A conceptual framework for land dynamics monitoring.

1. Integrated urban monitoring framework
A conceptual framework for land dynamics monitoring
Nicolas Lachance-Bernard1, Prof. François Golay1,
Prof. António P. Antunes2, Nuno N. Pinto2
1 Geographic Information Systems Laboratory, Ecole polytechnique fédérale de Lausanne
2 Department of Civil Engineering, University of Coimbra
7th VCT Virtual Cities and Territories Conference
October 11th – 13th 2011, Lisbon, Portugal
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Integrated urban monitoring framework for land dynamics

2. Content
• Introduction and context
• Integrated urban monitoring framework
• Indicator illustration
• Data: Geneva (CH) vs. Coimbra (PT)
• Further research
Cover picture: Photograph NLB, City of Istanbul, 2010
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Integrated urban monitoring framework for land dynamics

3. Introduction
• Urbanized area rapid expansion (urban sprawl)
– Transportation systems and land uses interdependency [1]
Looking for stronger land market management: densification
– Legal tools
Zonings, urban belts, development areas, land taxes... Efficient?
– Planning
Current policies concentrate on responding to land market [2]
• Monitoring of land development and GIS [3]
– EEA with CORINE land cover and MOLAND land use (scale) [4]
– COST Act. C9 “participative evaluation and decision framework” [5]
– Participative SMURF global and aggregated indicators [6,7]
– Land change science (LCS) - DPSIR indicator framework [8,9,10,11]
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Integrated urban monitoring framework for land dynamics

4. Context
• Problems
– Fact
Urban activities and fluxes are influenced by urban development
– Principal need
Developing method to compare city evolution in relation to
(master) plans
– Goal
“Spatio-temporal” monitoring of urban dynamics
• Challenges
1. To include monitoring process within decision making process
2. To use very large datasets and diverse/complementary models
3. To challenge conceptual master plan with actual geoinformation
4. To determine monitoring indicators for urban land dynamics
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Integrated urban monitoring framework for land dynamics

5. Transportation and Land Use Issues
Density
Centrality Accessibility
Diversity
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Integrated urban monitoring framework for land dynamics

6. Integrated Urban Monitoring Framework
Top-down
Bottom-up
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Integrated urban monitoring framework for land dynamics

7. Stakeholder Tier
• Concepts
– Planning: questions and needs
– Decision process oriented
Operational (local scale, low risk)
Tactical (city scale, medium risk)
Strategical (regional scale, high risk)
• Computer tools
– Dashboard
– Geo-atlas
– Geovisualization
– Executive report
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Integrated urban monitoring framework for land dynamics

8. Knowledge Tier
• Concepts
– Indicators, Indicator systems
– Trends, outliers, flux, hotspots
– Spatio-temporal, scales (multi)
– Comparison / Correlation
• Computer tools
– Aggregation and disaggregation
– Fuzzy-map comparison
– Adapted landscape metrics
– Clustering
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Integrated urban monitoring framework for land dynamics

9. Information Tier
• Concepts
– Real information
Update frequency
– Historical information
“Composted” vs. aggregated
– Projected information
Short and long terms
• Computer tools
– Time-fixed i.e. states
GWR, KDE, NetKDE, MCA, Localization, Multimodal accessibility
– Itterative i.e. models
UrbanSim, Cellular Automata, Multi-scale Multi-agent model
– Knowledge oriented
Stream cubes, SOLAP
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Integrated urban monitoring framework for land dynamics

10. Data Tier
• Concepts
– Raw data
• Privately produced
(government, agencies, companies)
• Volunteered geographic information
(public, NGO)
– Availability and liability
– Resolution and frequency
• Computer tools
– Spatial Data Infrastructure (SDI)
– Geospatial Metadata Management (ISO 19115/19139, ISO/TC211)
– Spatial Extraction-Transformation-Loading tool (ETL)
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Integrated urban monitoring framework for land dynamics

11. Thematic / Data / Indicator
• Density
– 2D: Population, Activities, Public Services (number * weight)
– 3D: Buildings (volume * footprint, level * surface)
• Diversity
– Mix-uses building (%, ratio, surface/use)
– Non-residential, Industrial, Green area/plot
• Centrality
– Network segment straightness, betweeness, closeness
(scale value)
• Accessibility
– Residential-work, Residential-school
– Job-services, Job-activities (travel times)
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Integrated urban monitoring framework for land dynamics

12. Plan vs. Statistics Ratios Hotspots Outliers
KNOW
Plan vs. Models
Models vs. Statistics Flux Potentials Trends
Landscape metrics Fuzzy-map Clustering
Diversity Density Centrality Accessibility
INFO
Models
States Diversity Density Centrality Accessibility
Street network Buildings Population
Pedestrian network Building use(s) Jobs/Students
DATA
Bike network Land uses Activities
Public network Origin-Destination Services
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Integrated urban monitoring framework for land dynamics

