GIS Technology in Transition Moving Maps to Mapped Data, Spatial Analysis and Beyond Presented by Joseph K. Berry GIS is more different than it is similar

GIS Technology in TransitionGIS Technology in Transition

Moving Maps to Mapped Data, Spatial Analysis and BeyondMoving Maps to Mapped Data, Spatial Analysis and Beyond

Presented byPresented by Joseph K. BerryJoseph K. Berry

GIS is more different than it is GIS is more different than it is similar to similar to

traditional mapping and data traditional mapping and data analysisanalysisBerry & Associates // Spatial Information SystemsBerry & Associates // Spatial Information Systems

2000 South College Ave, Suite 300, Fort Collins, CO 805252000 South College Ave, Suite 300, Fort Collins, CO 80525Phone: (970) 215-0825 Email: [email protected]: (970) 215-0825 Email: [email protected]

……visit our website atvisit our website at www.innovativegis.com/basiswww.innovativegis.com/basis

2003 Northwest GIS User Group Meeting2003 Northwest GIS User Group MeetingSeptember 16, 2003 – Skamania Lodge, Stevenson, Washington September 16, 2003 – Skamania Lodge, Stevenson, Washington

Traditional MappingTraditional Mapping manually drafted map manually drafted map

Historical Setting and GIS EvolutionHistorical Setting and GIS Evolution

Computer MappingComputer Mapping automates the cartographic process (70s) automates the cartographic process (70s)

Spatial Database ManagementSpatial Database Management links computer mapping techniques with links computer mapping techniques with

traditional database capabilities (80s)traditional database capabilities (80s)

GIS ModelingGIS Modeling representation of relationships withinrepresentation of relationships within

and among mapped data (90s) and among mapped data (90s)

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(Berry)(Berry)Indelix, www.idelix.com Indelix, www.idelix.com

Map Map DisplayDisplay

Where is What Where is What …and Wow…and Wow

ConnectivityConnectivity and and Map DeliveryMap Delivery

SDT, www.spatialdatatech.com SDT, www.spatialdatatech.com

WHAT -- databaseWHAT -- database

WHERE – Digital MapWHERE – Digital Map

Mapped data can be queried by interacting Mapped data can be queried by interacting with the map (where) or database with the map (where) or database (what)(what)

Query BuilderQuery Builder

1)1) Select forest type Aspen, Select forest type Aspen, SP1= AwSP1= Aw2) Select tall Aspen stands, 2) Select tall Aspen stands, Height > 20mHeight > 20m

Where is What and Wow to…Where is What and Wow to… Why and So WhatWhy and So What

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Vector-basedVector-based processing provides Mapping processing provides Mapping and Geo-Query capabilities that and Geo-Query capabilities that repackage repackage existing spatial dataexisting spatial data as reports and displays as reports and displays

Discrete ObjectsDiscrete Objects

Descriptive MappingDescriptive Mapping

WHERE IS WHATWHERE IS WHAT

Grid-basedGrid-based processing processing provides Map Analysis provides Map Analysis capabilities that capabilities that derive derive new informationnew information on on relationships within and relationships within and among mapped dataamong mapped data Continuous SurfacesContinuous Surfaces

Prescriptive MappingPrescriptive Mapping

WHY AND SO WHATWHY AND SO WHAT

Simple Erosion ModelSimple Erosion Model

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……a a Command Command Macro LanguageMacro Language consists of a consists of a graphical graphical interface for interface for entering, editing, entering, editing, executing, executing, documenting, documenting, storing and storing and retrieving a GIS retrieving a GIS Model Model

……GIS ModelingGIS Modeling involves logical sequencing of map involves logical sequencing of map analysis operationsanalysis operations

Script

Logic

Variable-Width BufferVariable-Width Buffer (Sediment loading)(Sediment loading)

Simple Buffer

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Effectively far away, though right near a stream

…how can that be? …what about different soils? …what about roughness? …or time of year?

