Analysis and Modeling in GIS

5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 1

GIS and the Levels of Science

Description: Using GIS to create

descriptive models

of the world --representations of reality as it exists.

Analysis: Using GIS to answer a question or test an hypothesis.

Often involves creating a new conceptual

output

layer, (or table or chart), the values of which are some descriptive

input

layer.

transformation

of the values in the --e.g. buffer or slope or aspect layers Prediction: Using GIS capabilities to create a

predictive model

of a real world process, that is, a model capable of reproducing processes and/or making predictions or projections as to how the world might appear.

--e.g. flood models, fire spread models, urban growth models 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 2

The Analysis Challenge

•

Recognizing which generic GIS analytic capability (or combination) can be used to solve your problem:

–

meet an operational need

–

answer a question posed by your boss or your board

–

address a scientific issue and/or test a hypothesis

Send mailings to property owners potentially affected by a proposed change in zoning Determine if a crime occurred within a school’s “drug free zone” Determine the acreage of agricultural, residential, commercial and industrial land which will be lost by construction of new highway corridor Determine the proportion of a region covered by igneous extrusions Do Magnitude 4 or greater sub-oceanic earthquakes occur closer to the Pacific coast of South America than of North America?

Are gas stations or fast food joints closer to freeways?

3 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

• • •

Availability of Capabilities in GIS Software

Descriptive Focus: Basic Desktop GIS packages

– Data editing, description and basic analysis – ArcView – Mapinfo – Geomedia

Analytic Focus: Advanced Professional GIS systems

– More sophisticated data editing plus more advanced analysis – ARC/INFO, MapInfo Pro, etc.

Provided through extra cost Extensions or professional versions of desktop packages

Prediction: Specialized modeling and simulation

– via scripting/programming within GIS » VB and ArcObjects in ArcGIS » Avenue scripts in ArcView 3.2

» AMLs in Workstation ARC/INFO (v. 7) Write your own or download from ESRI Web site – via specialized packages and/or GISs » 3-D Scientific Visualization packages » transportation planning packages e.g TransCAD » ERDAS, ER Mapper or similar package for raster Capabilities move ‘down the chain’ over time.

In earlier generation GIS systems, use of advanced applications often required learning another package with a different user interface and operating system (usually UNIX).

Description and Basic Analysis

(Table of Contents)

•

Spatial Operations

Vector – spatial measurement – Centrographic statistics – buffer analysis – spatial aggregation » redistricting » regionalization » classification – Spatial overlays and joins Raster – neighborhood analysis/spatial filtering – Raster modeling

•

Attribute Operations

– record selection » tabular via SQL » ‘information clicking’ with cursor – variable recoding – record aggregation – general statistical analysis – table relates and joins 5 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Spatial operations:

Spatial Measurement

• • • • • •

Spatial measurements: distance measures

– between points – from point or raster to polygon or zone boundary – between polygon centroids

polygon area polygon perimeter polygon shape volume calculation

– e.g. for earth moving, reservoirs

direction determination

– e.g. for smoke plumes ArcGIS geodatabases contain automatic • • •

Comments: Cartesian distance via Pythagorus

d ij



where:

(

X i



X j

) 2  (

Y i

d = arc distance possible distance metrics:

– straight line/airline – – – city block/manhattan metric distance thru network time/friction thru network 

Y j

) 2 Used for projected data by ArcMap measure tools

Spherical distance via spherical coordinates Cos d = (sin a sin b) + (cos a cos b cos P) a = Latitude of A b = Latitude of B P = degrees of long. A to B

Used for unprojected data by ArcMap measure tools variables: •

shape often measured by:

shape.length:

line length or polygon perimeter perimeter area x 3.54

= 1.0 for circle = 1.13 for square Large for complex shape

shape.area:

polygon area Automatically updated after editing.

For shapefiles, these must be calculated •

Projection affects values!!!

Distances depend on

e.g. by opening attribute table and applying

Calculate Geometry

to a column (AV 9.2)

projection. Perimeter to area ratio differs

6 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

SHAPE Polygon Polygon Polygon Polygon Polygon Polygon Polygon Polygon Polygon Polygon Polygon Polygon

Spatial operations:

Spatial Measurement

AREA 0.265

0.368

0.209

0.072

0.233

0.233

0.299

PERIMETER CNTY_ 2.729

2.564

2.171

2605 2545 2680 2.642

1.941

1.941

2.278

2899 2335 2103 2870 CNTY_ID NAME 2605 Anderson 2545 Andrews 2680 Angelina 2899 Aransas 2335 Archer 2103 Armstrong 2870 Atascosa FIPS 48001 48003 48005 48007 48009 48011 48013 Shape Index 1.50

