1/3/2008 gisc 6382 applied gis briggs ut-dallas 1 spatial analysis an introduction to concepts and...

1/3/2008 GISC 6382 Applied GIS Briggs UT-Dallas 1

Spatial Analysis

An Introduction to Concepts

and their

Implementation in ArcMap


Description and Analysis• Most GIS systems are acquired by large organizations for the purpose of

representing and describing features of the real world which are relevant to that organization’s mission– Spatial databases perform this function– Most concepts discussed so far relate to this

• Points, lines, polygons concepts for representation• Coordinate systems as fundamental properties of spatial data• geographic file formats for storage

Most GIS system capabilities are focused here

• Analysis involves gaining an understanding of the patterns, and associated cause and effect processes, underlying the features which have been described in order to– Help the organization better carry out its mission

• Make better decisions, for example

– Understand the phenomena as a goal in itself• This is the role of science

GIS systems are less capable here, and often must be supplemented


Process, Pattern and Analysis

• Processes operating in space produce patterns

• Spatial Analysis is aimed at:– Identifying and describing the pattern– Identifying and understanding the process


Spatial Analysis: successive levels of sophistication

• Spatial data manipulation: classic GIS capabilities– Spatial queries & measurement, buffering, map layer overlay

• Spatial data analysis: descriptive and exploratory– Visualization through data manipulation and mapping

• John Snow’s maps of cholera in 1850s London

• Spatial statistical analysis: hypothesis testing– Are data “to be expected” or are they “unexpected” relative

to some statistical model, usually of a random process

• Spatial modeling: prediction– Constructing models (of processes) to predict spatial

outcomes (patterns)– What if analyses


GeoStatistics & Spatial Statistics

Object View• The real world is a series of entities located in space.

– An object is a digital representation of an entity

• Objects analyzed with Spatial Statistics– The focus of this course

Field View• The real world has properties which vary continuously

over space– every place has a value

• Fields analyzed with GeoStatistics– The focus of the Spatial Analysis course


The Pitfalls of Spatial Analysis• Spatial autocorrelation

– Data from location near to each other are more likely to be similar than data from location remote from each other– Causes serious problems with traditional statistical models

• Spatial statistical models are essential

• Modifiable areal unit problem (MAUP)– Results may depend on the areal unit used

• Census tracts versus counties (scale issue)• Census tracts versus zip codes (not a scale issue)

• Ecological fallacy– Results obtained from aggregated data (e.g. census tracts) cannot be assumed to apply to individual people– A special case of the MAUP problem– Encountered in spatial and non-spatial analysis

• Scale affects representation and results– Cities may be points or polygons– MAUP may be viewed as a scale issue

• Nonuniformity of Space and Edge Issues– Phenomena is not distributed evenly in space

• Bank robberies cluster ‘cos banks are clustered in space

– Edges, beyond which there is no data, can significantly effect results


Fundamental Spatial Concepts• Distance

– The magnitude of spatial separation– Euclidean (straight line) distance often only an approximation

• Adjacency– Nominal or binary equivalent of distance– Levels of adjacency exist: 1st, 2nd, 3rd nearest neighbor, etc..

• Interaction– The strength of the relationship between entities– An inverse function of distance

• Neighborhood– An association between one entity and those around it– May be based upon

• Interaction: flows or connections (functional)• Similarity of attributes (formal)


Primarily carried out in ArcMap:• via Selection/Select by Location

– this selects features of one layer(s) which relate in some specified spatial manner to the features in another layer

– if desired, selected features may be saved later to a new theme via Data/Export Data

– Individual features are not themselves modified• via Spatial Join (right click layer in T of C, select Join/Joins

and Relates, then click down arrow in first line of Join Data window---see Joining Data in Help for details)– Use for: points in polygon (identifies polygon in which point is

located)lines in polygon (identifies polygons crossed by line)points on lines (to calculate distance to nearest line)points on points (to calculate distance to “nearest

neighbor” point)– operate on tables and normally creates a new table with additional

variables, but again does not modify spatial features themselves• via ArcToolbox

– Generally these tools modify geographic feature, thus they create a new layer (e.g. shape file)

– Tools are organized into multiple categories

Implementing Spatial Analysis in ArcGIS 9


Differences• Selection: simply selects (“highlights”) entire spatial features in the target

layer, but doesn’t modify these features– Selection only– Only Selected features (a subset of all features) are “output”– No new output file saved unless you use Export/data

• joins: operate on tables and normally creates a new table with additional fields or variables (columns), but again does not modify actual spatial features (rows) – adds attributes (columns) to the layer’s table from another layer’s table– All features are “output”– No features modified– No new output file saved unless you use Export/data

• Analysis Toolbox (and others) in ArcToolbox – Often these modify or create spatial features thus they output new spatial files

Different approaches can be used, in some cases, to produce same results.