Characterizing Slope (and Aspect)Characterizing Slope (and Aspect)A digital terrain surface is formed by assigning A digital terrain surface is formed by assigning an elevation value to each cell in an analysis an elevation value to each cell in an analysis grid. The “slant” of the terrain at any location grid. The “slant” of the terrain at any location can be calculatedcan be calculated– inclination of a plane fitted – inclination of a plane fitted to the elevation values of the immediate vicinity. to the elevation values of the immediate vicinity.

Micro Terrain AnalysisMicro Terrain Analysis

Calculation of slope considers Calculation of slope considers the arrangement and magnitude the arrangement and magnitude of elevation differencesof elevation differences

““Map-ematics”Map-ematics”

(Berry)(Berry)(See Map Analysis, “Topic 11” for more information)(See Map Analysis, “Topic 11” for more information)

Characterizing Surface FlowCharacterizing Surface FlowThe relative amount of water passing through The relative amount of water passing through each grid cell is determined by simulating a each grid cell is determined by simulating a drop of water landing in each cell and drop of water landing in each cell and proceeding downhill by the steepest path. The proceeding downhill by the steepest path. The number of paths crossing each location number of paths crossing each location identifies the total uphill confluence.identifies the total uphill confluence.

Map AnalysisMap Analysis

Data MiningData Mining investigates the “numerical” relationships in mapped data…investigates the “numerical” relationships in mapped data…

DescriptiveDescriptive— — aggregate statistics (e.g., average/stdev, similarity, clustering)aggregate statistics (e.g., average/stdev, similarity, clustering) PredictivePredictive— — relationships among maps (e.g., regression)relationships among maps (e.g., regression) PrescriptivePrescriptive— — appropriate actions (e.g., optimization) appropriate actions (e.g., optimization)

Surface ModelingSurface Modeling maps the spatial distribution and pattern of point data…maps the spatial distribution and pattern of point data…

Map GeneralizationMap Generalization— — characterizes spatial trends (e.g., titled plane)characterizes spatial trends (e.g., titled plane) Spatial InterpolationSpatial Interpolation— — deriving spatial distributions (e.g., IDW, Krig)deriving spatial distributions (e.g., IDW, Krig) OtherOther— — roving window/facets (e.g., density surface; tessellation)roving window/facets (e.g., density surface; tessellation)

Spatial AnalysisSpatial Analysis investigates the “contextual” relationships in mapped data…investigates the “contextual” relationships in mapped data…

ReclassifyReclassify— — reassigning map values (position; value; size, shape; contiguity) reassigning map values (position; value; size, shape; contiguity) OverlayOverlay— — map overlay (point-by-point; region-wide; map-wide)map overlay (point-by-point; region-wide; map-wide) DistanceDistance— proximity and connectivity (movement; optimal paths; visibility)— proximity and connectivity (movement; optimal paths; visibility) NeighborsNeighbors— — ”roving windows” (slope/aspect; diversity; anomaly)”roving windows” (slope/aspect; diversity; anomaly)

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Map GeneralizationMap Generalization— — characterizes spatial trends (e.g., titled plane)characterizes spatial trends (e.g., titled plane) Spatial InterpolationSpatial Interpolation— — deriving spatial distributions (e.g., IDW, Krig)deriving spatial distributions (e.g., IDW, Krig) OtherOther— — roving window/facets (e.g., density surface; tessellation) roving window/facets (e.g., density surface; tessellation)



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Spatial InterpolationSpatial Interpolation (Geographic Distribution)(Geographic Distribution)

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““Surface ModelingSurface Modeling” is similar to slapping a big chunk of modeler’s clay ” is similar to slapping a big chunk of modeler’s clay over the “data spikes,” then taking a knife and cutting away the excess to over the “data spikes,” then taking a knife and cutting away the excess to

leave a leave a continuous surfacecontinuous surface that encapsulates the peaks and valleys implied that encapsulates the peaks and valleys implied by the spatial pattern of the field samplesby the spatial pattern of the field samples

……nearby things are more alike than distant things nearby things are more alike than distant things

Mapping the VarianceMapping the Variance

Spatial StatisticsSpatial Statistics seeks to seeks to map the variancemap the variance

Spatial Interpolation is Spatial Interpolation is similar to throwing a similar to throwing a

blanket over the “data blanket over the “data spikes” to conforming to spikes” to conforming to the geographic pattern the geographic pattern

of the data.of the data.

