Raster data

Abstract: UNIT 1. INTRODUCTION. Chapter 1. Introduction to Digital Geography. Learning Objectives. Why Geographic Information Systems? What Are Geographic Information Systems? Where Do I Begin? Terms. Review Questions. References. UNIT 2. DIGITAL GEOGRAPHIC DATA AND MAPS. Chapter 2. Basic Geographic Concepts. Learning Objectives. Developing Spatial Awareness. Spatial Measurement Levels. Spatial Location and Reference. Spatial Patterns. Geographic Data Collection. Populations and Sampling Schemes. Making Inferences from Samples. Terms. Review Questions. References. Chapter 3. Map Basics. Learning Objectives. Abstract Nature of Maps. A Paradigm Shift in Cartography. Map Scale. More Map Characteristics. Map Projections. Grid Systems for Mapping. The Cartographic Process. Map Symbolism. Map Abstraction and Cartographic Databases. Terms. Review Questions. References. Chapter 4. GIS Data Models. Learning Objectives. A Quick Review of the Map as an Abstraction of Space. Some Basic Computer File Structures. Simple Lists. Ordered Sequential Files. Indexed Files. Computer Database Structures for Managing Data. Hierarchical Data Structures. Network Systems. Relational Database Management Systems. Graphic Representation of Entities and Attributes. GIS Data Models for Multiple Maps. Raster Models. Compact Storing of Raster Data. Commercial Raster Compaction Products. Vector Models. Compacting Vector Data Models. A Vector Model to Represent Surfaces. Hybrid and Integrated Systems. Terms. Review Questions. References. UNIT 3. INPUT, STORAGE, AND EDITING. Chapter 5. The Input Subsystem. Learning Objectives. Primary Data. Input Devices. Raster, Vector, or Both. Reference Frameworks and Transformations. Map Preparation and the Digitizing Process. What to Input. How Much to Input. Methods of Vector Input. Methods of Raster Input. Remote Sensing as a Special Case of Raster Data Input. GPS data input. Secondary Data. Metadata and Metadata Standards. Terms. Review Questions. References. Chapter 6 Data Storage and Editing. Learning Objectives. Storage of GIS Databases. The Importance of Editing the GIS Database. Detecting and Editing Errors of Different Types. Entity Errors: Vector. Attribute Errors: Raster and Vector. Dealing with Projection Changes. Joining Adjacent Maps: Edge Matching. Conflations. Templating. Terms. Review Questions. References. UNIT 4. ANALYSIS: THE HEART OF THE GIS. Chapter 7. Elementary Spatial Analysis. Introduction to GIS Spatial Analysis. Learning Objectives. Preliminary Notes About Flowcharting. GIS Data Query. Locating and Identifying Spatial Objects. Defining Spatial Characteristics. Point Attributes. Line Attributes. Area Attributes. Working with Higher-Level Objects. Higher-Level Point Objects. Higher-Level Line Objects. Higher-Level Area Objects. Terms. Review Questions. References. Chapter 8. Measurement. Learning Objectives. Measuring Length of Linear Objects. Measuring Polygons. Calculating Polygon Lengths. Calculating Perimeter. Calculating Areas of Polygonal Features. Measuring Shape. Measuring Sinuosity. Measuring Polygon Shape. Measuring Distance. Simple Distance. Functional Distance. Terms. Review Questions. References. Chapter 9. Classification. Learning Objectives. Classification Principles. Elements of Reclassification. Neighborhood Functions. Roving Windows: Filters. Immediate Neighborhoods. Extended Neighborhoods. Buffers. Terms. Review Questions. References. Chapter 10. Statistical Surfaces. Learning Objectives. What Are Surfaces? Surface Mapping. Sampling the Statistical Surface. The DEM. Raster Surfaces. Interpolation. Linear Interpolation. Methods of Nonlinear Interpolation. Problems of Interpolation. Terrain Reclassification. Steepness of Slope. Azimuth or Orientation (Aspect). Shape or Form. Visibility and Intervisibility. Slicing the Statistical Surface. Cut And Fill. Terms. Review Questions. References. Chapter 11 Spatial Arrangement. Learning Objectives. Point, Area, and Line Arrangements. Point