1.19

1.34

2.78

1.14

1.14

1.18

0.224

0.222

0.368

0.072

1.900

1.889

2.580

1.421

2471 2481 2106 2386 2471 Dallas 2481 Dawson 2106 Deaf Smith 2386 Delta 48113 48115 48117 48119 1.13

1.13

1.20

1.50

Area and Perimeter measures are automatically maintained in the attributes table for a Geodatabase or coverage. For a shapefile, you need to apply

Calculate Geometry

to an appropriate column in the attribute table (or convert to a geodatabase) . The

shape index

can be calculated from the area and perimeter measurements. (Note: shapefile and shape index are unrelated) 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 7

Spatial Measurement:

Calculating the Area of a Polygon

Area=(2 x 4)/2=4 4,7 Area=(3 x 4)=12 7,7 A = B

-

C

=

-

7,3 2,3 0 5 0 5 10 0 5 10 6,2 Area=(5 x 1)/2=2.5

0 5 The area of the above 10 polygon is 18.5, based on dividing it into rectangles and triangles. However, this is not practical for a complex polygon.

Area of triangle =

The actual algorithm used obtains the area of

A

by calculating the areas of

B

and

C

, and then subtracting.

The actual formulae used is as follows:

i

1 2 3 4 5  i n

X

2 4 7 7 6 2  1 (X 2 X 1 ) ( Y 1  Y 2 )/2 Its implementation in Excel is shown below.

Y

3 7 7 3 2 3

X 2 -X 1

2 3 0 -1 -4

(base x height)/2

5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

(Y 1 +Y 2 )/2

5 7 5 2.5

2.5

product

10 21 0 -2.5

-10

sum

10 31 31 28.5

18.5

8 10

• • • •

Spatial Operations:

Centrographic Statistics

Basic descriptors for spatial point distributions Two dimensional (spatial) equivalents of standard descriptive statistics (mean, standard deviation) for a single-variable distribution

Measures of Centrality (equivalent to mean) – Mean Center and Centroid Measures of Dispersion (equivalent to standard deviation or variance) – Standard Distance – Standard Deviational Ellipse

Can be applied to polygons by first obtaining the centroid of each polygon Best used in a

comparative context

to compare one distribution (say in 1990, or for males) with another (say in 2000, or for females)

9 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Centroid and Mean Center

• • •

balancing point for a spatial distribution

– analogous to the mean – single point representation for a polygon (centroid)

X

– single point summary for a point distribution (mean center) 

i n

  1

X i n

,

Y



i n

  1

n Y i

– can be weighted by ‘magnitude’ at each point (analogous to weighted mean) – minimizes squared distances to other points, thus ‘distant’ points have bigger influence than close points ( Oregon births more impact than Kansas births!) – is not the point of “minimum aggregate travel”--this would minimize distances (not their square) and can only be identified by approximation.

useful for

– summarizing change over time in a distribution (e.g US pop. centroid every 10 years) – placing labels for polygons

for weird-shaped polygons, centroid may not lie within polygon

centroid outside polygon

Note: many ArcView applications calculate only a “psuedo” centroid: the coordinates of the Can be implemented via: bounding box (the extent) of the polygon ArcToolbox>Spatial Statistics Tools>Measuring Geographic Distributions>Mean Center 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 10

2,3 4,7 6,2 7,7 7,3 Calculating the centroid of a polygon or the mean center of a set of points.

1 2 3 4 5 sum Centroid/MC 2 4 7 7 6 26

5.2

3 7 7 3 2 22

4.4

(same example data as for area of polygon)

X



i n

  1

X i

,

Y n



n



i

 1

Y i n

0 0 2,3 4,7 5 5 6,2 7,7 7,3 10 10

i

1 2 3 4 5 sum w MC Calculating the weighted mean center. Note how it is pulled toward the high weight point.

X

2 4 7 7 6 26

Y

3 7 7 3 2 22

weight

3,000 500 400 100 300 4,300

wX wY

6,000 2,000 2,800 700 1,800 13,300

3.09

9,000 3,500 2,800 300 600

X



i n

  1 

w i X i w i

,

Y



i n

  1 

w i Y i w i

16,200

3.77

11 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Source:

US Statistical Abstract 2003

Median Center:

Intersection of a north/south and an east/west line drawn so half of population lives above and half below the e/w line, and half lives to the left and half to the right of the n/s line.

Same as “

point of minimum aggregate travel

” the location that would minimize travel distance if we brought all US residents straight to one location.

Mean Center:

Balancing point of a weightless map, if equal weights placed on it at the residence of every person on census day

.

Note: minimizes squared distances. The point is considerable west of the median center because of the impact of “squared distance” to “distant” populations on west coast For a fascinating discussion of the effect of population projection see: E. Aboufadel & D. Austin,

A new method for calculating the mean center of population center of the US

Professional Geographer, February 2006, pp. 65-69

Standard Distance Deviation

single unit measure of the spread or dispersion of a distribution.

