Integrated land dynamics monitoring framework

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Nicolas Lachance-Bernard
Geographic Information Systems Laboratory, Ecole polytechnique fédérale de Lausanne, Switzerland

European Regional Science Association, 24th Summer School Modelling Cities and Urban Dynamics, July 10th 2011,
Université du Luxembourg

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Integrated land dynamics monitoring framework

  1. 1. Integrated land dynamics monitoring framework Nicolas Lachance-Bernard Geographic Information Systems Laboratory, Ecole polytechnique fédérale de Lausanne, Switzerland European Regional Science Association, 24th Summer School Modelling Cities and Urban Dynamics, July 10th 2011, Université du LuxembourgNLB / 10.07.11 / p.1 Integrated Land Dynamics Monitoring Framework
  2. 2. Plan • Introduction • Land dynamics monitoring framework • Network based kernel density estimator • Case studiesNLB / 10.07.11 / p.2 Integrated Land Dynamics Monitoring Framework
  3. 3. Planning Practice • Public policy – Concentrates on responding to land market demand (Knaap 2001) – Stronger spatio-temporal market management (supply & demand… specially in Switzerland) • Challenges – Housing, commercial and activities densification – Adaptation of planning tools: zonings, taxes, … – Sparse data • Time - incomplete, not updated, lack of historical depth • Space – incomplete, insufficient resolution or scale – Maps making not adapted to monitoringNLB / 10.07.11 / p.3 Integrated Land Dynamics Monitoring Framework
  4. 4. Planning versus Change • Urban planning – Geographic information systems (GIS) since 1990s (Nedović-Budić et al 2005) – Interdependency of transportation systems and land uses (Handy 2005) – CORINE land cover, MOLAND land use, EEA Cellular Automata, CityCoop project, SMURF, (and many others)… • Land change science (LCS) – Data availability, aggregation process, validation, sensitivity (Rindfuss et al. 2004) – Driver, Pressure, State, Impact and Response framework (DPSIR) (Nuissl et al. 2009)NLB / 10.07.11 / p.4 Integrated Land Dynamics Monitoring Framework
  5. 5. R&D opportunities • Land monitoring systems • Land covers (i.e. regional sprawl) • Land uses (i.e. urban segregation, urban densification) • Land markets (i.e. risk, trends) • Development (i.e. permit emission, value capture, micro-credit) – General indicators (comparison region to region) – Specific indicators (following city objectives and goals)NLB / 10.07.11 / p.5 Integrated Land Dynamics Monitoring Framework
  6. 6. This paper… • Urban monitoring framework – Developed for integrated land dynamics (Transportation & Land uses) – Looking for spatio-temporal trends, hotspots, axes, flux, … (What? Where? Who? When? How? …) – Illustrated by innovative indicators (NetKDE, MCA, Jensen, Multimodal accessibility, …) • Proof-of-concept: i.e. Density indicator (NetKDE) – Ljubljana: biking around the city (Where people behave?) – Barcelona: playing with scale and comparing model (How scale change vision?) – Baghdad: playing with time, classification and complexity (Which time evolution and about who?)NLB / 10.07.11 / p.6 Integrated Land Dynamics Monitoring Framework
  7. 7. Plan • Introduction • Land dynamics monitoring framework • Network based kernel density estimator • Case studiesNLB / 10.07.11 / p.7 Integrated Land Dynamics Monitoring Framework
  8. 8. Monitoring FrameworkNLB / 10.07.11 / p.8 Integrated Land Dynamics Monitoring Framework