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Non-Spatial statisticsNon-Spatial statistics seeks seeks the “typical” condition and the “typical” condition and

applies uniformly applies uniformly throughout geographic throughout geographic

space-- space-- AVERAGEAVERAGE








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Visualizing Spatial RelationshipsVisualizing Spatial Relationships

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What What spatial spatial relationshipsrelationships do do you see?you see?……do relatively high levels do relatively high levels of P often occur with high of P often occur with high levels of K and N?levels of K and N?

……how often?how often?

……where?where?

Interpolated Spatial DistributionInterpolated Spatial Distribution

Phosphorous (P)

Clustering MapsClustering Maps

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……groups of “floating balls” in data space identify locations in the field groups of “floating balls” in data space identify locations in the field with similar data patterns– with similar data patterns– data zonesdata zones

The Precision Ag ProcessThe Precision Ag Process (Fertility example)(Fertility example)

As a combine moves through a field As a combine moves through a field 1)1) it uses GPS to check its location then it uses GPS to check its location then 2)2) checks checks the yield at that location to the yield at that location to 3)3) create a continuous map of the yield variation every few create a continuous map of the yield variation every few feet. This map feet. This map 4)4) is combined with soil, terrain and other is combined with soil, terrain and other maps to derive a maps to derive a 5)5) “Prescription Map” that is used to “Prescription Map” that is used to 6)6) adjust fertilization levels every few feet in the field. adjust fertilization levels every few feet in the field.

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Variable Rate ApplicationVariable Rate Application

Step 6)Step 6)

Cyber-Farmer, Circa 1992Cyber-Farmer, Circa 1992

Farm dBFarm dBStep 4)Step 4)


On-the-Fly On-the-Fly Yield MapYield Map

Steps 1) – 3)Steps 1) – 3)

Prescription MapPrescription MapStep 5)Step 5)

Zone 1

Zone 3

Zone 2

Spatial Data MiningSpatial Data Mining

……making sense out of a map stackmaking sense out of a map stack

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Mapped data that Mapped data that exhibits high exhibits high spatial spatial dependencydependency create create strong prediction strong prediction functions. As in functions. As in traditional statistical traditional statistical analysis, spatial analysis, spatial relationships can be relationships can be used to predict used to predict outcomesoutcomes

……the difference is the difference is that spatial statisticsthat spatial statisticspredicts wherepredicts where responses will be responses will be high or lowhigh or low

Precision Ag

Precision Conservation

Leaching Leaching

Leaching

Chemicals

Runoff

SoilErosion

Wind Erosion

Precision Ag to Precision Conservation Precision Ag to Precision Conservation From a From a FieldField perspective to perspective to WatershedWatershed, , LandscapeLandscape and and EcosystemEcosystem perspective perspective

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SURFACE MODELINGSPATIAL DATA MINING

Isolated Perspective

2-dimensional

Interconnected Perspective

3-dimensional

SPATIAL ANALYSIS








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Elevation Surface

Overland Flow Model

1)1) The The PipelinePipeline is positioned on the is positioned on the Elevation surfaceElevation surface

1) Pipeline

2)2) Flow from Flow from Spill PointsSpill Points along the pipeline are simulated along the pipeline are simulated

X2) Spill Point #1

3)3) High Consequence AreasHigh Consequence Areas (HCA) are identified (HCA) are identified

3) HCA

4)4) A A ReportReport is written identifying flow paths that cross HCA areas is written identifying flow paths that cross HCA areas

X

HCA Impact

4) Report

5)5) Overland flow is halted when Overland flow is halted when Flowing WaterFlowing Water is encountered (Channel Flow Model) is encountered (Channel Flow Model)

5) Flowing Water

Spill Migration ModelingSpill Migration Modeling

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Types of Surface FlowsTypes of Surface Flows

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Common sense suggests that “water flows downhill” Common sense suggests that “water flows downhill” however the corollary is “…but not always the same way.” however the corollary is “…but not always the same way.”

