1. GIS is composed of layers Layers –land/water –roads –urban areas –pollution levels Data can be represented by VECTORS, or Data can be represented by RASTERS

2. Vector and Raster Data Models

3. Vector Data Model Discrete –Boundaries are well defined (x,y coordinates) Geographic features are represented as: Points Lines Polygons Every object is given a location

4. Types of Vector Data Models Georelational (e.g. shapefiles) –Spatial and attribute stored separately “geo” – graphic/spatial part “relational” – database part (tabular) Classical approach to vector data Object-based (oriented) (e.g. geodatabase) Spatial and tabular component are stored as a single system Spatial features can have properties and methods Recent trend towards object-based model

5. Vector Data File Types Shapefiles – georelational Coverage – georelational Geodatabase – object-based (oriented) DXF Digital Exchange Format (Autocad) ASCII w/binary code maintains layers DLG Digital Line Graph - USGS (1:100,000 & 1:24,000) ASCII

6. Maps as numbers Binary 0000 1111 –Eight bits in a row are termed a byte –256 combinations or 0 to 255 ASCII text- American Standard Code for Information Interchange - 256 standard meanings for the values that fall into one byte. (letters, numbers, special characters) –http://www.asciitable.com/http://www.asciitable.com/

7. Shapefiles (~1990) Most common vector data format Openly published files specs – non proprietary Simple file structure –3 main files with same name but different 3 letter extension LocalStreets.shp LocalStreets.dbf LocalStreets.shx –Attribute data stored in a dBase file (.dbf) –Geometry and location data stored in the.shp file –The.shx provides the “glue” Does not support true topology

8. Topology – Spatial Relationships Study of geometric properties that do not change when forms are bent, stretched, etc… Knowledge about relative spatial positioning of features –How are features connected and which features are adjacent to each other –Directed lines are called arcs (have length and direction) –Points where arcs meet or intersect are called nodes arc node

9. Raster Data Model The world is composed of cells/pixels arranged in a grid Each cell/pixel is assigned a numeric value –Integer – (no decimal) –Floating-point (decimal) (However data may be represented by codes) The size of the cell/pixel determines the resolution Every location given an object

11. Creating A Raster Overlay grid on real world give each cell a value

12. Cell Values Assume only one value per cell in any given layer How do you decide what value to give the cell? –Value of greatest proportion? –Value of the most important feature? –Some systems allow for percent composition, edge effect

14. Characteristics of a Raster Resolution –smallest unit discernible –often grid size, but not always Orientation –angle that grid makes with true north Value –information stored in cell

15. Characteristics of a Raster Zones –areas of continuous values e.g. county, land parcels, etc. Class - term used to describe all the zones of same value in a layer –e.g. state parks

16. Characteristics of a Raster Location –each cell has a unique location often defined by bottom left corner X, Y coordinate

18. Raster Data Structure and Compression –Lossless – no information is lost –Lossy – information is degraded How is the raster data stored? –Cell-by-cell Encoding - data not compressed –Run-Length Encoding – data compressed –Quad Tree – data compressed –Wavelet – data compressed (lossy)

19. Storing the Information Full length encoding –store every single cell’s value individually

20. Storing the Information Run Length encoding –compress data

21. Storing the Information Quadtree Encoding – compress data e.g. 0 and 2 are homogenous And 1 and 3 are broken down further

22. Types of Raster Data Remotely Sensed Images –Satellite Landsat (http://landsat.usgs.gov/)(http://landsat.usgs.gov/) AVHRR (http://edc.usgs.gov/products/satellite/avhrr.html)(http://edc.usgs.gov/products/satellite/avhrr.html) SPOT (http://www.spot.com/)(http://www.spot.com/) –Digital Elevation Models (DEMs) U.S. Geologic Survey (USGS) DEMs LIDAR (light detection and ranging) Multibeam sonar (acoustics for capturing depth information) –Digital Orthophotos

23. Types of Raster Data – Images Digital Raster Graphics (DRGs) –Scanned USGS topographic maps (http://topomaps.usgs.gov/drg/) (http://topomaps.usgs.gov/drg/) Graphic Image Files – historic aerial photos, scanned paper maps –.tif (Tagged Image File Format) –sid (LizardTech MrSID) –.img (ERDAS Imagine) –.jpg (Joint Photographic Experts Group). Many packages work on RECTIFYING these images photograph’s scale is not constant across image Associated world file provides geo- reference.

24. Raster Data Formats –ESRI Grids Proprietary format Discrete – integer (whole number) Continuous – floating point (number with decimals)

25. Raster and Vector Summary Vectors have advantage of accuracy but not good with continuous fields Vectors were used first - digitizing Earliest include ASCII (x,y coordinates but got too large) then binary took over. Raster not good with lines or points but good with continuous coverage areas. Raster has the mixed pixel problem.

26. Raster Advantages: Simple data structure Compatible with remotely sensed or scanned data Simpler spatial analysis procedures Raster Disadvantages: Requires greater storage space on computer Depending on pixel size, graphical output may be less pleasing Projection transformations are more difficult (and can be time consuming) More difficult to represent topological relationships Positional precision set by cell size

27. Vector Advantages Requires less disk storage space Topological relationships are readily maintained Graphical output more closely resembles hand-drawn maps Preferred for network analysis Vector Disadvantages More complex data structure Not as compatible with remotely sensed data Software and hardware are often more expensive Some spatial analysis procedures may be more difficult Overlaying multiple vector maps is often time consuming

28. Triangulated Irregular Networks TIN A data model commonly used to represent terrain heights. TIN forms a connected network of triangles It is not a raster or vector format