University:
California State University, Northridge
Course:
GEOG 206/L | Introduction to Geographical Information Science and Lab
Academic year:

2009
Views:

102

Pages:

31
Author:

Kade Blevins

Lecture 3 GIS Data Models, Data Formats, ArcCatalog and Data Management Outline ► GIS Data Models Vector Raster ► GIS Data Formats ► Data Structure ► The Geodatabase ► ArcCatalog ► Data Management Representing Physical Entities ► In a GIS, physical entities such as lakes, roads or vegetation type are represented in a simplified fashion by spatial features (i.e. polygons or lines). ► The spatial objects that represent an entity are determined by the person or organization creating the data based on: 1. The intended use of the data 2. The desired level of detail and accuracy. So what are Data Models? ► The objects in a spatial database plus the relationships among them. ► Provides a formal means of representing and manipulating spatial information. ► Two types of data are used to represent entities: 1. Coordinate or geometric data 2. Attribute data Coordinate or Geometric Data ► Used to define the spatial location and extent. ► Frequently consists of a pair of numbers. ► 1 or many pairs of coordinates represent the shapes and boundaries that define objects. Attribute Data ► ► ► Use to capture non-spatial aspects of an entity. Most often contained in a table Attributes can be categorized as: Nominal: Provide descriptive info. Ex. Color, names, types of soil. No implied order, size of quantity. Ordinal: Imply rank order or scale. Does not represent differences in scale. Ex. Descriptive (short, medium, long) or numeric (1-100). Interval/Ratio: Where both order and absolute differences in magnitude are represented. Ex. Length, weight, height or depth. GIS Data Models ► Common Vector Raster Spatial Data Models Vector Spatial Data Models ► ► ► Points – A coordinate pair Lines (arcs) – Ordered set of coordinate pairs that begin and end with a node. Polygons (feature with area) – Ordered set of connected lines. Spaghetti Vector Data Models ► Early vector model ► Unstructured – Does not record or enforce connections between line segments or shared polygon boundaries. ► Results in inefficient and inaccurate analysis. ► Usually upgraded to a topological data model Topological Vector Data Models ► Topology: The study of geometric properties that do not change when the forms are bent, stretched or undergo similar transformations. Captures the relationship between features. ► 3 Types of Relationships: Adjacency Connectivity Containment Advantages and Disadvantages of Topological Vector Data Models Advantages: ► Familiar and intuitive representation for many kinds of data ► Efficient (in terms of memory and computing) representation for relatively sparse data ► Offers very good resolution of linear and point features ► Facilitates TOPOLOGICAL ANALYSIS Disadvantages of Vector Data Model: ► Compute-intensive when working with multiple overlays ► Not good at representing continuous surface Raster Spatial Data Models Defines the world as a set of cells in a grid pattern. Raster Cells Raster Compression ► ► With raster data, we must deal with storing data differently than vector to reduce volume. The dominant data compression techniques are: run length coding quad tree compression Advantages and Disadvantages of the Raster Data Model Advantages of a raster data model: • Very efficient for processing and analyzing multiple overlays (different thematic layers) • More accurate and natural representation for continuous, smoothly-varying information (such as topography) • Constant cell size and regular geometry facilitate some analysis and modeling tasks--computing areas, for example, is just counting cells. • Best for use with probabilistic modeling Disadvantages of raster data model: • Data volume and redundancy -- dense grid of data involves large memory requirements and computer power. • Difficult to resolve fine details (little to no variation of values of large area) better captured by vector data. = OR Vector vs. Raster Data Models ► Choice depends on conditions and type of data you are trying to model. Triangulated Irregular Networks (TIN’s) Used to display and analyze surfaces. ► Contain irregularly spaced points that have x,y coordinates describing their location and a z-value that describes the surface at that point. ► Can be created from several types of data including rasters, and point, ► line, and polygon feature classes that have z-coordinate values. Elevation Based TIN Vector vs. Raster vs. TIN’s Digital Elevation Example GIS Data Formats ► Types of files used to store and transfer spatial data. ► Most common file formats Shapefiles – Vector Coverages - Vector Geodatabases - Vector and Raster Grids – Raster Images (Ex. Tiff’s, Jpeg’s, etc) – Raster Common File Formats Shapefiles ► A shapefile is a feature class—it stores a collection of features that have the same geometry type (point, line, or polygon), the same attributes, and a common spatial extent ► File-based data format native to ArcView® 3.x software Viewed using a File Explorer Viewed in ArcCatalog Coverages ► ► ► ► Coverages have a geometry type of point, line, OR polygon and represent a single thematic layer. A file-based data format native to ESRI's ArcInfo® Workstation software. The attributes and spatial relationships associated with a coverage feature class are stored in INFO-format tables. ALWAYS use ArcCatalog to move, edit or delete coverages. Geodatabases ► ► ► The geodatabase is a container for storing spatial and attribute data and the relationships that exist among them Format introduced by ESRI with ArcGIS® software Primary format we will be working with in this class. Icons identify feature types Geodatabases and Data Organization ► Geodatabases can consist of: Feature Datasets Feature Classes Annotation Feature Classes Raster Datasets Nonspatial Tables Types of Geodatabases Scalable Functionality ► 3 Types: File Geodatabases: Stored as folders in a file system. Each dataset holds up to 1 TB of data. Fast performance, less restrictive editing locks and supported by many platforms. ► Personal Geodatabases: Stored within Microsoft Access. Holds up to 2 GB of data. ArcSDE Geodatabases: Stored in a relational database using Oracle, Microsoft SQL Server, IBM DB2, or IBM Informix. Requires the use of ArcSDE software. Unlimited in size and numbers of users. ArcCatalog The application for browsing, managing and documenting geographic data. ► Create connections to drives that store data and maps. ► Utilize drag and drop functionality to interface with ArcMap. ► Catalog Tree Preview Pane ArcCatalog: Data Connections Direct Connect ArcCatalog: Metadata ► Data about data ► Provides information about a dataset ► Certain properties generated automatically ► Other properties require manual entry Data Management ► Know where your data is! ► Best location is on the root of the C or D drive. ► Stay away from spaces in folder or file names. Use “_” instead. ► Limit characters ► Create folders as needed to keep data organized! Data Management (Cont.) Data is stored separately from the ArcMap document (.mxd file). ► If you move the ArcMap document, the data does NOT go with it. ► If you move or rename the data layers OR the folders they are stored in, the ArcMap document will NOT know where to find them. Use ► Updating the Data Source ► ► ► When layer is grayed out, click on “Layer Properties”. Click “Set Data Source…” Navigate to current location of data.

GIS Data Models, Data Formats, Arccatalog and Data Management

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