• Is the spatial equivalent of standard deviation for a single variable • Equivalent to the standard deviation of the distance of each point from the mean center • Given by: 

i n

 1 (

X i



X c

) 2  

i n

 1 (

Y i



Y c

) 2

N

which by Pythagoras reduces to: 

i n

 1

N d iC

2 ---the square root of the average squared distance ---essentially the average distance of points from the center We can also weight each point and calculate weighted standard distance (analogous to weighted mean center.) 13 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Standard Distance Deviation

Example

4,7 Circle with radii=SDD=2.9

7,7 7,3 2,3

i

1 2 3 4 5 sum Centroid

X

2 4 7 7 6 26 5.2

Y

3 7 7 3 2 22 4.4

(X - Xc) 2 (Y - Yc) 2

10.2

1.4

3.2

3.2

0.6

2.0

6.8

6.8

2.0

5.8

18.8

sum divide N sq rt 23.2

42.00

8.40

2.90

0 6,2

i

1 2 3 4 5 sum Centroid

X

2 4 7 7 6 26 5.2

5

Y

3 7 7 3 2 22 4.4

(X - Xc) 2

10.2

1.4

3.2

3.2

0.6

18.8

sum of sums divide N sq rt

(Y - Yc) 2

2.0

6.8

6.8

2.0

5.8

23.2

42 8.4

2.90

10

sdd

 

i n

 1 (

X i



X c

) 2  

i n

 1 (

Y i



Y c

) 2

N

5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 14

Standard Deviational Ellipse:

concept

• • •

Standard distance deviation is a good single measure of the dispersion of the incidents around the mean center, but it does not capture any

directional bias

– doesn’t capture the shape of the distribution.

The standard deviation ellipse gives dispersion in two dimensions Defined by 3 parameters

– Angle of rotation – Dispersion along major axis – Dispersion along minor axis The major axis defines the direction of maximum spread of the distribution The minor axis is perpendicular to it and defines the minimum spread

Standard Deviational Ellipse:

example

There appears to be no major difference between the location of the software and telecommunications industry in North Texas. For formulae for its calculation, see Lee and Wong

Statistical Analysis with ArcView GIS

pp. 48-49 (1 st ed.), pp 203-205 (2 nd ed.) 16 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Spatial Operations:

buffer zones

• region within ‘x’ distance units • buffer any object: point, line or polygon • use multiple buffers at progressively greater distances to show gradation • may define a ‘friction’ or ‘cost’ layer so that spread is not linear with distance • Implement in Arcview 3.2 with

Theme/Create buffers

in ArcGIS 8 with

ArcToolbox>Analysis Tools>Buffer

point buffers line buffer polygon buffer

Examples

• 200 foot buffer around property where zoning change requested • 100 ft buffer from stream center line limiting development • 3 mile zone beyond city boundary showing ETJ (extra territorial jurisdiction) • use to define (or exclude) areas as options (e.g for retail site) or for further analysis • in conjunction with ‘friction layer’, simulate spread of fire

Note: only one layer is involved, but the buffer can be output as a new layer

Spatial Operations:

• • •

spatial aggregation

districting/redistricting

– grouping

contiguous

polygons into

districts

– original polygons preserved

Regionalization (or dissolving)

– grouping polygons into contiguous regions – original polygon boundaries dissolved

classification

– grouping polygons into non contiguous regions – original boundaries usually dissolved – usually ‘formal’ groupings Implement in ArcView 9 thru ArcToolbox>Generalization>Dissolve

Grouping/combining polygons—is applied to one polygon layer only.

Criteria may be:

– formal (based on in situ characteristics) e.g. city neighborhoods – functional (based on flows or links): e.g. commuting zones

Groupings may be:

– contiguous – non-contiguous

Boundaries for original polygons:

– may be preserved – may be removed (called dissolving) • • • • • •

Examples:

elementary school zones to high school attendance zones (

functional districting

) election precincts (or city blocks) into legislative districts (

formal districting

) creating police precincts (

funct. reg

.) creating city neighborhood map (

form. reg.

) grouping census tracts into market segments--yuppies, nerds, etc (

class.

) creating soils or zoning map (

class

)

Districting

: elementary school attendance zones grouped to form junior high zones.

