Assessing the thermal performance of
green infrastructure on urban microclimate
Carlos Bartesaghi Koc
PhD Candidate
March 2015 – 2018
Supervisors:
Dr. Paul Osmond
Prof. Alan Peters
CRCLCL Node of Excellence in HPA
UNSW
08-06-2016
Research Questions
•
What is the thermal performance of different green infrastructure typologies?
•
What is most effective composition, amount and arrangement of GI required to
provide a maximum thermal cooling?
URBAN MICROCLIMATE
GREEN INFRASTRUCTURE
(Trees, parks, green roofs, vertical
greenery systems, water bodies)
(Surface- & Canopy Layer- Urban heat
island – SUHI, CLUHI)
Airborne
Remote
Sensing
6/3/2016
Image: Michael Van Valkenburgh Associates
Method to
map and
assess the
thermal effects
of GI
2
Source: Dr. Matthias Irger (2014)
Research Objectives
O1
O2
• Propose a new green infrastructure typology to support urban microclimate studies.
• Propose a methodological framework combining empirical and predictive analysis to
evaluate the thermal performance of GI typologies in a more comprehensive and precise way.
O3
• Propose a standardised GIS-based workflow that makes use of readily accessible data and
can be easily replicable.
O4
O5
• Use Sydney and Melbourne as case studies to apply the GIS-based methodology.
• Propose a list of evidence-based guidelines and recommendations for practitioners, industry
and local governments.
NSW Public Works – Sydney Green
Grid
6/3/2016
Image: http://www.greenroofs.com
3
Research Method
- Hyper-/multi-spectral
- Cadastral
- LiDAR
A. LCZ classification
6/3/2016
Evaluation of functional, structural and configurational attributes using a combination
of airborne remote sensing, empirical observations and predictive modelling.
- Hyper-/multi-spectral
- LiDAR
- Aerial
B. GIT classification
- Ground-based monitoring
- Products of steps A & B
- Thermal infrared (TIR)
C. Statistical analysis
4
Research Challenges
Winter data > Dr. Matthias Irger & CSIRO
Summer data > Parramatta City Council (LPI)
Summer data > City of Port Phillip &
Dr. A. Coutts
• Data collection > two case studies: Sydney and Melbourne > unmatched datasets
• Calculation of indicators > NDVI, LAI, Evapotranspiration model, Landscape metrics (FRAGSTATS)
• Emissivity corrections to calculate more precise land surface temperatures (TIR images)
• Big data processing and analysis: Day-night / Winter-Summer / 3 different locations
6/3/2016
• Formulation of a predictive model > statistical analysis
5
Outcomes / Innovation / Contributions
6/3/2016
•
A standardised classification of GI to
facilitate the reporting of thermal analyses,
and inter-site & inter-typology comparison.
•
Formulation of a GIS-based methodological
framework to map GI conditions, prioritise
greening interventions and deliver more
sustainable neighbourhoods with greater
confidence.
•
Use of very high resolution airborne remote
sensing imagery for a more precise and
accurate analysis at local and micro scales.
•
Estimation of evapotranspiration in urban
areas and heterogeneous contexts.
•
Formulation of guidelines as a
communication and visualisation tool for
designers and policy-makers.
6
Image: EEA (2013). Building a green infrastructure for Europe.
Thank you for
your attention
6/3/2016
Acknowledgments: This research is conducted at the Faculty of Built Environment,
University of New South Wales (UNSW-Australia) and the Node of Excellence –
Cooperative Research Centre for Low Carbon Living (CRC-LCL). This research is
possible thanks to the financial support of the Graduate Research School –UNSW
(University International Postgraduate Award - UIPA) and the CRC for Low Carbon
Living (Top-up scholarship). The data used in this research has been kindly provided 7
by Dr. Matthias Irger, CSIRO, Parramatta City Council (Dr. Paul Hackney) and City of
Port Phillip - Melbourne.