensing Satellites
10.4.3 Recording Principles of Scanners on Satellite Systems
10.4.4 Recording Systems with Radar
10.4.5 Weather Satellites
10.4.6 Landsat
10.4.6.1 Mission
10.4.6.2 Recording Systems of Landsat 1 to 7
10.4.6.3 Landsat 8 and 9
10.4.6.4 Data Preparation
10.4.7 SPOT and Pléiades
10.4.8 ASTER on Terra
10.4.9 Copernicus and Sentinel
10.4.10 Recent Commercial High-Resolution Sensors
10.5 Digital Images
10.5.1 Recording Digital Images in Remote Sensing
10.5.2 Visualising Digital Images in Remote Sensing
10.5.3 Remote Sensing Data: Acquisition
10.6 Digital Image Processing
10.6.1 Image Pre-Processing
10.6.1.1 Radiometric Correction
10.6.1.2 Rectification, Registration and Resampling
10.6.2 Image Enhancement: Contrast Enhancement
10.6.2.1 Linear Contrast Stretching
10.6.2.2 Histogram Equalisation
10.6.3 Image Enhancement: Image Transformation in the Spectral Domain
10.6.3.1 Band Ratios and Vegetation Indices
10.6.3.2 Principal Components Transformation
10.6.4 Image Enhancement: Spatial Filtering
10.6.4.1 Low-Pass Filter
10.6.4.2 High-Pass Filter
10.6.5 Merging Multiple Remote Sensing Images
10.6.5.1 Geometric Mosaicking
10.6.5.2 Radiometric Mosaicking
10.6.5.3 Image Fusion
10.7 Classification
10.7.1 Pixel-Based Classification Methods: Principle
10.7.2 Pixel-Based Classification Methods: Implicit Assumptions
10.7.3 Unsupervised Classification
10.7.4 Determining Training Areas in the Supervised Classification
10.7.5 Classification Based on Statistical Parameters
10.7.6 Classification Accuracy
10.7.7 Pixel-Based Classification Methods: Problems
10.7.8 Object-Oriented Image Segmentation and Classification
10.7.9 Modern Advanced Classification Approaches
10.7.9.1 Classification with the Help of Neural Networks
10.7.9.2 Classification with Support Vector Machine
10.7.9.3 Classification with the Help of Decision Trees
References
Index