Environmental GIS

Environmental GIS

Nicholas A. Procopio, Ph.D, GISP

[email protected]

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. 12906, all federal agencies and organizations must document their geospatial data using the FDGC Content Standard for Digital Geospatial Metadata

http://www.fgdc.gov/

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.

Code Country Population Area (sq km) Area (sq mi)AF Afghanistan 17250390 641869.19 247825.7AL Albania 3416945 28754.5 11102.11AG Algeria 27459230 2320972 896127.31AQ American Samoa 53000 186.895 72.16AN Andorra 55335 452.485 174.704AO Angola 11527260 1252421 483559.81AV Anguilla 9208 86.296 33.319AY Antarctica -99999 12302740 4750088AC Antigua and Barbuda 65212 462.378 178.524AR Argentina 33796870 2781013 1073749AM Armenia 3377228 29872.461 11533.76

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!

Attribute Types

Qualitative• No measurement or magnitude

• Non-numeric descriptions

• No numeric meaning, even if shown as code numbers (i.e., 1=category 1)

Attribute Types

Quantitative• Numeric and have mathematical meaning

• Serve as measurements or magnitudes of the features they refer

• Example: city population

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” digitizingManual “heads-up” digitizing ScannersScanners

• Appropriate for encoding raster data since this is Appropriate for encoding raster data since this is the output format for most scanners. the output format for most scanners.

• Problems may includeProblems may include Scanning unwanted informationScanning unwanted information Optical distortionOptical distortion The higher the resolution, the more volume of data The higher the resolution, the more volume of data

producedproduced

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 availableCostMediaFormat

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 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 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 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)


Advantages• Requires less storage space• Topology easily maintained• Graphical output usually more pleasing


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

1 1,2,3,4,5,6,72 1,7,8,9,10,11

Arcs File

6

2

3

4

51

79

10

11

8

1

2

A

1 x y2 x y3 x y4 x y5 x y6 x y7 x y8 x y9 x y10 x y11 x y

Po

ints

File

A: 1, 2, Area, Attributes

Files of arcs by polygons

Topology Example

Topology not attained!

Sliver

Topology is attained!

Summary of Data Models

Real World

1

1

1

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0

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0

0

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Raster Windmills0 = No Data1 = 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

Rasterization

Loose topological features Positional accuracy decreases


Vectorization

Features look “jagged” or “pixelated” in the vector representation

Topology is created

Raster Format Vector Format


Vector Representations of Surfaces

A vector surface is 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

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

Aronoff, 1993. Geographic Information Systems: A Management Perspective.

Ottawa : WDL Publications.

Digital Elevation Model

(A)Landslide risk map for Pisa, Italy (Courtesy of Earth Science Department, University of Siena, Italy)

(B) Yangtse River, China (Courtesy of Human Settlements ResearchCenter, Tsinghua University, China)

Examples of applications that use the TIN data model

Environmental GIS

Documents

Transcript of Environmental GIS