New Metrics for Spatial and Temporal 3D Urban Form Sustainability Assessment Using Time Series Lidar Point Clouds and Advanced GIS Techniques

Monitoring sustainability of urban form as a 3D phenomenon over time is crucial in the era of smart cities for better planning of the future, and for such a monitoring system, appropriate tools, metrics, methodologies and time series 3D data are required. While accurate time series 3D data are becoming available, a lack of 3D sustainable urban form (3D SUF) metrics, appropriate methodologies and technical problems of processing time series 3D data has resulted in few studies on the assessment of 3D SUF over time. In this chapter, we review volumetric building metrics currently under development and demonstrate the technical problems associated with their validation based on time series airborne lidar data. We propose new metrics for application in spatial and temporal 3D SUF assessment. We also suggest a new approach in processing time series airborne lidar to detect three-dimensional changes of urban form. Using this approach and the developed metrics, we detected a decreased volume of vegetation and new areas prepared for the construction of taller buildings. These 3D changes and the proposed metrics can be used to numerically measure and compare urban areas in terms of trends against or in favor of sustainability goals for caring for the environment.

[1]  Dengsheng Lu,et al.  Land‐cover binary change detection methods for use in the moist tropical region of the Amazon: a comparative study , 2005 .

[2]  Qun Gao,et al.  Quantifying Circular Urban Expansion Patterns of Compact Chinese Cities: The Case of Yangtze River Delta, China , 2015 .

[3]  Norzailawati Mohd Noor,et al.  Urban morphology analysis by remote sensing and gis technique, case study: Georgetown, Penang , 2014 .

[4]  Biswajeet Pradhan,et al.  Land use change modeling and the effect of compact city paradigms: integration of GIS-based cellular automata and weights-of-evidence techniques , 2018, Environmental Earth Sciences.

[5]  Biswajeet Pradhan,et al.  City Compactness: Assessing the Influence of the Growth of Residential Land Use , 2018 .

[6]  Anders Gullberg,et al.  Images of the Future City: Time and Space For Sustainable Development , 2011 .

[7]  Biswajeet Pradhan,et al.  Sustainable Brownfields Land Use Change Modeling Using GIS-based Weights-of-Evidence Approach , 2016 .

[8]  Eric J. Miller,et al.  Urban Form, Energy and the Environment: A Review of Issues, Evidence and Policy , 1996 .

[9]  Luca Salvati,et al.  Towards sustainable growth? A multi-criteria assessment of (changing) urban forms , 2017 .

[10]  Susan L Handy,et al.  METHODOLOGIES FOR EXPLORING THE LINK BETWEEN URBAN FORM AND TRAVEL BEHAVIOR , 1996 .

[11]  Elena G. Irwin,et al.  Towards a comprehensive framework for modeling urban spatial dynamics , 2009, Landscape Ecology.

[12]  Sara Shirowzhan,et al.  Building Classification from Lidar Data for Spatio-temporal Assessment of 3D Urban Developments , 2017 .

[13]  Kevin J. Gaston,et al.  The impact of urbanisation on nature dose and the implications for human health , 2018, Landscape and Urban Planning.

[14]  Long Zhou,et al.  Urban Form, Growth, and Accessibility in Space and Time: Anatomy of Land Use at the Parcel-Level in a Small to Medium-Sized American City , 2018, Sustainability.

[15]  G. Gesquière,et al.  Change Detection of Cities , 2015 .

[16]  Yu-hsin Tsai Quantifying Urban Form: Compactness versus 'Sprawl' , 2005 .

[17]  C. Lavalle,et al.  Analysing the compactness of urban areas by using indicators derived from data acquired by remote sensing , 2007, 2007 Urban Remote Sensing Joint Event.

[18]  Yosef Jabareen,et al.  Sustainable Urban Forms , 2006 .

[19]  Jianping Wu,et al.  Automated derivation of urban building density information using airborne LiDAR data and object-based method , 2010 .

[20]  Juha Hyyppä,et al.  Automatic Detection of Buildings and Changes in Buildings for Updating of Maps , 2010, Remote. Sens..

[21]  Steven Hancock,et al.  Variation in experiences of nature across gradients of tree cover in compact and sprawling cities , 2017 .

[22]  Sara Shirowzhan,et al.  Spatial compactness metrics and Constrained Voxel Automata development for analyzing 3D densification and applying to point clouds: A synthetic review , 2018, Automation in Construction.

[23]  Yuek Ming Ho,et al.  Monitoring and assessment of urban growth patterns using spatio-temporal built-up area analysis , 2018, Environmental Monitoring and Assessment.

[24]  Lishan Xiao,et al.  A sustainable urban form: The challenges of compactness from the viewpoint of energy consumption and carbon emission , 2015 .