Analysis in GISAnalysis in GIS

Analysis ComponentsAnalysis Components

analyses may be applied to (use as input):analyses may be applied to (use as input):– tabular attribute datatabular attribute data– spatial data/layersspatial data/layers– combination of spatial and tabular combination of spatial and tabular

results may be displayed as (produce as output):results may be displayed as (produce as output):– table subsets, table combinations, highlighted records table subsets, table combinations, highlighted records

(rows), new variables (columns)(rows), new variables (columns)– chartscharts– maps/map features:maps/map features:

highlights on existing themes highlights on existing themes new themes/layersnew themes/layers

– combinationcombination

Availability of Analytical Capabilities:Availability of Analytical Capabilities:Analysis OptionsAnalysis Options

Basic: Desktop GIS packages Basic: Desktop GIS packages – ArcGIS ArcViewArcGIS ArcView– MapinfoMapinfo– Geomedia (Bentley); Geographics (Intergraph)Geomedia (Bentley); Geographics (Intergraph)

Advanced: Professional GIS systems Advanced: Professional GIS systems – ArcGIS ArcINFO, Intergraph MGEArcGIS ArcINFO, Intergraph MGE– provide data editing plus more advanced analysisprovide data editing plus more advanced analysis

Specialized: modelling and simulation Specialized: modelling and simulation – via scripting/programming within GISvia scripting/programming within GIS

ArcObjects in ArcGISArcObjects in ArcGIS– via specialized packages and/or GISsvia specialized packages and/or GISs

3-D Scientific Visualization packages3-D Scientific Visualization packages transportation planning packagestransportation planning packages ER Mapper, PCI for rasterER Mapper, PCI for raster

Capabilities move

‘up the chain’

over time.

Advanced and Specialized Advanced and Specialized Applications:Applications:

in comparison to basic applicationsin comparison to basic applicationsMost ‘Most ‘basic’ basic’ analyses are used to create analyses are used to create descriptive descriptive models models of of

the world, that is, representations of reality as it exists.the world, that is, representations of reality as it exists.

Most ‘Most ‘advanced’ advanced’ analysesanalyses involve creating a new involve creating a new conceptual conceptual output output layer, or in some cases table(s) or chart(s), the layer, or in some cases table(s) or chart(s), the values of which are some values of which are some transformationtransformation of the values in of the values in the the descriptivedescriptive input input layer.layer.

e.g. slope or aspect layere.g. slope or aspect layer

Most ‘Most ‘specializedspecialized’ applications involve using GIS capabilities ’ applications involve using GIS capabilities to create a to create a predictivepredictive model model of a real world process, that of a real world process, that is, a model capable of reproducing processes and/or is, a model capable of reproducing processes and/or making predictions or projections as to how the world making predictions or projections as to how the world mightmight appear. appear.e.g. fire spread model, traffic projections e.g. fire spread model, traffic projections

Analysis Options: Analysis Options: BasicBasic Spatial OperationsSpatial Operations

– centroid determinationcentroid determination– spatial measurementspatial measurement– buffer analysisbuffer analysis– neighborhood neighborhood

analysis/spatial filteringanalysis/spatial filtering– geocodinggeocoding– polygon overlay polygon overlay – spatial aggregationspatial aggregation

redistrictingredistricting regionalizationregionalization classificationclassification

Attribute OperationsAttribute Operations– record selectionrecord selection

tabular via SQLtabular via SQL ‘‘information information

clicking’ with clicking’ with cursorcursor

– variable recodingvariable recoding– record aggregationrecord aggregation– general statistical general statistical

analysisanalysis

Analysis Options: Analysis Options: Advanced & Advanced & Specialized Specialized

AdvancedAdvanced surface analysissurface analysis

– cross section creationcross section creation– visibility/viewshed visibility/viewshed

proximity analysisproximity analysis– nearest neighbor layernearest neighbor layer– distance matrix layerdistance matrix layer

network analysisnetwork analysis– routingrouting

shortest path (2 points)shortest path (2 points) traveling salesman (n points)traveling salesman (n points)

– time districtingtime districting– allocationallocation

Thiessen Polygon creationThiessen Polygon creation

SpecializedSpecialized Remote Sensing image Remote Sensing image

processing and classification processing and classification raster raster modellingmodelling 3-D surface modelling3-D surface modelling spatial statistics/statistical spatial statistics/statistical

modellingmodelling functionally specializedfunctionally specialized

– transportation modellingtransportation modelling– land use modellingland use modelling– hydrological modellinghydrological modelling– etc.etc.

