Local climate zone approach on local and micro scales: Dividing the urban open space

Abstract This article is a formalisation of the local climate zone (LCZ) classification on a local and micro scales. It is also an attempt to transpose this classification to a fine grained level of detail. The urban space is divided into virtual sensors for which five morphological indicators are calculated. Therefore, this work exposes a comparison of two methods dividing the urban space: the Delaunay triangulation versus a Skeletonization. These algorithms are based on a standard vector dataset and integrated in a free and open source Geographic Information System. These algorithms are applied to New York and districts of Nantes. The skeletonization presents the advantage of pulling down the calculation time without affecting the accuracy. Moreover, the methodology proposed is reproducible everywhere. In addition, the major LCZ obtained on the districts of Nantes are verified by comparison to previous measurements and classifications, which supports the results presented in this paper. Finally, the methodology and functionalities developed in this paper seem useful for the urban climate community and town planners, because LCZ can provide input data for numerical climate models that incorporate urban canopy parameters to forecast climate variables and forecast Urban heat island (UHI).

[1]  Gerald Mills,et al.  Cities as agents of global change , 2007 .

[2]  H. Andrieu,et al.  A pavement-watering thermal model for SOLENE-microclimat: Development and evaluation , 2018, Urban Climate.

[3]  Jan Geletič,et al.  GIS-based delineation of local climate zones: The case of medium-sized Central European cities , 2016 .

[4]  Fredrik Lindberg,et al.  Computing continuous sky view factors using 3D urban raster and vector databases: comparison and application to urban climate , 2009 .

[5]  J. Mendes,et al.  Sky view factors estimation using a 3d-gis extension , 2003 .

[6]  J. Unger,et al.  Design of an urban monitoring network based on Local Climate Zone mapping and temperature pattern modelling , 2014 .

[7]  Michel Couprie,et al.  Comparing Sky Shape Skeletons for the Analysis of Visual Dynamics along Routes , 2007 .

[8]  E. Bocher,et al.  Sky View Factor Calculation in Urban Context: Computational Performance and Accuracy Analysis of Two Open and Free GIS Tools , 2018, Climate.

[9]  Rajashree Kotharkar,et al.  Evaluating urban heat island in the critical local climate zones of an Indian city , 2018 .

[10]  Maria Tombrou,et al.  The International Urban Energy Balance Models Comparison Project: First Results from Phase 1 , 2010 .

[11]  J. Monteith,et al.  Boundary Layer Climates. , 1979 .

[12]  Xueyao Zhang,et al.  How to Design a Park and Its Surrounding Urban Morphology to Optimize the Spreading of Cool Air , 2018 .

[13]  C. Inard,et al.  The use of SOLENE-microclimat model to assess adaptation strategies at the district scale , 2015 .

[14]  T. Oke,et al.  Local Climate Zones for Urban Temperature Studies , 2012 .

[15]  Dieter Scherer,et al.  Intra and inter ‘local climate zone’ variability of air temperature as observed by crowdsourced citizen weather stations in Berlin, Germany , 2017 .

[16]  J. Bouyer,et al.  Using Local Climate Zone scheme for UHI assessment: Evaluation of the method using mobile measurements , 2015 .

[17]  Rohinton Emmanuel,et al.  A "Local Climate Zone" based approach to urban planning in Colombo, Sri Lanka , 2016 .

[18]  Stan Openshaw,et al.  Modifiable Areal Unit Problem , 2008, Encyclopedia of GIS.

[19]  Daniel Fenner,et al.  Micro-Scale Variability of Air Temperature within a Local Climate Zone in Berlin, Germany, during Summer , 2018 .

[20]  C. Inard,et al.  Assessment of Direct and Indirect Impacts of Vegetation on Building Comfort: A Comparative Study of Lawns, Green Walls and Green Roofs , 2017 .

[21]  Urban morphology and energy performance: the direct and indirect contribution in mediterranean climate , 2015 .

[22]  Frieke Van Coillie,et al.  Quality of Crowdsourced Data on Urban Morphology—The Human Influence Experiment (HUMINEX) , 2017 .

[23]  T. Oke Street design and urban canopy layer climate , 1988 .

[24]  I. D. Watson,et al.  The determination of view-factors in urban canyons , 1984 .

[25]  Timothy R. Oke,et al.  Evaluation of the ‘local climate zone’ scheme using temperature observations and model simulations , 2014 .

[26]  P. Keravec,et al.  Urban heat island temporal and spatial variations: Empirical modeling from geographical and meteorological data , 2017 .

[27]  Li-wei Lai The influence of urban heat island phenomenon on PM concentration: an observation study during the summer half-year in metropolitan Taipei, Taiwan , 2016, Theoretical and Applied Climatology.

[28]  H. Andrieu,et al.  Radiative properties of the urban fabric derived from surface form analysis: A simplified solar balance model , 2015 .

[29]  Bingfeng Yu,et al.  Study on the influence of albedo on building heat environment in a year-round , 2008 .

[30]  Nathalie Long,et al.  Building Local Climate Zones by using socio-economic and topographic vectorial databases , 2015 .

[31]  Timothy R. Oke,et al.  Towards better scientific communication in urban climate , 2006 .

[32]  Douw G. Steyn,et al.  The calculation of view factors from fisheye‐lens photographs: Research note , 1980 .

[33]  M. Benedikt,et al.  To Take Hold of Space: Isovists and Isovist Fields , 1979 .

[34]  Jacques Teller,et al.  Townscope II—A computer system to support solar access decision-making , 2001 .