Characterizing Overland Flow and QuantityCharacterizing Overland Flow and Quantity

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Intervening terrain and conditions form Intervening terrain and conditions form Flow ImpedanceFlow Impedance and and Quantity Quantity maps that are used to estimate flow time and retentionmaps that are used to estimate flow time and retention

Simulating Different Product TypesSimulating Different Product Types

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Flow Velocity is a function of—Flow Velocity is a function of—

Specific Gravity Specific Gravity (p),(p), Viscosity Viscosity (n)(n) and Depth and Depth (h)(h) of product of productSlope Angle Slope Angle (spatial variable computed for each grid cell)(spatial variable computed for each grid cell)

Physical properties combine with terrain/conditions to model Physical properties combine with terrain/conditions to model the flow of different product types the flow of different product types

Characterizing Impacted AreasCharacterizing Impacted Areas

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Flows from spill 1, 2 and 3Flows from spill 1, 2 and 3

The minimum time for flows from The minimum time for flows from all spills…all spills…

Drinking water HCADrinking water HCA Impacted portion of the Drinking water HCAImpacted portion of the Drinking water HCA

characterizes the impact characterizes the impact for the High Consequence Areas for the High Consequence Areas

Modeling Stream Channel FlowModeling Stream Channel Flow

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Channel Flow Model

1) Channel Flow Time

0 hr

7.3 hr

8.4 hr

9.6 hr

10.8 hr10.1 hr

13.1 hr

11.2 hr

13.6 hr

1)1) Channel FlowChannel Flow times along stream network segments are added times along stream network segments are added

BasePoint

2)2) Overland FlowOverland Flow time and quantity at entry is noted time and quantity at entry is noted

X

.14

.12

.27.12

.25.72.78

X

Overland Flow (2.5 hours)

2) Overland Flow Entry Time

X = 12.10 + .36 = 12.46 hr away from Base Point

11.2 hr

13.1 hr

3)3) Impacted High Consequence AreasImpacted High Consequence Areas (HCA) are identified (HCA) are identified

In= 11.46 hr

Out= 9.86 hr

HCA

3) Impacted HCA Times

HCA

HCA

HCA

HCA

HCA

4)4) Report Report is written identifying flow paths that cross HCA areas is written identifying flow paths that cross HCA areas

4) Report of Impacted HCA’s

2.5 + (12.46 -11.46) = 3.5 hours total

Modeling Customer FlowModeling Customer Flow

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……customer flow along a road customer flow along a road network is similar to water network is similar to water

flowing in a stream channelflowing in a stream channel

……a a Travel-time MapTravel-time Map identifies identifies the time to travel from the time to travel from

anywhere to a storeanywhere to a store

Competition AnalysisCompetition Analysis

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… … travel-time travel-time surfaces for two surfaces for two different storesdifferent stores

… … can be compared for relative travel-time advantagecan be compared for relative travel-time advantage

Transmission Line Siting ModelTransmission Line Siting Model

CriteriaCriteria – the transmission line route should… – the transmission line route should…

Avoid areas ofAvoid areas of high housing densityhigh housing density

Avoid areas that areAvoid areas that are far from roadsfar from roads

Avoid areasAvoid areas within or near sensitive areaswithin or near sensitive areas

Avoid areas of highAvoid areas of high visual exposure to housesvisual exposure to houses

HousesHouses

RoadsRoads

Sensitive AreasSensitive Areas

HousesHouses

ElevationElevation

GoalGoal – identify the– identify the best route for an electric best route for an electric transmission linetransmission line that considers various criteria that considers various criteria for minimizing adverse impacts.for minimizing adverse impacts.

Existing PowerlineExisting Powerline

Proposed Proposed SubstationSubstation

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AVOID AREAS OF HIGH AVOID AREAS OF HIGH VISUAL EXPOSURE VISUAL EXPOSURE

TO HOUSESTO HOUSES

Step 1. Visual Exposure levels (0-40 times Visual Exposure levels (0-40 times seen) are translated into values indicating seen) are translated into values indicating relative cost (1=low to 9=high) for siting a relative cost (1=low to 9=high) for siting a transmission line at every location in the transmission line at every location in the project area. project area.