Patterns. Quadrat Analysis. Nearest Neighbor Analysis. Thiessen Polygons. Area Patterns. Distance and Adjacency. Other Polygonal Arrangement Measures. Linear Patterns. Line Densities. Nearest Neighbors and Line Intercepts. Directionality of Linear and Areal Objects. Connectivity of Linear Objects. Gravity Model. Routing and Allocation. The Missing Variable: Using Other Map Layers. Terms. Review Questions. References. Chapter 12. Comparing Variables Among Maps. Learning Objectives. The Cartographic Overlay. Point-In-Polygon and Line-In-Polygon Operations. Polygon Overlay. Automating the Overlay Process. Automating Point-in-Polygon and Line-in-Polygon Procedures in Raster. Automating Polygon Overlay in Raster. Automating Vector Overlay. Types of Vector Overlay. CAD-Type Overlay. Topological Vector Overlay. Topological Vector Point-in-Polygon and Line-in-Polygon Overlay. A Note about Error in Overlay. Dasymetric Mapping. Some Final Notes on Overlay. Terms. Review Questions. References. Chapter 13. Cartographic Modeling. Learning Objectives. Model Components. The Cartographic Model. Types Of Cartographic Models. Inductive and Deductive Modeling. Factor Selection. Model Flowcharting. Working Through the Model. Conflict Resolution. Some Example Cartographic Models. Model Implementation. Model Verification. Terms. Review Questions. References. UNIT 5. GIS OUTPUT. Chapter 14. The Output from Analysis. Learning Objectives. Output: The Display of Analysis. Cartographic Output. The Design Process. Map Design Controls. Nontraditional Cartographic Output. GIS on the Internet. Noncartographic Output. Interactive Output. Tables and Charts. Terms. Review Questions. References. UNIT 6. GIS DESIGN, APPLICATIONS, AND RESEARCH. Chapter 15. GIS Design. Learning Objectives. Analytical Model and Database Design. Spatial Processes and the Scope and Structure of the Model. Establishing the Effective Spatial Domain of the Model. GIS Tools for Solving Problems. Study Area. Scale, Resolution, and Level of Detail. Classification. Coordinate System and Projection. Selecting the Software. Institutional / System Design. System Design Principles. System Development Waterfall Model. Some General Systems Characteristics. The Institutional Setting for GIS operations. The System and the Outside World. Internal Players. External Players. Cost-Benefit Issues. GIS Information Products. How Information Products Drive the GIS. Organizing the Local Views. Avoiding Design Creep. View Integration. Terms. Review Questions. References. Chapter 16. GIS Applications. Learning Objectives. Archive Emphasizing Applications. Pattern Detection and Characterization Emphasizing Applications. Pattern Exploitation Emphasizing Applications. Pattern Comparison Emphasizing Applications. Space-Time Emphasizing Applications. Predictive Modeling Applications. Terms. Review Questions. References. Chapter 17. GIS Research. Learning Objectives. Geographic Representation (Including Ontology). Scale.

Abstract: The increased availability of mapped environmental data calls for better tools to analyze the spatial characteristics and information contained in those maps. Publicly available, user-friendly and universal tools are needed to foster the interdisciplinary development and application of methodologies for the extraction of image object information properties contained in digital raster maps. That is the overarching goal of GuidosToolbox, which is a set of customized, thematically grouped raster image analysis methodologies provided in a graphical user interface and for all popular operating systems. The Toolbox contains a wide selection of dedicated algorithms and tools, which are complemented by batch-processing and pre- and post-processing routines, all designed to objectively describe and quantify various spatial properties of image objects in digital raster data. While first developed for the analysis of remote sensing data in environmental applications, the Toolbox now provides a generic framew...