Spatial operations:Spatial operations:Centroid or Mean CenterCentroid or Mean Center

balancing point for a spatial distributionbalancing point for a spatial distribution– point representation for a polygon--analogous to the meanpoint representation for a polygon--analogous to the mean– single point summary for a distribution (point or polygon)single point summary for a distribution (point or polygon)

useful for useful for – summarizing change over time in a distribution (e.g Canadian summarizing change over time in a distribution (e.g Canadian

pop. centroid every 10 years)pop. centroid every 10 years)– placing labels for polygonsplacing labels for polygons

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

centroid outside polygon

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Spatial operations: Spatial operations: Spatial MeasurementSpatial Measurement

Spatial measurements:Spatial measurements: distance measuresdistance measures

– between pointsbetween points– from point or raster to from point or raster to

polygon or zone boundarypolygon or zone boundary– between polygon centroidsbetween polygon centroids

polygon areapolygon area polygon perimeterpolygon perimeter polygon shapepolygon shape volume calculation volume calculation

– e.g. for earth moving, resevoirse.g. for earth moving, resevoirs

direction determinationdirection determination– e.g. for smoke plumese.g. for smoke plumes

Comments:Comments: possible distance metrics:possible distance metrics:

– straight line/airlinestraight line/airline– city block/manhattan metriccity block/manhattan metric– distance thru networkdistance thru network– time/friction thru networktime/friction thru network

shape often measured by:shape often measured by:

may generate output raster: may generate output raster: – value of spatial measurement value of spatial measurement

assigned to each pixel within assigned to each pixel within a polygon or zonea polygon or zone

Projection affects values!!!Projection affects values!!!

perimeterarea x 3.54

= 1.0 for circle= 1.13 for square

= large number for irregular polygon

Spatial operations: Spatial operations: Spatial Measurement--exampleSpatial Measurement--example

AREA PERIMETER CNTY_ CNTY_ID NAME FIPS0.265 2.729 2605 2605 Anderson 480010.368 2.564 2545 2545 Andrews 480030.209 2.171 2680 2680 Angelina 480050.072 2.642 2899 2899 Aransas 480070.233 1.941 2335 2335 Archer 480090.233 1.941 2103 2103 Armstrong 480110.299 2.278 2870 2870 Atascosa 480130.159 2.115 2830 2830 Austin 480150.203 1.806 2256 2256 Bailey 480170.205 2.114 2844 2844 Bandera 480190.218 1.842 2801 2801 Bastrop 480210.223 1.897 2338 2338 Baylor 48023

Attributes of ..... file in ArcView provides area and perimetermeasurements automatically.

Spatial Operations:Spatial Operations:buffer zonesbuffer zones

Buffer zonesBuffer zones region within ‘x’ distance region within ‘x’ distance

unitsunits buffer any object: point, line buffer any object: point, line

or polygonor polygon use multiple buffers at use multiple buffers at

progressively greater progressively greater distances to show gradationdistances to show gradation

may define a ‘friction’ or may define a ‘friction’ or ‘cost’ layer so that spread is ‘cost’ layer so that spread is not linear with distancenot linear with distance

ExamplesExamples 200 foot buffer around 200 foot buffer around

property where zoning change property where zoning change requestedrequested

100 ft buffer from stream 100 ft buffer from stream center line limiting center line limiting developmentdevelopment

3 mile zone beyond city 3 mile zone beyond city boundary showing ETJ (extra boundary showing ETJ (extra territorial jurisdiction)territorial jurisdiction)

use to define (or exclude) use to define (or exclude) areas as options (e.g for retail areas as options (e.g for retail site) or for further analysissite) or for further analysis

in conjunction with ‘friction in conjunction with ‘friction layer’, simulate spread of firelayer’, simulate spread of fire

polygon buffer

linebuffer

point buffers

Spatial OperationsSpatial Operations::neighborhood analysis/spatial filteringneighborhood analysis/spatial filtering

spatial convolution or filterspatial convolution or filter– value of each cell replaced by value of each cell replaced by

some function of the values of some function of the values of itself and the cells (or polygons) itself and the cells (or polygons) surrounding itsurrounding it

– can use ‘neighborhood’ or can use ‘neighborhood’ or ‘window’ of any size ‘window’ of any size

3x3 cells (8-connected)3x3 cells (8-connected) 5x5, 7x7, etc.5x5, 7x7, etc.