Regionalization

: census tracts grouped into neighborhoods

Classification

: cities categorized as central city or suburbs soils classified as igneous, sedimentary, metamorphic 19 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Spatial Operations:

Spatial Matching:

Spatial Joins and Overlays

•

combine two (or more) layers to: Examples

– – select features in one layer, &/or create a new layer • assign environmental samples (points) to census tracts to estimate •

used to integrate data having different spatial properties (point v. polygon), or different boundaries (e.g. zip codes and census tracts)

exposure per capita (point in polygon) • identify tracts traversed by freeway for study of neighborhood blight •

can overlay polygons on:

(polygon on lines) – points (

point in polygon)

– lines (

line on polygon

) – other polygons

(polygon on polygon)

– many different Boolean logic combinations possible » Union (A or B) » Intersection (A and B) • integrate census data by block with sales data by zip code (polygon on polygon) • Clip US roads coverage to just cover Texas (polygon on line) • » A and not B ; not (A and B)

can overlay points on:

• Join

capital city

layer to layer to calculate distance to nearest state capital

all city

– Points, which finds & calculates distance to nearest point in other theme (point on point) – Lines, which calculates distance to nearest line 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 20

Example: Spatial Matching:

Clipping and Erasing

(sometimes referred to as

spatial extraction

) •

CLIP

- extracts those features from an input coverage that overlap with a clip coverage. This is the most frequently used polygon overlay command to extract a portion of a coverage to create a new coverage.

•

ERASE

- erases the input coverage features that overlap with the erase coverage polygons.

5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 21

Example: Spatial Matching via

Polygon-on-Polygon Overlay: Union

Land Use Drainage Basins Atlantic Gulf Combined layer aG a.

aA b.

G.

bA bG A.

c.

cA cG The two layers (land use & drainage basins) do not have common boundaries. GIS creates combined layer with all possible combinations, permitting calculation of land use by drainage basin. Note: the definition of Union in GIS is a little different from that in mathematical set theory. In set theory, the union contains everything that belongs to any input set, but original set membership is lost. In a GIS union, all original set memberships are explicitly retained.

Another example

In set theory terms, the outcome of the above would simply be: 1 2 3 GIS Union Set Theory Union

Implementing Spatial Matching in ArcGIS 9

• • •

Available in three places

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 lines in polygon 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 • • • •

ArcToolbox Examples

Dissolve features based on an attribute

– Combine contiguous polygons and remove common border –

ArcToolbox>Generalization>Dissolve

Clip one layer based on another

– –

ArcToolbox>Analysis Tools>Extract>Clip Use one theme to limit features in another theme

(e.g. limit a Texas road theme to Dallas county only)

Intersect two layers (extent limited to common area)

– –

ArcToolbox>Analysis Tools>Overlay>Intersect Use for polygon on polygon overlay

Union two layers (covers full extent of both layers)

– –

ArcToolbox>Analysis Tools>Overlay>Intersect Use for polygon on polygon overlay

Spatial Operations

:

•

neighborhood analysis/spatial filtering

spatial convolution or filter

– applied to one raster layer – value of each cell replaced by some function of the values of itself and the cells (or polygons) surrounding it – can use ‘neighborhood’ or ‘window’ of any size » 3x3 cells (8-connected) » 5x5, 7x7, etc.

– differentially weight the cells to produce different effects –

kernel

for 3x3 mean filter: 1/9 1/9 1/9 1/9 1/9 1/9 1/9 1/9 1/9

weights must sum to 1.0

•

low frequency ( low pass) filter:

mean filter

– cell replaced by the mean for neighborhood – equivalent to weighting (mutiplying) each cell by 1/9 = .11 (in 3x3 case) – smooths the data – use larger window for greater smoothing

median filter

– use median (middle value) instead of mean – smoothing, especially if data has extreme value outliers 24 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Spatial Operations:

spatial filtering -- high pass filter

high frequency (high pass) filter

negative weight filter

– exagerates rather than smooths local detail – used for edge detection cell values ( v i ) on each side of edge

2 5

filtered values for highlighted pixel 1(5)(9)+5(5)(-1)+3(2)(-1) = 14

standard deviation filter (texture transform)

– calculate

standard deviation

of neighborhood raster values – high SD=high texture/variability – low SD=low texture/variability – again used for edge detection – neighorhoods spanning border have large SD ‘cos of variability 1(2)(9)+5(2)(-1)+3(5)(-1) = -7 –

kernel for example (

w i

)

1(2)(9)+8(2)(-1) = 2

-1 -1 -1

1(5)(9)+8(5)(-1) = 5

-1 9 -1

f i

.

v

.

i w i

-1 -1 -1

5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 25

• • •

Spatial Operations:

raster–based modelling

Relating multiple rasters

•

Suitability modeling

Processes may be:

– Local: one cell only – Neighborhood: cells relating to each other in a defined manner – Zonal: cells in a given section

•

– Global: all cells

ArcGIS implementation:

– All raster analyses require either the Spatial Analyst or 3-D Analyst extensions

•

– Base ArcView can do no more than display an image (raster) data set 1 0 soil 0 0 1 slope 0 1 1 1 for 1 sale 1 0

Diffusion Modeling

Incidence matrix

Connectivity Modeling

Initial State Probability mask Connectivity matrix 2 Site 0 3 options 2 System at time t+1 Resultant State 26 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Attribute Operations:

record selection or extraction

--features selected on the map are identified in the table (and visa versa)

