lecture 9geog2590 - gis for physical geography1 outline: – introduction – multi-criteria...

Lecture 9 GEOG2590 - GIS for Physical Geography

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Outline:– Introduction– Multi-criteria evaluation (MCE)– Multi-objective land allocation (MOLA)– Examples

Lecture 9.Lecture 9.Land suitability Land suitability

modellingmodelling


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IntroductionIntroduction

• Land is a scarce resource– essential to make best possible use– identifying suitability for:

agriculture forestryrecreationhousingetc.


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Sieve mappingSieve mapping

• Early methods– Ian McHarg (1969) Design with Nature

tracing paper overlays landscape architecture and facilities

location

– Bibby & Mackney (1969) Land use capability classification tracing paper overlaysoptimal agricultural land use mapping


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GIS approachesGIS approaches

• Sieve mapping using:– polygon overlay (Boolean logic)– cartographic modelling– Example uses:

nuclear waste disposal site locationhighway routing land suitability mappingetc.


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Question…Question…

• What problems or limitations are there with the sieve mapping approach?


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Multi-criteria Multi-criteria evaluationevaluation

• Basic MCE theory:– “Investigate a number of choice

possibilities in the light of multiple criteria and conflicting objectives” (Voogd, 1983)

– generate rankings of choice alternativessimple linear programming algorithmsmulti-objective optimisationmulti-dimensionality of planning problems


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Principles of MCEPrinciples of MCE

• Methodology– construct evaluation matrix…

– standardisation (normalisation) of criterion scores

– evaluation of matrix using MCE algorithms

S11…..SI1

S = . .

S1J…..SIJ


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MCE techniquesMCE techniques

• Many techniques– most developed for evaluating small

matrices– suitability for large (GIS) matrices?

layers = criterion scorescells or polygons = choice alternatives

– incorporation of levels of importance (weights)

– Incorporation of constraint maps– e.g. ideal point analysis, weighted linear

summation, hierarchical optimisation, etc.


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Example: weighted linear Example: weighted linear summationsummation

User weights

Map 1 Map 2 Map 3 Map 4

Evaluation matrix

MCE routine

Output

Standardise


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Multi-objective land Multi-objective land allocationallocation

• Basic MOLA theory:– procedure for solving multi-objective land

allocation problems for cases with conflicting objectivesbased on information from set of suitability

mapsone map for each objectiverelative weights assigned to objectivesamount of area to be assigned to each land

use

– determines compromise solution that attempts to maximize suitability of lands for each objective given weights assigned


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Principles of MOLAPrinciples of MOLA

• Methodology– construct ranked suitability maps for

each objective using MCE – decide on relative objective weights

and area tolerances– evaluate conflict demands on limited

land via iterative process


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Example: protected Example: protected areasareas

• Multi-layered system in Britain:– National Parks, Areas of Outstanding

Natural Beauty, Heritage Coasts, Special Areas of Conservation, Special Protection Areas, Sites of Special Scientific Interest, Nature Reserves, Ramsar Sites, National and Community Forests, Environmentally Sensitive Areas, National Scenic Areas, Regional Parks, Common Land, and Less Favoured Areas


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Protected areas in BritainProtected areas in Britain


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Identifying “wilderness” Identifying “wilderness” areasareas

• Wilderness Britain?– continuum of environmental modification

from “paved to the primeval” (Nash, 1981)

– the “Wilderness Continuum” concept– measurable and mappable?

remoteness from settlementremoteness from mechanised accessapparent naturalness (lack of human artefacts)biophysical naturalness (ecological integrity)


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Factor mapsFactor maps

Apparent naturalness Biophysical naturalness

Remoteness from mechanised access

Remoteness from settlement


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Possible solutionsPossible solutions

Stressing naturalness Stressing remotenessEqually weighted


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Wild and city park outputWild and city park output

Wild park with & without existing protected areas

constraint

City park with & without existing protected areas

constraint


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MOLA Results: wild park vs city MOLA Results: wild park vs city parkpark

Suitability for wild park

Suitability for city park

MOLA results (yellow = wild park, red = city park, blue = constraints


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ConclusionsConclusions

• Few GIS packages provide MCE functionality (e.g. Idrisi32)

• Most GIS provide facilities for building MCE analyses (e.g. Arc/Info GRID)

• Important method for:– site and route selection– land suitability modelling


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PracticalPractical

• MCE in GRID• Task: Locate suitable sites for a wind farm in the

Yorkshire Wolds using MCE• Data: The following datasets are provided…

– Digital elevation model (50m resolution 1:50,000 OS Panorama data)

– Contour data (10m interval 1:50,000 OS Panorama data)

– ITE land cover map (25m resolution)– Population data (200m resolution)– Roads (1:250,000 Meridian data)– Wind speed data


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PracticalPractical

• Steps:1. Decide on criterion/factors required

(including any constraints)2. Pre-process factor and constraint

maps (including standardisation of factor maps)

3. Decide on factor weights4. Build and run MCE model5. Display results


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PracticalPractical

• Experience with building and running MCE models in Arc/Info GRID

• Familiarity with MCE techniques and data requirements


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Next week…Next week…

• Spatial Decision Support Systems– principles and theory– examples– online SDSS

• Practical: Siting radioactive waste disposal facilities using web-based SDSS

lecture 9geog2590 - gis for physical geography1 outline: – introduction – multi-criteria...

Documents

limited land

common land

relative objective weights

sensitive areas

suitability of lands

special areas of conservation

special protection areas

national scenic areas