Abstract: Overview of the Book. Part One Image Processing. 1 Digital Image and Display. 1.1 What is a digital image? 1.2 Digital image display. 1.3 Some key points. Questions. 2 Point Operations (Contrast Enhancement). 2.1 Histogram modification and lookup table. 2.2 Linear contrast enhancement. 2.3 Logarithmic and exponential contrast enhancement. 2.4 Histogram equalization. 2.5 Histogram matching and Gaussian stretch. 2.6 Balance contrast enhancement technique. 2.7 Clipping in contrast enhancement. 2.8 Tips for interactive contrast enhancement. Questions. 3 Algebraic Operations (Multi-image Point Operations). 3.1 Image addition. 3.2 Image subtraction (differencing). 3.3 Image multiplication. 3.4 Image division (ratio). 3.5 Index derivation and supervised enhancement. 3.6 Standardization and logarithmic residual. 3.7 Simulated reflectance. 3.8 Summary. Questions. 4 Filtering and Neighbourhood Processing. 4.1 Fourier transform: understanding filtering in image frequency. 4.2 Concepts of convolution for image filtering. 4.3 Low-pass filters (smoothing). 4.4 High-pass filters (edge enhancement). 4.5 Local contrast enhancement. 4.6 *FFT selective and adaptive filtering. 4.7 Summary. Questions. 5 RGB-IHS Transformation. 5.1 Colour coordinate transformation. 5.2 IHS decorrelation stretch. 5.3 Direct decorrelation stretch technique. 5.4 Hue RGB colour composites. 5.5 *Derivation of RGB-IHS and IHS-RGB transformations based on 3D geometry of the RGB colour cube. 5.6 *Mathematical proof of DDS and its properties. 5.7 Summary. Questions. 6 Image Fusion Techniques. 6.1 RGB-IHS transformation as a tool for data fusion. 6.2 Brovey transform (intensity modulation). 6.3 Smoothing-filter-based intensity modulation. 6.4 Summary. Questions. 7 Principal Component Analysis. 7.1 Principle of PCA. 7.2 Principal component images and colour composition. 7.3 Selective PCA for PC colour composition. 7.4 Decorrelation stretch. 7.5 Physical-property-orientated coordinate transformation and tasselled cap transformation. 7.6 Statistic methods for band selection. 7.7 Remarks. Questions. 8 Image Classification. 8.1 Approaches of statistical classification. 8.2 Unsupervised classification (iterative clustering). 8.3 Supervised classification. 8.4 Decision rules: dissimilarity functions. 8.5 Post-classification processing: smoothing and accuracy assessment. 8.6 Summary. Questions. 9 Image Geometric Operations. 9.1 Image geometric deformation. 9.2 Polynomial deformation model and image warping co-registration. 9.3 GCP selection and automation. 9.4 *Optical flow image co-registration to sub-pixel accuracy. 9.5 Summary. Questions. 10 *Introduction to Interferometric Synthetic Aperture Radar Techniques. 10.1 The principle of a radar interferometer. 10.2 Radar interferogram and DEM. 10.3 Differential InSAR and deformation measurement. 10.4 Multi-temporal coherence image and random change detection. 10.5 Spatial decorrelation and ratio coherence technique. 10.6 Fringe smoothing filter. 10.7 Summary. Questions. Part Two Geographical Information Systems. 11 Geographical Information Systems. 11.1 Introduction. 11.2 Software tools. 11.3 GIS, cartography and thematic mapping. 11.4 Standards, interoperability and metadata. 11.5 GIS and the Internet. 12 Data Models and Structures. 12.1 Introducing spatial data in representing geographic features. 12.2 How are spatial data different from other digital data? 12.3 Attributes and measurement scales. 12.4 Fundamental data structures. 12.5 Raster data. 12.6 Vector data. 12.7 Conversion between data models and structures. 12.8 Summary. Questions. 13 Defining a Coordinate Space. 13.1 Introduction. 13.2 Datums and projections. 