HOUSESHOUSES

ELEVATIONELEVATION

VISUAL VISUAL EXPOSUREEXPOSURETO HOUSESTO HOUSES

DISCRETEDISCRETECOSTCOSTMAPMAP

Routing and Optimal PathsRouting and Optimal Paths

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ACCUMULATEDACCUMULATEDCOSTCOST

SURFACESURFACE

EXISTINGEXISTINGPOWERLINEPOWERLINE

(START)(START)

Step 2.Step 2. Accumulated Accumulated Cost from the Cost from the existing powerline to existing powerline to all other locations is all other locations is generated based on generated based on the Discrete Cost the Discrete Cost map.map.

MOST MOST PREFERRED PREFERRED

ROUTEROUTE

PROPOSEDPROPOSEDSUBSTATIONSUBSTATION

(END)(END)

Step 3.Step 3. The steepest The steepest downhill path from downhill path from the Substation over the Substation over the Accumulated the Accumulated Cost surface Cost surface identifies the “least identifies the “least cost path”—cost path”—

Most Preferred RouteMost Preferred Routeavoiding areas of high avoiding areas of high

visual exposurevisual exposure

Considering Multiple CriteriaConsidering Multiple Criteria

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HOUSINGHOUSINGDENSITY

AVOID AREAS OF HIGHHOUSINGDENSITY

ROADSPROXIMITYTO ROADS

AVOIDAREAS

THAT AREFAR FROM

ROADS

SENSITIVEAREAS

PROXIMITYTO

SENSITIVEAREAS

AVOIDAREAS

IN OR NEARSENSITIVE

AREAS

VISUALEXPOSURETO HOUSES

AVOIDAREAS

OF HIGHVISUAL

EXPOSURE

AVERAGECOST

STARTINGLOCATION

ACCUMULATIONSURFACE

ENDINGLOCATION

MOSTPREFERRED

ROUTE

AVOID AREAS OF HIGH HOUSING DENSITY

AVOID AREAS THAT ARE FAR FROM ROADS

AVOID AREAS IN OR NEAR SENSITIVE AREAS

HOUSING

AVOID AREAS OF HIGH VISUAL EXPOSURE

START

END

BaseMaps

DerivedMaps

Cost/AvoidanceMaps

AVG_COST

ACUMM_COST

BEST_ROUTE

CriteriaCriteria – the transmission line route should – the transmission line route should avoid…avoid…

Areas ofAreas of high housing densityhigh housing density Areas that areAreas that are far from roadsfar from roads Areas Areas within or near sensitive areaswithin or near sensitive areas Areas of highAreas of high visual exposure to housesvisual exposure to houses

ELEVATION

Step 2Step 2

Accumulated CostAccumulated Cost

Step 3Step 3

Steepest PathSteepest Path

Step 3Step 3 Discrete CostDiscrete Cost

Considering Multiple CriteriaConsidering Multiple Criteria

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AVOID AREAS OF HIGH HOUSING DENSITY

AVOID AREAS THAT ARE FAR FROM ROADS

AVOID AREAS IN OR NEAR SENSITIVE AREAS

AVOID AREAS OF HIGH VISUAL EXPOSURE

START

END

BaseMaps

DerivedMaps

Cost/AvoidanceMaps

AVG_COST

ACUMM_COST

BEST_ROUTE

CriteriaCriteria – the transmission line route should – the transmission line route should avoid…avoid…

Areas ofAreas of high housing densityhigh housing density Areas that areAreas that are far from roadsfar from roads Areas Areas within or near sensitive areaswithin or near sensitive areas Areas of highAreas of high visual exposure to housesvisual exposure to houses

Step 2Step 2

Accumulated CostAccumulated Cost

Step 3Step 3

Steepest PathSteepest Path

Step 3Step 3 Steepest PathSteepest Path

Step 1Step 1 Discrete Preference Map Discrete Preference Map

… … identifies the relative preference of locating a identifies the relative preference of locating a transmission line at any location throughout a project transmission line at any location throughout a project area considering multiple criteriaarea considering multiple criteria

Least

MostPreferred

…average of the four individual

preference maps

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Step 2Step 2 Accumulated Preference Map Accumulated Preference Map