• • •

Select by Attribute (tabular)

Independent selection by clicking table rows: – Open Attribute Table & click on grey

selection box

start of row (hold

ctrl

for multiple rows) Create SQL query – use

Selection/Select by Attribute

use table

Relates /Joins

to select specific data at • •

Outputs may be:

Simultaneously highlighted records in table, and features on map New tables and/or map layers • • • •

Select by Graphic

Manually, one point at a time –

use Select Features tool

within a rectangle or an irregular polygon –

use Selection/Select by Graphic

within a radius (circle) around a point or points –

use Selection/Select by Location (are wthin distance) Select by Location

By using another layer –

Use Selection/Select by Location

(same as

Spatial Matching

discussed previously) •

Hot Link

Click on map to ‘hot link’ to pictures, graphs, or other maps • • •

Examples

Use SQL query to select all zip codes with median incomes above $50,000 (tabular) identify zip codes within 5 mile radius of several potential store sites and sum household income (graphic) show houses for sale on map, and click to obtain picture and additional data on a selected house (hot link) 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 27

• • •

Attribute Operations:

statistical analysis on one or more columns in table

univariate (one variable or column)

– central tendency: mean, median, mode – dispersion: standard deviation, min, max – To obtain these statistics in ArcGIS: » Right click in T of C and select

Open attribute table

» Right click on column heading and select

Statistics

bivariate (relating two variables or columns)

– interval and nominal scale variables: sum or mean by category » average crop yield by silt-sand-clay soil types » To implement in ArcGIS, proceed as above but use

Summarize

– two interval scale variables: correlation coefficients » income by education » ArcScripts are available for this on ESRI web site (or use Excel!)

multivariate (more than two variables)

– usually requires external statistical package such as SAS, SPSS, STATA or S-PLUS 28 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

• •

Attribute Operations:

variable recoding

establishing/modifying number of classes and/or their boundaries for continuous variable. Options for ArcGIS

– natural breaks (default) (finds inherent inherent groups via Jenks optimization which minimizes the variances within each of the classes). – quantile (classes contain equal number of records- or equal area under the frequency distribution) – equal interval (user selects # of classes)

Implement in ArcGIS via:

Right click in T of C, select

Properties

, then

Symbology

tab (equal width classes on variable) – Defined interval (user selects width of classes) (equal width classes on variable) – standard deviation 23% 25% 25% (assumes a Normal distribution) 23% Equal area % (categories based on 1,2, etc, SDs 14% 34% 34% 14% Equal interval % above/below mean) – Manual (user defined) -2 » whole numbers (e.g. 2,000) » meaningful to phenomena (e.g zero, 32 o ) -1 -.68

0 0 .68

1 2 Standard Deviation Equal interval score Equal area score

aggregating categories on a nominal (or ordinal) variable

– pine and fir into evergreen

No change in number of records (observations).

5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 29

Attribute Operations:

record aggregation

• • • • combining two or more records into one, based on common values on a key variable the attribute equivalent of regionalization or classification equivalent of PROC SUMMARY in SAS interval scale variables can be aggregated using mean, sum, max, min, standard deviation, etc. as appropriate

Fips

48085 48113 48121 48139 48213 48231 48257 48397 48221 48251 48367 48439

PMSA_90 PMSA_93 Pop90

1920 1920 264036

Pop95_est Pop90-95% MedInc89 Suburb Name

346232 5.93

46020 1 Collin 1920 1920 1920 1920 1920 1920 1920 1852810 273525 85167 58543 1959281 334070 94223 64293 1.09

4.22

2.03

1.87

31605 36914 30553 20747 0 1 1 1 Dallas Denton Ellis Henderson 1920 64343 66972 0.78

25317 1 Hunt 1920 1920 2800 2800 2800 1920 1920 2800 2800 2800 2800 52220 25604 28981 97165 64785 1170103 60114 32725 33384 106181 73794 1278606 2.88

5.30

2.89

1.77

2.65

1.77

27280 42417 31627 30612 30592 32335 1 1 1 1 1 0 Kaufman Rockwall Hood Johnson Parker Tarrant Source: US Bureau of the Census MedInc=Median Household Income. Pop90 as of April 1. Pop95 as of July 1.

• ordinal and nominal require special consideration • example: aggregate county data to states, or county to CMSA

Fips PMSA_90 PMSA_93 Pop90

1920 2676248

Pop95_est Pop90-95% MedInc89 Suburb Name

2957910 2.00

32607 7 Dallas 2800 1361034 1491965 1.83

31292 3 Fort Worth

Record count decreases (e.g. from 12 to 2)

sum 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals sum re-calc.

