Integrated urban monitoring framework     A conceptual framework for land dynamics monitoring     Nicolas Lachance-Bernard...
Content •    Introduction and context •    Integrated urban monitoring framework •    Indicator illustration •    Data: Ge...
Introduction •     Urbanized area rapid expansion (urban sprawl)         – Transportation systems and land uses interdepen...
Context •     Problems         – Fact           Urban activities and fluxes are influenced by urban development         – ...
Transportation and Land Use Issues                                Density          Centrality                             ...
Integrated Urban Monitoring Framework                                                     Top-down                        ...
Stakeholder Tier •     Concepts         – Planning: questions and needs         – Decision process oriented            Ope...
Knowledge Tier •     Concepts         –   Indicators, Indicator systems         –   Trends, outliers, flux, hotspots      ...
Information Tier •     Concepts         – Real information           Update frequency         – Historical information    ...
Data Tier •     Concepts         – Raw data                  •   Privately produced                      (government, agen...
Thematic / Data / Indicator •     Density         – 2D: Population, Activities, Public Services     (number * weight)     ...
Plan vs. Statistics        Ratios            Hotspots              Outliers                                               ...
Plan vs. Statistics        Ratios            Hotspots              Outliers                                               ...
KNOWLEDGE                                               K-mean clustering on                                        econom...
Financial           Legal and accounting                      INFORMATION                                                 ...
Available Public Data (for Research)                             Data           Geneva (CH)                          Coimb...
Conclusion •     Urban monitoring for land dynamics         – Accessibility, Diversity, Centrality and Density            ...
References [1] Handy S. (2005), Smart Growth and the Transportation-Land Use Connection: What Does the Research Tell Us? I...
Many thanks for your attention! The authors are grateful to COST, European Cooperation in Science and Technology (www.cost...
Upcoming SlideShare
Loading in...5
×

Integrated urban monitoring framework

819

Published on

A conceptual framework for land dynamics monitoring.

Published in: Technology, Real Estate
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
819
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
0
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Integrated urban monitoring framework

  1. 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, PortugalNLB-FG-APA-NNP / p.1 Integrated urban monitoring framework for land dynamics
  2. 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, 2010NLB-FG-APA-NNP / p.2 Integrated urban monitoring framework for land dynamics
  3. 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]NLB-FG-APA-NNP / p.3 Integrated urban monitoring framework for land dynamics
  4. 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 dynamicsNLB-FG-APA-NNP / p.4 Integrated urban monitoring framework for land dynamics
  5. 5. Transportation and Land Use Issues Density Centrality Accessibility DiversityNLB-FG-APA-NNP / p.5 Integrated urban monitoring framework for land dynamics
  6. 6. Integrated Urban Monitoring Framework Top-down Bottom-upNLB-FG-APA-NNP / p.6 Integrated urban monitoring framework for land dynamics
  7. 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 reportNLB-FG-APA-NNP / p.7 Integrated urban monitoring framework for land dynamics
  8. 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 – ClusteringNLB-FG-APA-NNP / p.8 Integrated urban monitoring framework for land dynamics
  9. 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, SOLAPNLB-FG-APA-NNP / p.9 Integrated urban monitoring framework for land dynamics
  10. 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)NLB-FG-APA-NNP / p.10 Integrated urban monitoring framework for land dynamics
  11. 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)NLB-FG-APA-NNP / p.11 Integrated urban monitoring framework for land dynamics
  12. 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 ServicesNLB-FG-APA-NNP / p.12 Integrated urban monitoring framework for land dynamics
  13. 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 ServicesNLB-FG-APA-NNP / p.13 Integrated urban monitoring framework for land dynamics
  14. 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 2011NLB-FG-APA-NNP [12] Integrated urban monitoring framework for land dynamics
  15. 15. Financial Legal and accounting INFORMATION Economical activities (NetKDE, Geneva 2009) Specialized constructions activities Other personal RestorationNLB-FG-APA-NNP / p.15Source: Gasser 2011 [12] Integrated urban monitoring framework for land dynamics
  16. 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, StopsNLB-FG-APA-NNP / p.16 Integrated urban monitoring framework for land dynamics
  17. 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 …NLB-FG-APA-NNP / p.17 Integrated urban monitoring framework for land dynamics
  18. 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.NLB-FG-APA-NNP / p.18 Integrated urban monitoring framework for land dynamics
  19. 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.NLB-FG-APA-NNP / p.19 Integrated urban monitoring framework for land dynamics

×