13.3 How coordinate information is stored and accessed. 13.4 Selecting appropriate coordinate systems. Questions. 14 Operations. 14.1 Introducing operations on spatial data. 14.2 Map algebra concepts. 14.3 Local operations. 14.4 Neighbourhood operations. 14.5 Vector equivalents to raster map algebra. 14.6 Summary. Questions. 15 Extracting Information from Point Data: Geostatistics. 15.1 Introduction. 15.2 Understanding the data. 15.3 Interpolation. 15.4 Summary. Questions. 16 Representing and Exploiting Surfaces. 16.1 Introduction. 16.2 Sources and uses of surface data. 16.3 Visualizing surfaces. 16.4 Extracting surface parameters. 16.5 Summary. Questions. 17 Decision Support and Uncertainty. 17.1 Introduction. 17.2 Decision support. 17.3 Uncertainty. 17.4 Risk and hazard. 17.5 Dealing with uncertainty in spatial analysis. 17.6 Summary. Questions. 18 Complex Problems and Multi-Criteria Evaluation. 18.1 Introduction. 18.2 Different approaches and models. 18.3 Evaluation criteria. 18.4 Deriving weighting coefficients. 18.5 Multi-criteria combination methods. 18.6 Summary. Questions. Part Three Remote Sensing Applications. 19 Image Processing and GIS Operation Strategy. 19.1 General image processing strategy. 19.2 Remote-sensing-based GIS projects: from images to thematic mapping. 19.3 An example of thematic mapping based on optimal visualization and interpretation of multi-spectral satellite imagery. 19.4 Summary. Questions. 20 Thematic Teaching Case Studies in SE Spain. 20.1 Thematic information extraction (1): gypsum natural outcrop mapping and quarry change assessment. 20.2 Thematic information extraction (2): spectral enhancement and mineral mapping of epithermal gold alteration, and iron ore deposits in ferroan dolomite. 20.3 Remote sensing and GIS: evaluating vegetation and land-use change in the Nijar Basin, SE Spain. 20.4 Applied remote sensing and GIS: a combined interpretive tool for regional tectonics, drainage and water resources. Questions. References. 21 Research Case Studies. 21.1 Vegetation change in the three parallel rivers region, Yunnan province, China. 21.2 Landslide hazard assessment in the three gorges area of the Yangtze river using ASTER imagery: Wushan-Badong-Zogui. 21.3 Predicting landslides using fuzzy geohazard mapping an example from Piemonte, North-west Italy. 21.4 Land surface change detection in a desert area in Algeria using multi-temporal ERS SAR coherence images. Questions. References. 22 Industrial Case Studies. 22.1 Multi-criteria assessment of mineral prospectivity, in SE Greenland. 22.2 Water resource exploration in Somalia. Questions. References. Part Four Summary. 23 Concluding Remarks. 23.1 Image processing. 23.2 Geographical information systems. 23.3 Final remarks. Appendix A: Imaging Sensor Systems and Remote Sensing Satellites. A.1 Multi-spectral sensing. A.2 Broadband multi-spectral sensors. A.2.1 Digital camera. A.2.2 Across-track mechanical scanner. A.2.3 Along-track push-broom scanner. A.3 Thermal sensing and thermal infrared sensors. A.4 Hyperspectral sensors (imaging spectrometers). A.5 Passive microwave sensors. A.6 Active sensing: SAR imaging systems. Appendix B: Online Resources for Information, Software and Data. B.1 Software - proprietary, low cost and free (shareware). B.2 Information and technical information on standards, best practice, formats, techniques and various publications. B.3 Data sources including online satellite imagery from major suppliers, DEM data plus GIS maps and data of all kinds. References. General references. Image processing. GIS. Remote sensing. Part One References and further reading. Part Two References and further reading. Index.