Type of processing:

average of medians!

count 30

Attribute Operations:

Joining and Relating Tables

associating spatial layer to non-spatial table

Join: one to one, or one to many, relationship appends attributes Associate table of country capitals with country layer: only one capital for each country (one to one) Country Code

29 68 106 248 199 9

Country

France Saudi Arabia Chad Spain Venezuela UK 96 Philippines

Layer Attribute Table

Country Code

199 96 68 29 106 9

Capital

Caracas Manila Riyadh Paris N'Djamena London 248 Madrid

NonSpatial Table

Country Code

9 29 68 96 106 199 248

Country

UK France Saudi Arabia Philippines Chad Venezuela

Capital

London Paris Riyadh Manila N'Djamena Caracas Spain Madrid

Layer Attribute Table after Join

Associate country layer with type of government: one gov. type assigned to many countries--but each country has only one gov. type (one to many) Gov. Code

20 30 15 20 10 15

Country

France Vietnam UK Argentina Saidi Arabia Sweden 45 Portugal

Layer Attribute Table

Gov. Code

10 15 20 30 45

Type

Absolute Monarchy Const. Monarchy Republic Communist State Parliamentary Democracy

Gov. Code

20 30 15 20 10 15 45

Country

France Vietnam UK Argentina Saudi Arabia Sweden

Type

Republic Communist State Const. Monarchy Republic Absolute Monarchy Const. Monarchy Portugal Parliamentary Democracy

Layer Attribute Table after Join NonSpatial Table

31 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Single most common error in GIS Analysis

--intending a one to one join of attribute to spatial table --getting a one to many join of attributes to spatial table NAME Alabama Alaska …..

Georgia Hawaii Idaho …..

Wisconsin Wyoming FIPS 01 02 13 15 16 55 56 CODE AL AK GA HI ID WI WY POP2000 4,447,100 626,932 8,186,453 1,211,537 1,293,953 5,363,675 493,782 Spatial 51 states Total 282,421,906 FID 0 1 11 12 13 14 15 16 53 54 SHAPE Polygon Polygon Polygon Polygon Polygon Polygon Polygon Polygon Polygon Polygon NAME Alabama Alaska …..

Georgia Hawaii-Hawaii FIPS 01 02 13 15 Hawaii-Maui Hawaii-Oahu Hawaii-Kauai Idaho …..

Wisconsin Wyoming 15 15 15 16 55 56 CODE AL AK GA HI HI HI HI ID WI WY Total POP2000 4,447,100 626,932 8,186,453 1,211,537 1,211,537 1,211,537 1,211,537 1,293,953 5,363,675 493,782 286,056,517 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals After joining attribute to spatial data 32

Attribute Operations:

Joining and Relating Tables

associating spatial layer to non-spatial table (contd.)

Relate: many to one relationship, attributes not appended Associate country layer with its multiple cities (many to one) Country Code Country

29 France 68 Saudi Arabia 106 Chad 248 Spain 199 Venezuela 9 UK 96 Philippines

Layer Attribute Table

Country Code

129 129 29 29 29 60 248 248 248

City

Mombasa Nairobi Paris Lyon Marseille Katmandu Madrid Barcelona Valencia

NonSpatial Table

If

joined

Paris to France, for example, we lose Lyon and Marseille, therefore use

relate

Note: if we flip these tables we can do a join since there is only one country for each city (one to many)

• •

For both Joins and Relates: Association exists only in the map document Underlying files not changed unless export data

5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 33

Analysis Options:

Advanced & Specialized

• • • • •

Advanced

(Table of Contents)

Specialized

Proximity/point pattern analysis

• Remote Sensing image processing and classification – nearest neighbor layer • raster modeling – distance matrix layer • 3-D surface modeling

surface analysis

– cross section creation • spatial statistics/statistical – visibility/viewshed modeling

network analysis

– routing • functionally specialized – transportation modeling » shortest path (2 points) » travelling salesman (n points) – land use modeling – hydrological modeling – time districting – etc.

– allocation

Convex Hull Thiessen Polygon creation

5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 34

Advanced Applications:

Proximity Analysis

• •

Nearest Neighbor

location (distance) relative to nearest neighbor ( points or polygon centroids) location (distance) relative to nearest objects of selected other types (e.g. to line, or point in another layer, or polygon boundary)

Point Pattern Analysis

is pattern?

Random Clustered Dispersed

Requires only one output column –

altho generalizable to k th nearest neighbor

•

Full matrix

measure location of each object relative to every other object –

requires output matrix with as many columns as rows in input table

Requires the application of

Spatial Statistics

•Nearest neighbor statistic •Moran’s I such as which are based on proximity of points to each other

ArcToolbox>Spatial Statistics Tools

35 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Advanced Applications:

• •

Routing

Network Analysis

Network-based Districting

•

shortest path between two points

– direction instructions (locating hotel from airport)

travelling salesman: shortest expand from site along network until criteria (time, distance, cost, object count) is reached; then assign area to district

– creating market areas, attendance zones, etc – essentially network-based buffering

path connecting n points Network-based Allocation

– bus routing, delivery drivers •

assign locations to the nearest center

for water, sewage, etc.).

based upon travel thru network

In all cases, ‘distance’ may be measured in miles, time, cost or other ‘friction’ (e.g pipe diameter • – assign customers to pizza delivery outlets

draw boundaries (lines of equidistance between 2 centers) based on the above

Arc or node attributes (e.g one-way streets, no left turn) may also be critical.

