land use modelling in switzerland using land u se s tatistic data
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Land‐use modelling in Switzerland using land u se s tatistic data. Context. Socio-economic processes are strong drivers of land- use change across Europe Land abandonment has been a dominant process Urbanisation is increasing at a rapid rate

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context
Context
  • Socio-economicprocessesare strong driversof land-usechangeacross Europe
  • Land abandonmenthasbeen a dominant process
  • Urbanisation isincreasing at a rapid rate
  • Increasingpushestowardsrenewableenergysources

=

  • Unknownextentandlocationoflandusechanges
  • Unknownimpact on landscapeservices
land cover change scenarios
Land coverchangescenarios
  • Over-archingprocesses
    • Population growth
    • Economicgrowth
    • Political change
      • newenergypolicy
      • conservationpolicy, etc
  • Storylinesforfuturescenariosto 2035
    • Relatedto IPCC storylinesfordevelopment (A1, A2, B1, B2)
  • Drivers oflandcoverchange
    • Land abandonment
    • Urban sprawl
    • Land useintensification
slide4

Globalisation, High global economic growth but low Swiss growth

(A1)

Heterogeneous world, regionally centered growth, (comparatively) high economic growth for Switzerland (A2)

Lessintervention

¨Drivingforces

Population

Economy

….

More global

More regional

Globalisation but emphasis on services, high ecological concerns. Low Swiss growth (B1)

Self-sufficiency, Regionally centered development, high ecological concerns (B2)

More intervention

slide5

Low population growth

  • Average technological innovation
  • Increased food importation
  • Low levels of policy-led restrictions on development
  • High population growth
  • High per capita urban demand
  • Low support for subsidies
  • Low to no policy-led restrictions on development

Globalisation, High global economic growth but low Swiss growth

(A1)

Heterogeneous world, regionally centered growth, (comparatively) high economic growth for Switzerland (A2)

Lessintervention

¨Drivingforces

Population

Economy

….

More global

More regional

Globalisation but emphasis on services, high ecological concerns. Low Swiss growth (B1)

Self-sufficiency, Regionally centered development, high ecological concerns (B2)

More intervention

  • Medium population growth
  • Average technological innovation
  • Strong support for local agriculture
  • Strong policy-led restrictions on development
  • Strong support for subsidies
  • Very low - no population growth
  • Low technological innovation
  • Increased food importation
  • Policy-led restrictions on development
  • Support for subsidies
base dataset
Base dataset

Swiss land-use statistics (Arealstatistik der Schweiz)

  • Aerial photography interpretation
  • 100m grid = each point represents 1ha
  • 72 categories of land-use/cover in theme areas
    • Settlement and urban
    • Agricultural areas
    • Wooded areas
    • Unproductive
  • 3 time points
    • 1979/85
    • 1992/97
    • 2004/2009

1997

2009

1985

land use land cover types classification
Land use/land cover types classification

Closed Canopy Forest

Open Forest/ Scrub

Overgrown

Areas

Urban

Areas

PastureAgriculture

ArableAgriculture

slide8

Land coverchangescenarios

  • Agriculturalchange
  • Land abandonment, marginal open areastoforest
  • Agriculturalintensification
  • Urbanisation
  • high densityhousing
  • newsettlements

Arealstatistik

1985

1997

Land usedemand

Initial State

2009

Land-usesuitability 1ha resolution

Dyna-CLUEModellingframework

(P. Verburg, University of Amsterdam)

