Czech Technical University in Prague Faculty of Transportation Sciences Department of Transport Telematics Doc. Ing. Pavel Hrubeš, Ph.D. Geographical Information Systems

Actuality Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics  Presentations for download 

Rehearsal  GIS  Users, experts  Hardware  Software, analytical methods  Databases  Visualization  Modeling  Capturing  Storage  Modeling of real world  Digital version of real and virtual objects  Selection of objects or phenomena  Identification of objects  Definition of way of representation  Transformation rules  GIS data model  Recording of data into database Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics

Physical representation Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics

Recording of spatial information Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics  Raster Images  “pixels”  satellite images  aerial photos

Raster data Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics  Raster is a method for the storage, processing and display of spatial data. Each area is divided into rows and columns, which form a regular grid structure.  The spatial location of each cell is implicitly contained within the ordering of the matrix, unlike a vector structure which stores topology explicitly.  Areas containing the same attribute value are recognized as such, however, raster structures cannot identify the boundaries of such areas as polygons.

Raster data Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics

Raster data - grid size and resolution Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics  In raster GIS the pixel equivalent is usually referred to as a cell element or grid cell. Pixel/cell refers to the smallest unit of information available in an image or raster map. This is the smallest element of a display device that can be independently assigned attributes such as color.  Pixel size and number of rows and columns: "The size of the pixel must be half of the smallest distance to be represented" Star and Estes (1990)

Raster data - raster data structures Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics  exhaustive enumeration  In this data structure every pixel is given a single value, hence there is no compression when many like values are encountered.

Raster data - raster data structures Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics  run-length encoding  This is a raster image compression technique. If a raster contains groups of cells with identical values, run length encoding can compress storage. Instead of storing each cell, each component stores a value and a count of cells with that value. If there is only one cell the storage doubles, but for three or more cells there is a reduction.

Recording of spatial information Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics  Vector data model  features: points, lines & polygons  attributes: size, type, length, etc.

Vector data Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics  Vector is a data structure, used to store spatial data. Vector data is comprised of lines or arcs, defined by beginning and end points, which meet at nodes.  The locations of these nodes and the topological structure are usually stored explicitly.  Features are defined by their boundaries only and curved lines are represented as a series of connecting arcs.

Vector data Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics  co-ordinate Pairs of numbers expressing horizontal distances along orthogonal axes, or triplets of numbers measuring horizontal and vertical distances, or n- numbers along n-axes expressing a precise location in n-dimensional space. Co-ordinates generally represent locations on the earth's surface relative to other locations.  point A zero-dimensional abstraction of an object represented by a single X,Y co-ordinate. A point normally represents a geographic feature too small to be displayed as a line or area; for example, the location of a building location on a small-scale map, or the location of a service cover on a medium scale map.  line A set of ordered co-ordinates that represent the shape of geographic features too narrow to be displayed as an area at the given scale (contours, street centrelines, or streams), or linear features with no area (county boundary lines). A lines is synonymous with an arc.  polygon A feature used to represent areas. A polygon is defined by the lines that make up its boundary and a point inside its boundary for identification. Polygons have attributes that describe the geographic feature they represent.

Vector data Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics x Node Vertex y points lines areas

Rehearsal  Vector Data  Advantages :  Data can be represented at its original resolution and form without generalization.  Graphic output is usually more aesthetically pleasing (traditional cartographic representation);  Since most data, e.g. hard copy maps, is in vector form no data conversion is required.  Accurate geographic location of data is maintained.  Allows for efficient encoding of topology, and as a result more efficient operations that require topological information, e.g. proximity, network analysis.  Disadvantages:  The location of each vertex needs to be stored explicitly.  For effective analysis, vector data must be converted into a topological structure. This is often processing intensive and usually requires extensive data cleaning. As well, topology is static, and any updating or editing of the vector data requires re-building of the topology.  Algorithms for manipulative and analysis functions are complex and may be processing intensive. Often, this inherently limits the functionality for large data sets, e.g. a large number of features.  Continuous data, such as elevation data, is not effectively represented in vector form. Usually substantial data generalization or interpolation is required for these data layers.  Spatial analysis and filtering within polygons is impossible  Raster Data  Advantages:  The geographic location of each cell is implied by its position in the cell matrix. Accordingly, other than an origin point, e.g. bottom left corner, no geographic coordinates are stored.  Due to the nature of the data storage technique data analysis is usually easy to program and quick to perform.  The inherent nature of raster maps, e.g. one attribute maps, is ideally suited for mathematical modeling and quantitative analysis.  Discrete data, e.g. forestry stands, is accommodated equally well as continuous data, e.g. elevation data, and facilitates the integrating of the two data types.  Grid-cell systems are very compatible with raster- based output devices, e.g. electrostatic plotters.  Disadvantages:  The cell size determines the resolution at which the data is represented.;  It is especially difficult to adequately represent linear features depending on the cell resolution. Accordingly, network linkages are difficult to establish.  Processing of associated attribute data may be cumbersome if large amounts of data exists. Raster maps inherently reflect only one attribute or characteristic for an area.  Since most input data is in vector form, data must undergo vector-to-raster conversion. Besides increased processing requirements this may introduce data integrity concerns due to generalization and choice of inappropriate cell size.  Most output maps from grid-cell systems do not conform to high-quality cartographic needs. Czech Technical University in Prague - Faculty of Transportation Sciences Department of Control and Telematics

Advantages/disadvantages of raster and vector data models Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics rastervector precision in graphics xv traditional cartography xv data volume xv topology xv computation vx update vx continuous space vx integration vx discontinuous xv

Recording of attribute information Czech Technical University in Prague - Faculty of Transportation Sciences Department of Transport Telematics  Record in graphical part (raster format)  Spatial and attribute part divided to two records  Common in files (ESRI shapefiles)  Necessary to use unique identifiers  Spatial and attribute part together in one record  Databases