Spatial (coordinate) data model Relational (tabular) data model Introduction to GIS Overview Spatial (coordinate) data model Relational (tabular) data model Scale issues Sample data _ © Phil Hurvitz, 1999-2000

GIS are driven by spatial data Spatial Data Model GIS are driven by spatial data 2 basic spatial data models exist vector points lines polygons raster grid cells (images, bitmaps, DEMs) _ © Phil Hurvitz, 1999-2000

Characteristics of the vector data model: Features positioned accurately Shape of features represented correctly Features represented discretely (no fuzzy boundaries) Complex data structure (especially for polygons) _ © Phil Hurvitz, 1999-2000

Points: represent discrete point features Vector Data Model Points: represent discrete point features © Phil Hurvitz, 1999-2000

Lines: represent linear features Vector Data Model Lines: represent linear features © Phil Hurvitz, 1999-2000

Lines: represent linear features Vector Data Model Lines: represent linear features Lines start and end at nodes line #1 goes from node #2 to node #1 Vertices determine shape of line _ © Phil Hurvitz, 1999-2000

Polygons: represent bounded areas Vector Data Model Polygons: represent bounded areas © Phil Hurvitz, 1999-2000

Polygons: represent bounded areas Vector Data Model Polygons: represent bounded areas Polygon #2 is bounded by lines 1 & 2 Line 2 has polygon 1 on left and polygon 2 on right _ © Phil Hurvitz, 1999-2000

Polygons: represent bounded areas Vector Data Model Polygons: represent bounded areas complex data model “arc/node topology” _ © Phil Hurvitz, 1999-2000

Types (formats) of vector data available in ArcView Vector Data Model Types (formats) of vector data available in ArcView ArcView shapefiles ArcInfo coverages and libraries CAD files (AutoCAD DWG, DXF; Microstation DGN) StreetMap files Spatial Database Engine (SDE) data ASCII point coordinate data _ © Phil Hurvitz, 1999-2000

A relatively new vector data format Preferred in ArcView Draws fast Vector Data Model ArcView shapefiles A relatively new vector data format Preferred in ArcView Draws fast Fully editable in ArcView Simple in structure Does not use arc-node topology “Connected” lines do not necessarily share a common node Adjacent polygons do not share common bounding arcs Data sets are either point or line or polygon _ © Phil Hurvitz, 1999-2000

A commonly found format Data model more complex Vector Data Model ArcInfo coverages A commonly found format Data model more complex Draws more slowly in ArcView Coordinate data not editable in ArcView Can be used in both ArcView and ArcInfo Polymorphic Problematic file structure (more on this later in the term) _ © Phil Hurvitz, 1999-2000

AutoCAD & Microstation CAD drawing data Vector Data Model AutoCAD & Microstation CAD drawing data CAD data are very common (industry standard) DXF, DWG, and DGN formats supported in ArcView Coordinate data not editable in ArcView Frequently contain “sloppy” data No enforced topology rules Gaps in data Frequently contain little or no useful attribute data _ © Phil Hurvitz, 1999-2000

Easy to obtain from a variety of sources GPS Traverse Vector Data Model ASCII coordinate data Easy to obtain from a variety of sources GPS Traverse Direct reading from maps OS, architecture, and application independent © Phil Hurvitz, 1999-2000

Characteristics of the raster data model: Rectangular grid of square cells Shape of features generalized by cells Continuous (surface) data represented easily Simple data structure _ © Phil Hurvitz, 1999-2000

Raster data are good at representing continuous phenomena Raster Data Model Raster data are good at representing continuous phenomena Wind speed Elevation, slope, aspect Chemical concentration Likelihood of existence of a certain species Electromagnetic reflectance (photographic or satellite imagery) _ © Phil Hurvitz, 1999-2000

Raster spatial data model Raster Data Model Raster spatial data model origin is set explicitly cell size is known cell references (row/column locations) are known cell values are referenced to row/column location values represent numerical phenomena or index codes for non-numerical phenomena _ © Phil Hurvitz, 1999-2000