– Network-based market area delimitation – Essentially, network-based polygon tesselation 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 36

Advanced applications:

Surface Analysis

• •

Slope Transform

fit a plane to the 3 by 3 neighborhood around every cell, or use a TIN output layer is the

slope

(first derivative) of the plane for each cell • • •

Aspect Transform

direction slope faces: (E-W oriented ridge has slopes with northern and southern aspects) aspect normally classified into eight 45 degree categories calculate as horizontal component of the vector perpendicular to the surface

Cross-section Drawings and Volumes

• elevation (or slope) values along a line • Volume & cut-and-fill calculation • Cross-section easy to produce for raster, more difficult for vector especially if uses contours lines

Viewshed/Visibility

• terrain visible from a specific point • • applications – visual impact of new construction – select scenic overlooks – Military

Contouring

– Lines joining points of equal (vertical) value – From raster, massed-points or breakline data 37 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Advanced Applications: Convex Hull

• Formally: the smallest convex polygon (no concave angles) able to contain a set of points • Informally: a rubber band wrapped around a set of points • Just as a centroid is a point representation

No!

for a polygon, the convex hull is the polygon representation for a set of points • Go to the following web site for a neat application showing how convex hull changes as you move points around

–

http://www.cs.princeton.edu/~ah/alg_anim/version1/ConvexHull.html

38 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Advanced Applications:

Thiessen (Dirichlet, Voronoi) Polgons

•

and Delaunay Triangles

polygons generated from a point layer such that any location within a polygon is closer to the enclosed point than to a point within any other polygon • • • • they divide the space between the points as ‘evenly’ as possible used for market area delimitation, rain gauge area assignment, contouring via Delaunay triangles (DTs), etc.

elevation, slope and aspect of triangle calculated from heights of its three corners DTs are as near equiangular as possible and longest side is as short as possible, thus minimizes distances for interpolation Thiessen neighbors of point A share a common boundary. Delauney triangles are formed by joining point to its Thiessen neighbors.

5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Thiessen Polygons (or proximal regions or proximity polygons) A Delaunay Triangles A 39

Specialized Applications

• • •

Remote Sensing/Digital Image Processing

reflectance value (usually 8 bit; 256 values) collected for each bands (wavelength area) in the electro magnetic spectrum – 1 band for grey scale (Black & white) – 3 for color – up to 200 or so for ‘hyperspectral’ – permits creation of image

‘

spectral signature’: set of reflectance values/ranges over available bands typifying a specific phenomena – provides basis for identification of phenomena

Location Science/Network Modeling Network based models for optimum location decisions for (e.g.)

– police beats – School attendance zones – Bus routes – Hazardous material routing – Fire station location • •

Raster Modeling: 2-D

use of direction and friction surfaces to develop models for: – spread of pollution – dispersion of forest fires

Surface Modeling: 3-D

– flood potential – ground water/reservoir studies – Viewshed/visibility analysis

Spatial Statistics/Econometrics

analyses on spatial data which explicitly incorporates relative location or

proximity

property of observations Global (applies to entire study area) – spatial autocorrelation – Regressions adjusted for spatial autocorrelation Local (separately calculated for local areas) – LISA (local indicators of spatial autocorrelation) – Geographically weighted regression

We offer one or more courses on each!

40 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Implementation of Advanced and Specialized Applications in ArcGIS 8/9

• • • • • •

Extensions support many of the Advanced and some Specialized Applications Spatial Analyst

extension provides 2-D modeling of GRID (raster) data (AV 3.2 and 8/9)

3-D Analyst

extension provides 3-D modeling (AV 3.2 and 8/9)

Geostatistical Analyst Network Analyst extension (3.2 only) and ArcLogistics Route (standalone)

and network analysis extension provides interpolation (ArcGis 8/9 only) for routing

Image Analyst

extension for remote sensing applications in AV 3.2

– Leica Image Analysis and Stereo Analyst for ArcGIS 8 (9 version not yet released-Fall ’04)

Spatial Statistics Tools

in ArcToolbox provide spatial statistics (centroid, etc..) •

ArcScripts support other Advanced Applications and Specialized Applications ArcScripts (in Visual Basic, C++, etc.)

are used to customize ArcGIS 8 – A variety of scripts available at

http://support.esri.com/

– Note: ArcScripts written in

Avenue

>downloads

work only in ArcView 3 and will not work in ArcGIS 8/9 – Many functions previously requiring Avenue scripts for AV 3.2 are built into ArcGIS 8/9 • •