– differentially weight the cells to differentially weight the cells to produce different effects produce different effects

– kernelkernel for 3x3 mean filter: for 3x3 mean filter:

1/9 1/9 1/91/9 1/9 1/9

1/9 1/9 1/91/9 1/9 1/9

1/9 1/9 1/91/9 1/9 1/9

low frequency ( low pass) filter:low frequency ( low pass) filter:

mean filtermean filter– cell replaced by the mean for cell replaced by the mean for

neighborhoodneighborhood– equivalent to weighting equivalent to weighting

(mutiplying) each cell by(mutiplying) each cell by 1/9 = .11 (in 3x3 case) 1/9 = .11 (in 3x3 case)

– smoothssmooths the data the data – use larger window for greater use larger window for greater

smoothingsmoothing

median filtermedian filter– use median (middle value) use median (middle value)

instead of meaninstead of mean– smoothing, especially if data smoothing, especially if data

has extreme value outliershas extreme value outliers

weights must sum to 1.0

Spatial Operations:Spatial Operations:Polygon OverlayPolygon Overlay

combines two (or more) combines two (or more) layers to create a thirdlayers to create a third

used to integrate attribute used to integrate attribute data having different spatial data having different spatial properties (point v. polygon) properties (point v. polygon) or boundaries (zip and tract)or boundaries (zip and tract)

can overlay polygons on:can overlay polygons on:– points (points (point in polygon)point in polygon)– lines (lines (line on polygonline on polygon))– other polygonsother polygons

many different Boolean logic many different Boolean logic combinations possiblecombinations possible– Union (A or B)Union (A or B)– Intersection (A and B)Intersection (A and B)– A and not B ; not (A and B)A and not B ; not (A and B)

ExamplesExamples assign environmental samples assign environmental samples

(points) to census tracts to (points) to census tracts to estimate exposure per capita estimate exposure per capita (polygon on point)(polygon on point)

identify tracts traversed by identify tracts traversed by freeway for study of freeway for study of neighborhood blight (polygon neighborhood blight (polygon on lines)on lines)

integrate census data by integrate census data by block with sales data by zip block with sales data by zip code (polygon on polygon)code (polygon on polygon)

Spatial Matching via Polygon Overlay:Spatial Matching via Polygon Overlay:exampleexample

The two themes (land use & drainage basins) do not have common boundaries. GIS creates combined layer permitting calculation of land use by drainage basin.

a. b. c.

aGaA bA

bGcAcG

Land Use

DrainageBasins

A.G.

Atlantic

Gulf

Combined layer

Point-pointPoint-point is within , e.g. find all of the customer points within 1 km of this retail store point is within , e.g. find all of the customer points within 1 km of this retail store point is nearest to , e.g. find the hazardous waste site which is nearest to this groundwater is nearest to , e.g. find the hazardous waste site which is nearest to this groundwater

well well Point-linePoint-line ends at , e.g. find the intersection at the end of this street ends at , e.g. find the intersection at the end of this street is nearest to , e.g. find the road nearest to this aircraft crash site is nearest to , e.g. find the road nearest to this aircraft crash site Point-areaPoint-area is contained in , e.g. find all of the customers located in this ZIP code boundary is contained in , e.g. find all of the customers located in this ZIP code boundary can be seen from , e.g. determine if any of this lake can be seen from this viewpoint can be seen from , e.g. determine if any of this lake can be seen from this viewpoint Line-lineLine-line crosses , e.g. determine if this road crosses this river crosses , e.g. determine if this road crosses this river comes within , e.g. find all of the roads which come within 1 km of this railroad comes within , e.g. find all of the roads which come within 1 km of this railroad flows into , e.g. find out if this stream flows into this river flows into , e.g. find out if this stream flows into this river Line-areaLine-area crosses , e.g. find all of the soil types crossed by this railroad crosses , e.g. find all of the soil types crossed by this railroad borders , e.g. find out if this road forms part of the boundary of this airfield borders , e.g. find out if this road forms part of the boundary of this airfield Area-areaArea-area overlaps , e.g. identify all overlaps between types of soil on this map and types of overlaps , e.g. identify all overlaps between types of soil on this map and types of

