Environmental GIS Nicholas A. Procopio, Ph.D, GISP

Data Types In GIS, there are three main types of data Spatial Attribute Metadata Zygo, Lisa, Baylor University, Lecture Notes, 2002

Data Sources Data Types Primary – Measurements collected through first- hand observations Secondary – Measurements collected through a secondary source (i.e., neighborhood surveys)

Metadata Data documentation Data about the data Explains the form, content, accuracy, precision, usability, creator, purpose, etc. Metadata standards exist Metadata is a part of geospatial data

Metadata Metadata information includes Identification – title, area, dates, owners, organizations, etc. Data quality – attribute accuracy and spatial precision, consistency, sources of info, and methods of data production Spatial data organization – raster-vector format and organization of features in the data set, data model Spatial reference – map projections, datums, and coordinate system

Metadata Metadata is created to… Protect investment in data Staff turnover, memory loss Makes it easier to reuse and update data Provides documentation of sources, quality Easier to share data Helping the user understand the data Provides consistent terminology Focuses on key elements Helps user determine fitness for use Facilitates data transfer, interpretation by new users

Federal Geographic Data Committee Under Executive Order No , all federal agencies and organizations must document their geospatial data using the FDGC Content Standard for Digital Geospatial Metadata

Federal Geographic Data Committee Compliance with this executive order will… Minimize duplication of data Foster cooperative digital data collection activities Establish a national framework of quality data

Metadata Use ArcCatalog to create and edit metadata

Database Models Database – a collection of non-redundant data, which can be shared by different application systems Geographic database – database linked to geographic data for a particular area and subject.

Attribute Data The “where” of GIS is determined by the spatial data The “what” is determined by the attribute data The attribute data is just as important as the spatial data

Databases Attribute data are stored in database tables

Databases Advantages of a DBMS include Reduced redundancy of data duplication Various data access methods are possible (queries) Data is stored independently of the application for which they will be used Access to data is controlled and data is centralized Ease of updating and maintaining data

Creating a database Consider the following… Storage media How will the database change over time? What security is needed? Should the database be distributed or centralized? How should database creation be scheduled?

Codd’s Principles for Databases Only one value per cell All values in a column are about the same subject Each row is unique No significance to the sequence of columns No significance to the sequence of rows Keep your table simple!

Types of Databases Relational Presents data organized in a series of two- dimensional tables, each containing records for one entity

Relational Database Flexible approach to linkages between records comes closest to modeling the complexity of spatial relationships between objects Links attributes contained in separate files with a key attribute The key attribute is usually a non-redundant, unique identification number for each record The most popular DBMS model for GIS

Data Most data is input into a database by keycoding Other data may be obtained through government sources USGS US Census NOAA State Agencies Data may also be obtained from other projects

Methods of Spatial Data Entry Manual “heads-up” digitizing Manual “heads-up” digitizing Scanners Scanners Appropriate for encoding raster data since this is the output format for most scanners.Appropriate for encoding raster data since this is the output format for most scanners. Problems may includeProblems may include Scanning unwanted information Scanning unwanted information Optical distortion Optical distortion The higher the resolution, the more volume of data produced The higher the resolution, the more volume of data produced

Methods of Spatial Data Entry Electronic Data Transfers Downloading data from the internet Downloading data from a GPS unit Consider when obtaining electronic data What data is available Cost Media Format

Sources of Electronic Data United States Geological Survey (USGS) Digital Line Graphs (DLG) Digital Elevation Models (DEM) Digital Orthophoto Quads (DOQ) United States Census Bureau (USCB) Topologically Integrated Geographic Encoding Reference System (TIGER) First comprehensive GIS database at street level for entire U.S. National Oceanographic and Atmospheric Agency (NOAA) Satellite and radar images Bathymetry maps

Other Sources of Spatial Data Field Data Global Positioning System (GPS) Locating position from receiving a signal from orbiting satellites Manual Input Remote Sensing Utilizing satellite images to develop a base view of area of interest

Spatial Data Models

Spatial Databases Real world is infinitely complex Database size is limited Data model converts real world into elements that can be stored in a database

Toward Realism: Layers A GIS breaks down reality into different layers (themes) A layer can be composed of identical entities such the locational information for trees, manholes, buildings, etc. Layers can be overlapped to show the spatial relationship between various entities Layers can also represent different times