Specialized Software Packages

Remote Sensing packages such as Leica GeoSystems Imagine (formerly ERDAS Imagine) For links to some of these packages go to: http://www.utdallas.edu/~briggs/other_gis.html

41 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Appendix

Implementing Spatial Analysis in ArcView 3.2/3.3

5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 42

• • •

Implementing Spatial Measurement in ArcView 3.2

Unlike in ArcGIS 8.1 where spatial measurements are provided automatically, in AV 3.2 spatial measurement often has to be implemented using Avenue code:

– in functional expressions – in scripts

Using functional expression for areas and lengths:

– Use Edit/Add field to add a new variable to atttributes of…table called

area

– Use Field/calculate and make this variable equal to:

[Shape].ReturnArea

– – Calculation is based on map units irrespective of defined distance units.

If map units are feet, to obtain square miles use: (or similar)

[Shape].ReturnArea/5280/5280

– If file is a polyline file (arcs), for length of arcs use:

[Shape].ReturnLength

Using a Script for areas, perimeters and lengths

In Project window, select Script and click new button to open script window Use

Script/load text file

to load code from an existing text file e.g.

arcview\samples\scripts\calcapl.ave will calculate areas, perimeters, lengths

Click the “check mark” icon to compile the code.

Open a View and be sure the theme you want processed is active.

Click on script window then click the Runner icon to run script.

variables measuring area and perimeter will be added to theme table

43 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Implementing Spatial Matching in ArcView 3.2

•

Available in two places (plus additional user extensions such as districting)

via

Theme/select by theme

– this selects features of the active theme which relate in some

specified spatial manner

to • • • • • • another theme – if desired, selected features may be saved later to a new theme via

Theme/convert to shape file

• via Geoprocessing Wizard Extension (use

Options in Geoprocessing Wizard

(use

File/Extensions

– Six options available for different types of matching to load) – this creates a new theme (shape file) & combines attribute tables from 2 or more input themes

View/Geoprocessing Wizard

to activate)

Dissolve features based on an attribute

–

Use for spatial aggregation/dissolving

Merge themes together

– –

Use for edge matching

Clip one theme based on another

Use one theme to limit features in another theme (e.g. limit a Texas road theme to Dallas county only)

•Scripts and extensions can provide additional capabilities •Download from ArcScripts at ESRI http://gis.esri.com/arcscripts/ scripts.cfm

•Place extensions (.avx) in your

Intersect two themes

–

Use for polygon on polygon overlay

folder

Arcview/ext32

•The extension

district.avx

is good

Union two themes

–

Use for polygon on polygon overlay

for doing spatial aggregation or “districting”

Assign data by location (Spatial Join

) –

Use for: points in polygon lines in polygon points on lines (to calculate distance to nearest line) points on points (to calculate distance to “nearest neighbor” point)

44 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

•

Using Extensions and Scripts in ArcView 3.2

Obtain copy of script or extension

– Write yourself with Avenue language – Supplied with ArcView in folder:

arcview/samples/scripts

or

arcview/samples/ext

» Go to ArcView

Help/Contents/Sample Scripts and Extensions

for documentation – Buy from ESRI and other companies – Supplied free by ESRI or users and available on ESRI web site at:

http://arcsripts.esri.com/ Select Avenue language

» or go to www.esri.com

and click Support » Be sure to print or download documentation/description •

To load and use an extension

– Place .avx file in

arcview/ext32

folder – Open ArcView, choose

File/extensions

, place tick next to name, click OK •

To load and use a script

In Project window, select Script and click new button to open script window Use

Script/load text file

to load code from existing text file containing avenue code (.ave)

e.g. \av_gis30\ arcview\samples\scripts\calcapl.ave will calculate areas, perimeters, lengths

Click the “check mark” icon to compile the code.

Take steps within ArcView as appropriate for specific script e.g. Open a View and be sure the theme you want processed is active.

Click on script window then click the “Runner" icon to run script.

e.g. variables measuring area and perimeter will be added to theme table 45 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals

Some Example Avenue Scripts for ArcView 3

•

Avenue scripts and extensions

for AV 3.2 can be downloaded from ESRI Web site to do many basic, advanced and specialized applications not available in standard products. Some examples are: –

Addxycoo.ave:

adds X,Y coordinates of points (e.g of geocoded addresses), or of centroid for polygons, to

attributes of …

file – –

Polycen.ave:

creates point theme containing polygon centroids

Dwizard.zip:

various districting applications » Use

avdist31b

which is an update – –

Line.zip:

enhanced buffering of lines

Nearestneighbor.zip:

nearest neighbor analysis For more scripts, go to: http://arcsripts.esri.com/ Select

Avenue

language 5/6/2020 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 46