  9. 9. Stakeholder Tier • Concepts – Top-Down approach – Planning questions / needs – Decision process oriented – 3 levels (scale vs risk) • Operational (local, low) • Tactical (city, medium) • Strategical (regional, high) • Applications – Dashboard, visualization system, geo-atlas, drill-down • Current project – Land uses and networks monitoring (Coimbra vs. Geneva), 20 years, master plan vs. actual states, 10 indicators vs. dataNLB / 10.07.11 / p.9 Integrated Land Dynamics Monitoring Framework
  10. 10. Knowledge Tier • Concepts – Spatio-temporal indicators – Indicator repertories, index, systems – Comparison of model results – Multitemporal, multiscales • Applications – Aggregation and disaggregation – Fuzzy-map comparison – Adapted landscape metrics • Current projects – Temporal and aggregates analysis (Baghdad) - Casualties – Comparison of models (Ljubljana) – Cycling infrastructuresNLB / 10.07.11 / p.10 Integrated Land Dynamics Monitoring Framework
  11. 11. Information Tier • Concepts – Projected - short & long term – Actual - frequency – Historical - “composted” / aggregated • Applications (models) – Time-Fixed • GWR, KDE, NetKDE, MCA, Localization, Multimodal accessibility – Scenarios • UrbanSim, Cellular Automata, Multi-scale Multi-agent model • Current projects – NetKDE / KDE / MCA : Barcelona, Geneva, Bologna, Glasgow (economics activities), Ljubljana (cycling behavior) – Accessibility (Geneva), CA (Lausanne)NLB / 10.07.11 / p.11 Integrated Land Dynamics Monitoring Framework
  12. 12. Data Tier • Concepts – Bottom-up approach – Raw data • Public and private (government, agencies, companies) • Volunteered geographic information – Availability, liability, resolution, frequency • Applications – Spatial data infrastructure (SDI), Input translator, Topological checker, Metadata Management • Current projects – SDI for EPFL (15TB of data Swisstopo, OFS, …) – VGI in Ljubljana (cycling)NLB / 10.07.11 / p.12 Integrated Land Dynamics Monitoring Framework
  13. 13. Plan • Introduction • Land dynamics monitoring framework • Network based kernel density estimator • Case studiesNLB / 10.07.11 / p.13 Integrated Land Dynamics Monitoring Framework
  14. 14. KDE vs. NetKDE • Kernel Density Estimator (KDE*) – Operates in euclidean space – Weights events by their radial distances from grid centroid • Network Based Kernel Density Estimator (NetKDE*) – Operates in a network constrained space – Weights events by the distance from grid centroid measured along this network • Objectives – Handling large datasets in opensource framework/applications *NetKDE and KDE (2009-2011) by Timothée Produit, Nicolas Lachance-Bernard, Loic Gasser, Dr. Stephane Joost, Prof. François Golay, Prof. Sergio Porta, Emanuele StranoNLB / 10.07.11 / p.14 Integrated Land Dynamics Monitoring Framework
  15. 15. KDE vs. NetKDE KDE NetKDE Source: Produit 2009NLB / 10.07.11 / p.15 Integrated Land Dynamics Monitoring Framework
  16. 16. KDE vs. NetKDE KDE NetKDE Source: Produit and Lachance-Bernard, 2010NLB / 10.07.11 / p.16 Integrated Land Dynamics Monitoring Framework
  17. 17. Plan • Introduction • Land dynamics monitoring framework • Network based kernel density estimator • Case studiesNLB / 10.07.11 / p.17 Integrated Land Dynamics Monitoring Framework
  18. 18. Data Tier: Ljubljana and VGI • Low resolution KDE 100m  425km2 13,630 segments, 42,342 gridpoints, 442,260 GPS points KDE bandwidths [200m, 2500m] 24 X 100m steps (2-3h) • High resolution NetKDE/KDE 20m  20km2 8,114 segments, 314,250 gridpoints, 423,748 GPS points NetKDE bandwidths 60m (17h), 100m (19h), 200m (24h), 400m (27h) KDE bandwidths [40m, 100m] 7 X 10m steps [200m, 1000m] 9 X 100m steps (total 18h)NLB / 10.07.11 / p.18 Integrated Land Dynamics Monitoring Framework