Analysis Tools in ArcToolboxArcToolbox, particularly the Analysis Tools toolbox contains

• Extract toolset, including– Clip which limits one layer to the exact outer boundary of another layer

(e.g. limit a Texas road theme to Dallas county only)• Overlay toolset, including

– Intersect, which combines two polygon layers--with output limited to common area– Union, which combines two polygon layers--with output covering full extent of

both layers• Proximty toolset, including

– Buffer, for creating buffer polygons at a specified distance around points, lines or polygons

– Point Distance, for calculating distances between points within a specified radius• Statistics toolset, including

– Frequency, which gives you counts of attribute value combinations– Summary Statistics, which gives you summary descriptive statistics for columns

in a table, including sum, mean, min, max, etc..

Tools useful for analysis of vector data are located in other toolsets as well!!! For example:

– Data Management Tools>Generalization, contains• Dissolve, which removes boundaries between polgyons


The Components of An Analysisand the elements of its documentation

• Objective, which explains the purpose of the analysis and explains why it is significant, possibly including

– Hypotheses, which are potential explanations which you intend to test• Literature Review, which identifies the key pieces of existing research relevant

to the project and the hypotheses you have advanced • Data Sources, which identify and explain the data used.• Analysis and Methodology, which explains the methodology applied to the

data.• Results and Discussion, which describes your main research findings, whether

or not your hypotheses were upheld, and any potential problems with your interpretation of the results

• Conclusions, which discusses the implications of your finding relative to your initial project objective.

• References, which provides standard format citations for all resources drawn upon for the project.

For more detail, go to:http://www.utdallas.edu/~briggs/poec6389/gisc6389_contents.doc

http://www.utdallas.edu/~briggs/poec6389/gisc6389_contents.doc


Literature Review• All research and analysis builds upon the existing

base of scientific knowledge• It is imperative that you identify the existing state

of knowledge in order to – Establish appropriate objectives

– Advance meaningful hypotheses

– Select and use legitimate methodologies

• This is accomplished by reviewing the existing literature

• On scientific knowledge

• On best practices by other organizations


Doing a Literature ReviewDoing a standard Google search is not sufficient! Instead, use Google Scholar • http://scholar.google.com/

If you access Google Scholar from on-campus via the UTD Library web page at • http://www.utdallas.edu/library/it will give you automatic access to materials subscribed to by UTD library (very clever!)

For information on how to configure Google Scholar to access UTD library materials from off-campus, go to• http://www.utdallas.edu/library/howto/GoogleScholarPage.htmThis site also gives guidelines on when to use bibliographic databases in place of Google Scholar

Databases available at UTD for literature searches, covering both citations and complete text, can be found at:• http://www.utdallas.edu/library/collections/dbases.htm

The single most commonly used bibliographic database is probably “Web of Science” at• http://www.utdallas.edu/library/collections/dbUZ.htmOr directly at• http://isi10.isiknowledge.com/portal.cgi?DestApp=WOS&Func=Frame

For information on accessing these library databases from off-campus, go to:• http://www.utdallas.edu/library/howto/access.htm Because of licensing restrictions, you will need to follow these instructions for off-campus access

http://scholar.google.com/

http://www.utdallas.edu/library/




How to Format Citations

• It is important that you learn to use the correct format when citing literature

• Doing a copy/paste of a URL, which may be gone tomorrow, is not sufficient!

• The Chicago Manual of Style is the accepted norm.The Chicago Manual of Style. Chicago: University of Chicago Press, 15th ed., 2003

– Or replicate the format used by any mainline GIS journal

• A nice summary is available at:– http://www.libs.uga.edu/ref/chicago.html – Or, http://library.osu.edu/sites/guides/chicagogd.php – Use it!!!!

http://www.libs.uga.edu/ref/chicago.html



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