Land usesuitability

Mapsof land-usechangescenarios

Environmental

data

explanatory variables
Explanatory variables
  • Biogeographical (Static, 1ha)
    • Continentality index CSD/DEM25 (Zimmermann & Kienast 1999)
    • Yearly moisture index CSD/DEM25 (Zimmermann & Kienast 1999)
    • Yearly direct solar radiation CSD/DEM25 (Zimmermann & Kienast 1999)
    • Precipitation average growing season CSD/DEM25 (Zimmermann & Kienast 1999)
    • No. of summer precipitation days CSD/DEM25 (Zimmermann & Kienast 1999)
    • Elevation DEM100
    • Slope DEM100
    • Sine of aspect (east) DEM100
    • Cos of aspect (north) DEM100
    • Soil permeability Soil suitability maps BLW 2012
    • Soil stoniness Soil suitability maps BLW 2012
    • Soil suitability for agriculture Soil suitability maps BLW 2012
  • Socio-economic (temporally variable, per Gemeinde)
    • Taxable income per tax paying resident Federal Office for Statistics
    • Percentage inhabitants employed in primary sector Federal Office for Statistics
    • Public Transport accessibility Federal Office for Spatial Planning
  • Infrastructure (temporally variable, 1ha)
    • Distance to major roads Vector25
    • Distance to access roads Vector25
  • Neighbourhood variables
    • No. of neighbours in classes (Urban, closed forest, agriculture)
    • Distance to forest
model suitability for land use type
Model suitability for land use type

Explanatory variables/ Environmental

data

Landcover (AS)

Logistic

Regression

Modelling

Maximum

Entropy

Random

Forests

Land usesuitability

logistic regression
Logistic regression
  • Cross correlationanalysis, removalofhighlycorrelatedexplanatory variables
  • Sampling withineach land-use type
    • Unequalacrosslandcovertypes
    • ~5% of total points
    • Sampling presenceandabsence
    • Minimum 1km apart toavoidspatialautocorrelationissues
    • Small classes (overgrown) fewersamples
    • Capturingwithinclassvariability – geographicaland environmental space
  • Model averaging
    • Every combinationofexplanatory variables to find best fit model (AIC)
    • Averagingprocesstodeterminecoefficientforeachexplanatory variable
quantification of scenarios
Quantification of Scenarios
  • Population growth scenarios defined by the Swiss Federal Statistics Office
  • Per capita urban demand (Swiss Federal Statistics Office)
    • Mean
    • Upper and lower 95% CI bounds
  • Agricultural demand related to population and level of imports
  • Land cover change restrictions representing policy and planning
    • Conversion restrictions
    • Spatial restrictions
  • Common to all scenarios
    • Forests and current National Parks/protected areas are ‘sacred’
slide13

Quantificationof Scenarios

Trend Scenario

  • Linear Interpolation of 1985-1997-2009 trend in growth (orreduction) oflanduseclasses

A1 (Global/Low Intervention)

  • BfS ‘Low’ populationgrowthscenario, mean urban areademand per capita
  • Nofurtherspatialrestrictions

A2 (Regional/Low Intervention)

  • BfS ‘High’ populationgrowthscenario, high urban areademand per capita
  • Weightingof urban suitabilitytoreflectimprovedpublictransportconnectivity in regional areas
  • Nofurtherspatialrestrictions

B1 (Global/High Intervention)

  • ‘Stagnation’ scenarioforpopulationgrowth (nogrowth), low urban areademand per capita
  • Restrictions on urbanisationthroughexisitingbuildingzones (‘Bauzone’)
  • Restrictions on conversionfrompasturetoovergrownabove 900m asl
  • IncreaseddemandforAgriculture

B2 (Regional/High Intervention)

  • BfS ‘Medium’ populationgrowthscenario, mean per captia urban areademand
  • Restrictions on conversionfrompasturetoovergrownabove 900m asl
  • Weightingof urban suitabilitytoreflectimprovedpublictransportconnectivity in regional areas
  • Urban growthpermitted outside of ‘Bauzone’ -regionalisation
results land cover transitions
Results: land cover transitions

Land abandonment

Urbanisation

Reforestation

summary key results
Summary Key Results
  • Strongest scenario is A2 (regionalisation, low intervention)
    • Strong trend to urban sprawl, especially in lowlands
    • Land use intensification in lowlands
    • Land abandonment in Alps
    • Concentration of growth despite weighting for regionalisation
  • Population growth is key driver of land cover change, but
  • Planning/Policy restrictions can have mitigating control
    • Conservation policy to prevent land abandonment
    • Building zone controls
thanks
Swiss Federal Institute for Snow, ForestandLandscaperesearch, WSL Thanks

Questions?

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