Upload
vantuyen
View
217
Download
0
Embed Size (px)
Citation preview
1st EC-JRC Urbanization Workshop
Modelling urbanization processes
in Europe
Filipe Batista and LUISA team
Ispra, 27th May 2015
EC-JRC-IES, Sustainability Assessment Unit http://ec.europa.eu/jrc/en/luisa/
2
Cities…
� Environmental and social issues: soil imperviousness,
pollution, local climate change, congestion, crime, spread
of diseases… But…
� Socio-economic and environmental advantages due
to scaling: economies of scale (more efficient use of
resources), concentration of critical mass and economic
opportunities, productivity, innovation, economic growth…
Super linear growth?
Bettencourt et al. (2007) PNASOECD (2014)
Regions with big cities experience more economic growth
Higher wages and more
innovation in bigger cities
4
5
Cities in Europe…
� Have expanded greatly in the last two centuries due to
economic growth and urbanization.
� But what is the future of cities in Europe in a period of
demographic decline? Which cities will win and which will
loose?
� Either way, the future of Europe is tied to the future of its
cities…
6
� What is LUISA
� How LUISA works
� Baseline trajectory of future urbanization
� On-going and future work
Contents
7
� What is LUISA
� How LUISA works
� Baseline trajectory of future urbanization
� On-going and future work
Contents
8
What is LUISA? (1)
� EC-based modeling platform: JRC (development and
application) ENV, REGIO, CLIMA (funders , costumers);
� Conceived to contribute to Territorial Impact Assessment of EU
policies in an integrated manner;
� More than one stand-alone model. It is a platform of inter-linked
data, processes, models and indicators;
� Linked to several upstream models to capture sector trends
and multi-policy scenarios;
9
What is LUISA? (2)
� A core, state-of-the-art, land use model simulates future land use
changes given a set of scenario specifications, and resolving
competition for land by the different sectors;
� Beyond conventional land use/cover modeling. From discrete land
use allocation to activity-based modeling:
� Endogenous dynamic allocation of population (implemented),
activities, and services (foreseen);
� Endogenous modelling of effects of infrastructure improvements
and other spatial planning policies.
10
Macro and exogenous dynamicsDemography, Economy
(define demand for land)
Local conditionsGeography, neighborhood effects, accessibility, soil
characteristics.
(define local suitabilities)
Land
allocation
Policies with
territorial impact
Current Land Uses;
Conversion rules,
transition costs, etc..
Eg. Zoning,
spatial planning
regulations
Eg. Policies
influencing macro
dynamics (usually
through scenarios)
What is LUISA? (3)
LUISA merges top-down and bottom-up dynamics:
11
What is LUISA? (4)
Main technical characteristics
� Originally based on the CLUE model family (EUClueScanner)
� Supported by the GeoDMS Data Model Server (GeoDMS)
� Spatial extent: EU-28
� Spatial resolution: 100 meters
� Thematic resolution: 8 fully simulated land use classes (+ agricultural breakdown +
‘abandoned’ land uses)
� Temporal resolution / time span: yearly / up to 2050
� Base-map: CORINE Land Cover 2006 ‘refined’
� Primary outputs: Maps of land use, population, and accessibility
� Secondary outputs: Spatially explicit thematic indicators
12
Main land use categories in LUISA
Urban areas Industrial/commercial areas
Forested areasAgricultural areas
13
� What is LUISA
� How LUISA works
� Baseline trajectory of future urbanization
� On-going and future work
Contents
Land requirements from different sectors are
estimated given exogenous macro-drivers:
Economy and Demography.
Computes land function indicators.
Resolves the spatial arrangement of land uses at
fine pixel scale, taking into consideration
competition for land, land suitability, and
neighborhood.
14
Demand
module
Allocation
module
Indicator
module
Accessibility
Nr. of people
3 tier structure
151 June 2015
100 m pixels
Biophysical & economic suitability
Regions (NUTS2)
Regional land demands
Allow rules + discrete allocationNeighbourhood
dependencies
How does LUISA work?
161 June 2015
Allow rules + discrete allocation
AccessibilityNr of people
100 m
Land-use pattern
Outputs from LUISA
at pixel level
171 June 2015
AccessibilityNr of people
100 m
Land-use pattern
Indicators obtained through combination and/or
aggregation
}50+ indicators
- Land use- Resources- Productivity- Air quality- Ecosystems- Hydrology- Accessibility
18
� The expected land surface required to support future
societal and economic activities;
� Defined for the ‘active land use classes’ (urban, industry-
services, agriculture, forest);
� Determined within LUISA exogenously;
� The output of LUISA is very sensitive to the ‘demand’ definition.