land use on this other map land use on this other map is nearest to , e.g. find the nearest lake to this forest fire is nearest to , e.g. find the nearest lake to this forest fire is adjacent to , e.g. find out if these two areas share a common boundary is adjacent to , e.g. find out if these two areas share a common boundary

Spatial Operations:Spatial Operations:GeocodingGeocoding

assigning spatial coordinates (explict location) to assigning spatial coordinates (explict location) to addresses (implicit location)addresses (implicit location)

usually assigns x,y coordinates; could be lat/longusually assigns x,y coordinates; could be lat/long requires street network file with street attribute requires street network file with street attribute

information (street name and number range for information (street name and number range for each block) for all street segments (blocks)each block) for all street segments (blocks)

precise matching of street names can be precise matching of street names can be problemmaticproblemmatic– completeness (esp. for ‘new’ streets) importantcompleteness (esp. for ‘new’ streets) important– PO boxes, building names, and apartment complex PO boxes, building names, and apartment complex

names cause problems.names cause problems.

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

Regionalization: census tracts grouped into neighborhoods

Classification: cities categorized as central city or suburbssoils classified as igneous, sedimentary, metamorphic

Spatial Operations:Spatial Operations:spatial aggregation (dissolving)spatial aggregation (dissolving)

Groupings may be:Groupings may be: formal (based on in situ formal (based on in situ

characteristics)characteristics)e.g. city neighborhoodse.g. city neighborhoods

functional (based on flows or links): functional (based on flows or links): e.g. commuting zonese.g. commuting zones

districting/redistrictingdistricting/redistricting– grouping grouping contiguous contiguous polygons into polygons into

districtsdistricts– original polygons original polygons preservedpreserved

regionalizationregionalization– grouping polygons into contiguous grouping polygons into contiguous

regionsregions– original polygon boundaries original polygon boundaries dissolveddissolved

classificationclassification– grouping polygons into grouping polygons into non-non-

contiguous contiguous regionsregions– original boundaries usually dissolvedoriginal boundaries usually dissolved– usually ‘formal’ groupingsusually ‘formal’ groupings

Examples:Examples: elementary school zones to high elementary school zones to high

school attendance zones (school attendance zones (functional functional districtingdistricting))

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

creating police precincts (creating police precincts (funct. regfunct. reg.).) creating city neighborhood map creating city neighborhood map

((form. reg.form. reg.)) grouping census tracts into market grouping census tracts into market

segments--yuppies, nerds, etc segments--yuppies, nerds, etc ((class.class.))

creating soils or zoning map (creating soils or zoning map (classclass))

Advanced Applications:Advanced Applications:Network AnalysisNetwork Analysis

RoutingRouting shortest path between shortest path between

two pointstwo points– direction instructions direction instructions

(locating hotel from (locating hotel from airport)airport)

travelling salesman: travelling salesman: shortest path connecting shortest path connecting n pointsn points– bus routing, delivery bus routing, delivery

driversdrivers

DistrictingDistricting expand from site along network until expand from site along network until

criteria (time, distance, cost, object criteria (time, distance, cost, object count) is reached; then assign area to count) is reached; then assign area to districtdistrict– creating market areas, attendance creating market areas, attendance

zones, etczones, etc

AllocationAllocation assign locations to the nearest centerassign locations to the nearest center

– assign customers to pizza delivery assign customers to pizza delivery outletsoutlets

draw boundaries (lines of draw boundaries (lines of equidistance) based on the above equidistance) based on the above – market area creationmarket area creation– example of application of Thiessen example of application of Thiessen

polygonspolygonsIn all cases, ‘distance’ may be measured in miles, time, cost or other ‘friction’ (e.g pipe diameter for water, sewage, etc.). Arc or node attributes (e.g one-way streets, no left turn) may also be critical.