  19. 19. NetKDE (Left) KDE (Right) results 20m grid (Bandwidths: a-60m; b-100m; c-200m; d-400m) Data Tier: Ljubljana and VGINLB / 10.07.11 / p.19 Integrated Land Dynamics Monitoring Framework
  20. 20. Data Tier: Ljubljana and VGINetKDE (Left)KDE (Right)Results 20m grid(Bandwidths: 400m)*Deciles distributionNLB / 10.07.11 / p.20 Integrated Land Dynamics Monitoring Framework
  21. 21. KDE results 20m grid Bandwidths: A)60m B)100m C)200m D)400m *Deciles distributionNLB / 10.07.11 / p.21 Integrated Land Dynamics Monitoring Framework
  22. 22. NetKDE results 20m grid Bandwidths: A)60m B)100m C)200m D)400m *Deciles distributionNLB / 10.07.11 / p.22 Integrated Land Dynamics Monitoring Framework
  23. 23. Information Tier: Barcelona KDE vs. NetKDE Data 2002 Treatments (Agencia de Ecologia Urbana) • Multiple grids • Retail and service activities 10m, 20m, 50m, 100m, 200m 166,311 entities • Multiple density models • Street network NetKDE, KDE 11,222 segments • Multiple bandwidths NetKDE [100m, 1000m] KDE [20m, 6000m] • Duration: +500 hours with 9 computersNLB / 10.07.11 / p.23 Integrated Land Dynamics Monitoring Framework
  24. 24. Barcelona Activities KDE/NetKDE bandwidth variations (200m grid) KDE 400m KDE 600m KDE 800m KDE 1000m NetKDE 400m NetKDE 600m NetKDE 800m NetKDE 1000m Low density High density Not calculatedNLB / 10.07.11 / p.24 Integrated Land Dynamics Monitoring Framework
  25. 25. Barcelona Activities KDE/NetKDE grid scale variations H KDE grid: 200m, band.: 500m NetKDE grid: 200m, band.: 500m L KDE grid: 50m, band.: 500m NetKDE grid: 50m, band.: 500mNLB / 10.07.11 / p.25 Integrated Land Dynamics Monitoring Framework
  26. 26. Barcelona Activities KDE/NetKDE high resolution grid variations H KDE grid: 10m, band.: 500m (ZOOM) NetKDE grid: 10m, band.: 500m (ZOOM) L KDE grid: 10m, band.: 500m NetKDE grid: 10m, band.: 500mNLB / 10.07.11 / p.26 Integrated Land Dynamics Monitoring Framework
  27. 27. Knowledge Tier: Spatio-temporal evolution Baghdad • Events – Data journalism war death casualties Baghdad 2004-2009 Coalition Iraqi Civilians Insurgents Forces Forces Attack 86 1,167 1,627 3,775 Direct Fire 482 4,270 4,766 6,807 Indirect Fire 192 284 2,087 1,040 IED Explosion 2,107 5,990 20,228 3,455 Murder 9 2,169 32,563 73 Total (93,157) 2,876 13,880 61,251 15,150 • Network Open Street Map (OSM) 66,648 segments • Grid 200m resolution 22,644 gridpoints / 50m resolution 362,304 gridpointsNLB / 10.07.11 / p.27 Integrated Land Dynamics Monitoring Framework
  28. 28. Distribution of religious groups in Baghdad Source: Loic Gasser, 2011NLB / 10.07.11 / p.28 Integrated Land Dynamics Monitoring Framework
  29. 29. Spatio-temporal KDE-NetKDE* • Proposed by Demsar and Virrantaus (2010) based on space-time cube by Hägerstrand • 3D KDE function 3D Epanechnikov kernel function * Developped by Loic Gasser, Timothée Produit and Nicolas Lachance-BernardNLB / 10.07.11 / p.29 Integrated Land Dynamics Monitoring Framework
  30. 30. Baghdad IED explosions KDE January 2004 - December 2009 • 2,652 events - 1,030 km2 - 76 steps, 1500m KDE • 1 day equivalent to 10 meters Source: Loic Gasser, 2011NLB / 10.07.11 / p.30 Integrated Land Dynamics Monitoring Framework
  31. 31. Discussion • Research under rapid evolution… – 3rd-4th algorithm: Calculation optimization 90-95% – Professional uses: Architects, Planners, Criminologs, Biologists • Actual projects… – Spatio-temporal and statistical analysis – Fuzzy-map comparison (time, model, resolution, bandwidth) – Testing Adapted Landscape metrics – Testing HPC for calculation and subsequent analysisNLB / 10.07.11 / p.31 Integrated Land Dynamics Monitoring Framework

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