Land demand
19
Population
projection
Nr.
households
Urban land
demand
Parameter:Average
household size
*
*
*
* Subject to scenario / policy option specification
Parameter:Urban
density
Other drivers of urban land (e.g. tourism)
Demand for urban land use
20
1. Continuous allocation of residents, given:
� Net regional population = (Pt1 – Pt0) + (0.1 * Pt0), given
population projections;
� Location suitability factors: Potential accessibility, proximity
to road, slope, land uses (based on spatial econometric
calibration);
� Housing supply -> penalizes/incites population changes in
case of shortage/surplus.
Land allocation
211 June 2015
LUISA Population potentialsRed: highestYellow: mediumGreen: lowest
22
2. Discrete allocation of land uses:
� Based on multinomial logistic regression – addressing
competition for land;
� The highest bidder takes land (i.e. the land use type with
the highest overall suitability level at each location).
� Overall suitability (for each land use in each location) is a
combination of bio-physical suitability, allow rules, transition
costs, neighborhood and land demand.
Land allocation
100 m
Outputs of LUISA
241 June 2015
Outputs of LUISA
Population Urban sprawl
Potential accessibility
25
� What is LUISA
� How LUISA works
� Baseline trajectory of future urbanization
� On-going and future work
Contents
A European baseline scenario
A baseline scenario…
� assumes the most likely socio-economic trends (often business-as-
usual approach) and the expected effect of established policies;
� serves as benchmark for comparison of policy alternatives, allowing
their ex-ante evaluation.
The “Energy-Climate Reference Scenario 2013” is used as BASELINE:
� Known EU level policies (Cohesion policy, biodiversity and habitat
protection, renewables directive…);
� Most likely future regional demands;
� Business as usual preferences.Dependence on several
upstream sector models
27
On aggregate… further losses of land use intensity
Results
28
1990-2010
2010-2050
But… large spectrum of behaviors among NUTS3 regions…
Results
29
30
31
32
LAND TAKE / YEAR LAND TAKE / CAPITA / YEAR BUILT-UP PER MN INHABITANTS
Focus on Large Urban Zones…
Population density - 2010
Population density - 2050
Expansion
2010 2050
Stagnation / de-growth
2010 2050
Concentration
2010 20502050
Absolute changes in population 2010-2050
39
Density profiles in Functional Urban Areas
40
RC= Vd x Conc x GA
Pollutant concentration maps (current & future) Pollutant removal capacity
Focus on environmental/quality of life indicators (e.g. Air Quality)
41
Urban population exposed to pollutant concentration exceeding the daily
limit value for more than 35 days in a year.
Focus on environmental/quality of life indicators (e.g. Air Quality)
42
� What is LUISA
� How LUISA works
� Baseline trajectory of future urbanization
� On-going and future work
Contents
� Urban efficiency indicators (land use, and energy/transport efficiency);
� Scenarios of sustainable urban development;
� Up-date of the reference Scenario (include new macro-assumptions);
� Pan-European coverage (2015-16 – gradual extension);
� Update of base year – 2012;
On-going and planned activities / improvements
� More economic rationale in LUISA:
� spatial allocation with net present value considerations
� modeling of services and employment distribution
� economic-demographic feedbacks (population following jobs)
� Validation activities and cross model comparison exercises.
On-going and planned activities / improvements
45
� Lavalle C, et al. 2011. A High Resolution Land use/cover Modelling Framework for
Europe: introducing the EU-ClueScanner100 model. In Computational Science and
Its Applications - ICCSA 2011, Part I, Lecture Notes in Computer Science vol. 6782,
edited by B. Murgante et al. Apduhan. Berlin: Springer-Verlag.
� Batista e Silva F, et al. 2014. Estimating demand for industrial and commercial
land use given economic forecasts. PLOS ONE 9 (3):e91991.
� Jacobs-Crisioni C, et al. 2014. Accessibility and territorial cohesion in a case of
transport infrastructure improvements with endogenous population
distributions. Forthcoming.
� Lavalle C, et al. et al. Land use and scenario modelling for Integrated
Sustainability Assessment. Forthcoming.
� More at: http://ec.europa.eu/jrc/en/luisa/
Some references
Thank you