13. Plan vs. Statistics Ratios Hotspots Outliers
KNOW
Plan vs. Models
Models vs. Statistics Flux Potentials Trends
Landscape metrics Fuzzy-map Clustering
Diversity Density Centrality Accessibility
INFO
Models
States Diversity Density Centrality Accessibility
Street network Buildings Population
Pedestrian network Building use(s) Jobs/Students
DATA
Bike network Land uses Activities
Public network Origin-Destination Services
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Integrated urban monitoring framework for land dynamics

14. KNOWLEDGE
K-mean clustering on
economical activity densities
(NetKDE, Geneva 2009)
Auto
1) La Treille’s wall separation
2) Les Tranchés area main
residential area of Geneva’s centre
3) St-Gervaix and Genève-Cité
area main economic centre
/ p.14
Source: Gasser 2011
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15. Financial Legal and accounting INFORMATION
Economical activities
(NetKDE, Geneva 2009)
Specialized constructions activities
Other personal Restoration
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Source: Gasser 2011 [12] Integrated urban monitoring framework for land dynamics

16. Available Public Data (for Research)
Data Geneva (CH) Coimbra (PT)
Population 100m2 grid (until 2010) Census blocks
Jobs/Students - Freguesia (Boroughs)
Origin-Destination - 1995, 2002 (Car)
Activities Address points, 100m2 (Coming…)
Services Buildings Buildings
Buildings 3D, Footprint, Height Footprint,
Average height/census block
Building-uses Building, No level info. Census block
Land-uses Parcel, % of cat. (zones)
Street network 1:1000 1:1000
Bike network 1:1000, Slope, Park, -
Opposed traffic
Pedestrian network 1:1000, Slope, Park (Possible…)
Public transit network Tram, Stops, (No Timetable) Bus, Timetable, Stops
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Integrated urban monitoring framework for land dynamics

17. Conclusion
• Urban monitoring for land dynamics
– Accessibility, Diversity, Centrality and Density
(One perspective about urban land dynamics)
– What about Construction, Energy Consumption/Production, …?
(General integrated monitoring framework)
• Further work
– The translation of master plan for comparison with
actual knowledge, information and data.
– The framework implementation for Economist, Engineering, Urbanism,
Architecture firms/research centres.
– … and much more …
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Integrated urban monitoring framework for land dynamics

18. References
[1] Handy S. (2005), Smart Growth and the Transportation-Land Use Connection: What Does the Research Tell Us?
International Regional Science Review, 28:2, pp.146-167
[2] Knaap G. (2001), Land Market Monitoring for Smart Urban Growth. Cambridge, MA, Lincoln Institute of Land Policy,
ISBN 1-55844-145-X, 392 pages
[3] Nedović-Budić Z., Yilmaz T. and Knaap G. (2005), ArcIMS-Based Land Development Monitoring: Prototype for
Harford County, Maryland. ESRI User Conference Proceedings, 32 pages
[4] European Environmental Agency (2006), Urban Sprawl in Europe, the Ignored Challenge. EEA Report 10/2006,
Copenhagen, Denmark.
[5] Nembrini A. et al. (2006), GIS and participatory diagnosis in urban planning: a case study in Geneva. In: GIS for
sustainable development, Boca Raton (FL), Taylor & Francis, pp.451-465
[6] Rapetti A., Soutter M. and Musy A. (2006), Introducing SMURF: a software system for monitoring urban
functionalities. Computers, Environment and Urban Systems, 30, pp.686-707
[7] Rapetti A., Desthieux G. (2006), A relational indicatorset model for urban land-use planning and management:
Methodological approach and application in two case studies. Landscape and Urban Planning, 77:1-2, pp.196-215
[8] Turner B. L., Lambin E. F. and Reenberg A. (2007), The emergence of land change science for global
environmental change and sustainability. Proceedings of the National Academy of Sciences of the United States of
America, 104:52, pp.20666-20671
[9] Rindfuss R. R. et al. (2004), Developing a science of land change: Challenges and methodological issues.
Proceedings of the National Academy of Sciences of the United States of America, 101:39, pp.13976-13981
[10] Nuissl H. et al. (2009), Environmental impact assessment of urban land use transitions – A context-sensitive
approach. Land Use Policy, 26:2, pp.414-424
[11] Scipioni A. et al. (2009), The dashboard of sustainability to measure the local urban sustainable development:
The case study of Padua municipality. Ecological Indicators, 9:2, pp.364-380
[12] Gasser L. (2011), Integration of Urban Structures in Point Process Analysis, Master thesis in
Environmental Engineering, Ecole polytechnique fédérale de Lausanne.
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Integrated urban monitoring framework for land dynamics

19. Many thanks for your attention!
The authors are grateful to COST, European Cooperation in Science and
Technology (www.cost.esf.org) and the COST Action TU0602 “Land
management for urban dynamics” management committee about covering the
costs of two short term scientific missions (STSM) by Nicolas Lachance-Bernard.
The first (COST-STSM-TU0602-04953) was completed at the University of
Coimbra (PT) in 2009. The second (ECOST-STSM-TU0602-010910-002716) was
completed at the University of Strathclyde (UK) in 2010.
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Integrated urban monitoring framework for land dynamics