Applied Use of Geodesign to Enhance Urban Cl imate Change Resi l ience Decision Making Corey Pembleton, M.Sc. CandidateFaculty of Environment

Designing with Nature

"In the quest for survival, success and fulfillment the ecological view offers an invaluable insight. It shows the way for the man who would be the enzyme of the biosphere-its steward, enhancing the creative fit of man-environment realizing man's design with nature"

Ian McHargfrom Design with Nature, 1969

Summary

• Section 1: Introduction• Problem Overview• Context

• Section 2: Geodesign and Resilience• Automated Urban Structure Type (UST) Classification• Geodesign, Climate Change Resilience & Decision Making• UST as key Geodesign input for resilience planning

Problem Overview

Coastal cities in the next several decades will be faced with climate-change related challenges such as flooding and severe weather events largely influenced by increasing sea-level rises (Batty, 2011);

Under various flooding scenarios, Vancouver expects to see up to 5,000 households displaced and cost evaluations in the billions of dollars.

As such, to move towards a more holistic and comprehensive understanding of these relationships and building cities accordingly is necessary

What are the benefi ts of a Geodesign approach for complex human-environmental interact ions?

Faced with the need to address increasingly complex issues simultaneously, decision-makers require a comprehensive and holistic approach to landuse planning. It should adequately incorporate spatial analysis and urban design best practices

Should be inclusive of:• Enhanced geospatial analysis from combined GIS and

remote-sensed data • Inclusion of social indicators such as those found in Social

Vulnerability Assessments

Enhancing the sociotechnical toolset of geodesign in Southlands Neighbourhood, VancouverAutomated urban structure type (UST) classifications and landcover classifications provide decision makers with a cost-effective and comprehensive method for monitoring changes and human-environment interactions.

Automated Urban Structure Type (UST) and LandcoverClassification using open data

• USTs have been identified in recent studies as an effective and holistic approach to understanding the relationship between the built and natural environments

• Decision-tree parameters include: building height mean, inverted FAR, rooftype, landscape shape index, urban density mean, building footprint mean (Volternsen et al., 2014)

UST Workflow

Prel iminary Results: Bui lding a Class Typology, nDSM

Early Classification for Sample Study: Roof type Classification

Normalized Digital Surface Model,Building Extractions

Geodesign as a decision-making tool• “geodesign tools were able to integrate the

engagement of stakeholders and assessment of measures. The experiment showed that decision-making on adaptation to climate change can benefit from the use of geodesign tools as long as the tool is carefully matched to the rationality that applies to the adaptation issue”

Eikelboom, T., & Janssen, R. (2015). Collaborative use of geodesign tools to support decision-making on adaptation to climate change. Mitigation and Adaptation Strategies for Global Change, (Ivm). doi:10.1007/s11027-015-9633-4

Anticipated Results• Develop a replicable tool for creating a UST using only

open-source data and mixed types including LiDAR, RS and GIS data types

• Enhance the understanding of the relationship between urban morphology and natural hazards in coastal areas

• Implement a Geodesign tool / software as a means of bridging the gap in understanding between geospatial analysis and decision-making

• Assess the feasibility of Geodesign methods for use in multi-source geospatial and geostatistical analysis

References Albers, R. a. W., Blocken, B., & Bosch, P. R. (2014). Overview of challenges and achievements in the Climate Proof Cities program. Building and Environment

Batty, M. (2011). Modeling and simulation in geographic information science: Integrated models and grand challenges. In Procedia -Social and Behavioral Sciences (Vol. 21, pp. 10–17).

Carter, J. G., Cavan, G., Connelly, A., Guy, S., Handley, J., & Kazmierczak, A. (2014). Climate change and the city: Building capacity for urban adaptation. Progress in Planning, 95, 1–66.

Eikelboom, T., & Janssen, R. (2015a). Collaborative use of geodesign tools to support decision-making on adaptation to climate change. Mitigation and Adaptation Strategies for Global Change, (Ivm).

Eikelboom, T., & Janssen, R. (2015b). Comparison of Geodesign Tools to Communicate Stakeholder Values. Group Decision and Negotiation, 24(6), 1065–1087.

Eikelboom, T., Janssen, R., & Stewart, T. J. (2015). A spatial optimization algorithm for geodesign. Landscape and Urban Planning, 144, 10–21.

Esri (2010) Changing Geography by Design: Selected Readings in Geodesign. Esri Press.

Heiden, U., Heldens, W., Roessner, S., Segl, K., Esch, T., & Mueller, A. (2012). Urban structure type characterization using hyperspectral remote sensing and height information. Landscape and Urban Planning, 105(4), 361–375.

McHarg, I. (1969). Design with nature. Garden City, N.Y.: Published for the American Museum of Natural History [by] the Natural History Press.

Voltersen, M., Berger, C., Hese, S., & Schmullius, C. (2014). Object-based Land Cover Mapping and Comprehensive Feature Calculation for an Automated Derivation of Urban Structure Types on Block Level. Remote Sensing of Environment, 154, 192–201. doi:10.1016/j.rse.2014.08.024