A few different types of raster data Raster Data Model A few different types of raster data digital orthophoto digital elevation model (DEM) _ © Phil Hurvitz, 1999-2000

Relational Database Model & Attribute Data Structures The “where” of GIS is determined by coordinate (map) data structures, but … The “what” of GIS is determined by tabular (relational database) data structures Thus, tabular data are just as important as coordinate data _ © Phil Hurvitz, 1999-2000

Relational Database Model & Attribute Data Structures Attribute data are stored in database tables. Tables are composed of: fields and records _ © Phil Hurvitz, 1999-2000

Relational Database Model & Attribute Data Structures You may already be familiar with relational databases dBase rBase Access Excel (database functionality) Oracle, INFORMIX, INGRES, SQL Server INFO (in ArcInfo) _ © Phil Hurvitz, 1999-2000

Relational Database Model & Attribute Data Structures ArcView uses tabular data formats from dBase, ASCII text, and INFO files tables are stored on the disk as .dbf, .txt, or in INFO directories _ © Phil Hurvitz, 1999-2000

Relational Database Model & Attribute Data Structures Tables can be linked and joined (“related”) by use of common values in fields © Phil Hurvitz, 1999-2000

Relational Database Model & Attribute Data Structures Different types of attribute tables in ArcView Vector point attribute tables polygon attribute line attribute node attribute* text attribute* route & event tables* Raster value attribute _ * in ArcInfo coverage data only © Phil Hurvitz, 1999-2000

Relational Database Model & Attribute Data Structures Relationship between tabular and map data one-to-one between features and records _ © Phil Hurvitz, 1999-2000

Scale of data plays an important role, and frequently causes problems Scale Issues Scale of data plays an important role, and frequently causes problems Be aware of: Data’s source scale Mixing data from different source scales Appropriateness of output scale _ © Phil Hurvitz, 1999-2000

Map measurement and true ground measurement Scale Issues Map measurement and true ground measurement A 1/40th in line on a 1:24,000 scale map is 50 ft on the ground A .30 mm line on a 1:200,000 scale map is almost 2,000 ft on the ground _ © Phil Hurvitz, 1999-2000

Data from different sources and scales can vary widely Scale Issues Data from different sources and scales can vary widely 1:100,000 scale data from USGS DLG © Phil Hurvitz, 1999-2000

Data from different sources and scales can vary widely Scale Issues Data from different sources and scales can vary widely 1:1,000,000 scale data from DCW (DMA) © Phil Hurvitz, 1999-2000

Data from different sources and scales can vary widely Scale Issues Data from different sources and scales can vary widely 1:2,000,000 scale data from USGS DLG © Phil Hurvitz, 1999-2000

Beware of scale statements Scale Issues Beware of scale statements “one to two-hundred”: does this mean one inch on the map equals 200 inches on the ground? or one inch on the map equals 200 feet on the ground? _ © Phil Hurvitz, 1999-2000

Pack Forest GIS database Course Sample Data Pack Forest GIS database Original data sources Legacy maps USGS digital line graphs DNR data GPS surveys Digital orthophoto interpretation _ © Phil Hurvitz, 1999-2000

Pack Forest GIS database Course Sample Data Pack Forest GIS database CD directory pfdata Forest stands Streams Roads, trails Soils Elevation contours Culverts Forest inventory data Digital orthophotos Digital elevation model … _ © Phil Hurvitz, 1999-2000

Course Sample Data ESRI Sample Data CD directory esridata Worldwide data sets countries major rivers United States data states counties cities rivers roads Canada Mexico _ © Phil Hurvitz, 1999-2000

Projection STATEPLANE Sample Data Pack Forest GIS database projection & coordinate definition Unless otherwise specified, Projection STATEPLANE Washington South Zone (State Plane 5626 or FIPSZone 4602) Datum HPGN (a.k.a. NAD83/91) Units FEET Spheroid GRS1980 _ © Phil Hurvitz, 1999-2000