Spatial Databases There are two primary models for spatial data in a GIS Raster a data structure or model based on grid cells Vector a data structure composed of nodes, vertices, and arcs or connected points

Raster Data Models Individual cells are used as the building blocks for creating point, line, and polygon entities Size of the cell very important because it will reflect how entities are displayed (i.e., more specific shape with greater number of cells). Cell represents some attribute or a reference ID to a table of attributes

Raster Spatial Databases Single objects displayed by shading individual cells Linear features displayed by shading a sinuous series of connected cells Polygon features displayed by shading a group of connected cells Relief can be shown by assigning a certain value to each selected cell

Raster Data Model Raster data are ideal for continuous data such as air temperatures, water pH, etc. What happens when two categories occupy the same cell?

Raster Data Models Cells may be homogenous (each cells contains the same feature) or heterogeneous (one cell contains varying features) Heterogeneity may be resolved by Simply looking for the presence or absence of features Looking at the cell center to determine placement of index code Dominant area analysis Transition cells Percentages

Spatial Databases Advantages of Raster Format Simple data structure Compatible with remotely sensed or scanned data Simple spatial analysis procedures

Spatial Databases Disadvantages of Raster Format Requires large storage space Graphical output may be less pleasing (depending on resolution) Projection transformations more difficult Difficult to maintain topology

Vector Spatial Databases Vector data models arose in the early 1960’s in relation to the development of the hierarchical attribute data structure The first generation were simply lines with an arbitrary start and ending point Files would typically consist of a few long lines and many short lines Often referred to as cartographic spaghetti

Spatial Databases Vector Data Model Uses two-dimensional Cartesian coordinates to store the shape of a spatial entity. The point is the basic building block from which all other spatial entities are constructed. Lines and areas are constructed by connecting a series of points

Vector Data Models Uses two-dimensional Cartesian coordinates to store the shape of a spatial entity. The point is the basic building block from which all other spatial entities are constructed. Lines and areas are constructed by connecting a series of points (nodes and vertices)

Vector Spatial Databases Advantages Requires less storage space Topology easily maintained Graphical output usually more pleasing

Vector Spatial Databases Disadvantages More complex data structure Not compatible with remotely sensed data Spatial analysis operations more difficult Selecting appropriate number of points to display feature Too few points would compromise shape or spatial properties (area, perimeter, etc.) Too many points means possible data duplication and increase costs in terms of data storage

Advancing Toward Topology The arc/node model developed as a “hierarchy” for spatial data Based on the principle that each type of structure consists of features built upon simpler features Coordinates make up points Connected points make lines Connected lines make polygons Allows the user to differentiate between points, line, and polygons, but requires maintenance of links between features

Topologic Models This new model allowed for drawing a line only once For example: If two polygons shared a side, that shared side would have to be traced when both polygons were drawn This would allow for the possibility of gaps or slivers between the individual lines (topological error) The new system avoided the error because the one arc “told” which polygon was to the left and which polygon was on the right

Topological Terms Nodes Where a line begins, ends, or where two lines intersect Vertices Where a line bends Arcs Line segment between two nodes Nodes Vertices Arcs

Topology Example Topology not attained! Sliver Topology is attained!

Summary of Data Models Real World Raster Windmills 0 = No Data 1 = Windmill Vector Windmills

Summary of Data Models Raster Every location given an object Vector Every object is given a location

Data Conversion Data can be transformed from one of these data models to the other You always loose some information when going from one data format to the other Vectorization Rasterization

Loose topological features Positional accuracy decreases Vector Format Raster Format

Vectorization Features look “jagged” or “pixelated” in the vector representation Topology is created Raster FormatVector Format

Representations of Surfaces A vector surface can modeled by creating a series of irregularly placed points as vertices Each of the vertices has an explicit topographic value Any 3 points are connected to represent an area of the same topography (triangle) Triangulated irregular network (TIN) a vector data model that uses Delaunay triangulation as a means of explicitly storing surface information Vector lines showing terrain contours Raster data can also represent surfaces DEM – Digital elevation model

The topology of a TIN

TINs Contain separate files for arcs triangles Became a popular way to show elevation, etc. for visualization and engineering Allowed for contouring, 3-D views, water flow directions, etc. Many CAD GIS systems use TINs

Digital Elevation Model