… … identifies the preference to construct the identifies the preference to construct the preferred transmission line from a starting preferred transmission line from a starting

location to everywhere in a project arealocation to everywhere in a project area

Splash AlgorithmSplash Algorithm – like tossing a stick into a pond with waves – like tossing a stick into a pond with waves emanating out and accumulating costs as the wave front movesemanating out and accumulating costs as the wave front moves

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Step 3Step 3 Most Preferred Route Most Preferred Route

… … the steepest downhill path over the the steepest downhill path over the accumulated preference surface identifies the accumulated preference surface identifies the

most preferred route — minimizes areas to avoidmost preferred route — minimizes areas to avoid

PreferredRoute

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Siting Model FlowchartSiting Model Flowchart (Model Logic)(Model Logic)

Model logic is captured in a flowchart where the boxes represent Model logic is captured in a flowchart where the boxes represent maps and lines identify processing steps leading to a spatial solutionmaps and lines identify processing steps leading to a spatial solution

Avoid areas of…Avoid areas of…

High Housing High Housing DensityDensity

Far from RoadsFar from Roads

In or Near In or Near Sensitive AreasSensitive Areas

High Visual High Visual ExposureExposure

Rankings Weights

……but what is high but what is high housing density and housing density and how important is it? how important is it? …etc?…etc?

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Calibrating Map LayersCalibrating Map Layers (Relative Preferences)(Relative Preferences)

Model calibration refers to establishing a consistent scale from 1 Model calibration refers to establishing a consistent scale from 1 (most preferred) to 9 (least preferred) for rating each map layer(most preferred) to 9 (least preferred) for rating each map layer

1 for 0 to 5 houses1 for 0 to 5 houses……group consensus is that group consensus is that low housing density is low housing density is most preferredmost preferred

The The Delphi ProcessDelphi Process is used to achieve is used to achieve consensus among consensus among group participants. group participants. It is a structured It is a structured method involving method involving iterative use of iterative use of anonymous anonymous questionnaires and questionnaires and controlled feedback controlled feedback with statistical with statistical aggregation of aggregation of group response.group response.

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Weighting Map LayersWeighting Map Layers (Relative Importance)(Relative Importance)

Model weighting establishes the relative importance among map Model weighting establishes the relative importance among map layers (model criteria) on a multiplicative scalelayers (model criteria) on a multiplicative scale

The The Analytical Hierarchy Process (AHP)Analytical Hierarchy Process (AHP) establishes relative importance among by establishes relative importance among by mathematically summarizing paired comparisons of map layers’ importance. mathematically summarizing paired comparisons of map layers’ importance.

HD * 10.38

R * 3.23

SA * 1.00

VE * 10.64

……group consensusgroup consensus is that housing density is very important (10.38 times more important than sensitive areas) is that housing density is very important (10.38 times more important than sensitive areas)

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Generating Alternate RoutesGenerating Alternate Routes (changing weights)(changing weights)

The model is run using three The model is run using three different sets of weights for the different sets of weights for the map layers—map layers—

……to generate three alternative to generate three alternative routes routes (draped over Elevation)(draped over Elevation)

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Transitioning Beyond MappingTransitioning Beyond Mapping

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Where is What and WowWhere is What and Wow mapping, geo-query, delivery mapping, geo-query, delivery and display…and display…

Data MiningData Mining investigates the “numerical” investigates the “numerical” relationships in mapped data…relationships in mapped data…

Surface ModelingSurface Modeling maps the spatial distribution maps the spatial distribution and pattern of point data…and pattern of point data…

Spatial AnalysisSpatial Analysis investigates the “contextual” investigates the “contextual” relationships in mapped data…relationships in mapped data…

(Berry)(Berry)

GIS technology is transitioning fromGIS technology is transitioning from

WhereWhere is is What What and and Wow Wow …to …to WhyWhy and and So WhatSo What

……for more importation online, seefor more importation online, see

GIS Technology in TransitionGIS Technology in Transition

……we’ve covered a lot, we’ve covered a lot, any questions? any questions?

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GIS Technology in Transition Moving Maps to Mapped Data, Spatial Analysis and Beyond Presented by Joseph K. Berry GIS is more different than it is similar