| id |
ecaade2020_075 |
| authors |
Yoffe, Hatzav, Plaut, Pnina, Fried, Shaked and J. Grobman, Yasha |
| year |
2020 |
| title |
Enriching the Parametric Vocabulary of Urban Landscapes - A framework for computer-aided performance evaluation of sustainable development design models |
| source |
Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 47-56 |
| doi |
https://doi.org/10.52842/conf.ecaade.2020.1.047
|
| summary |
Three decades past since the adoption of sustainability rating systems (SRS) by the Architecture Engineering and Construction industry (AEC) as standard methods for sustainable development evaluation. Nevertheless, these methods still suffer from a low adoption and implementation rate due to their manual, labor-intensive, expert dependent, and time-demanding process. The partial success of urban development evaluation puts forth the question: Are there faster, more accurate quantitative methods for advancing sustainability evaluation? The paper describes a prototype workflow for evaluating the performance of urban landscape design in a single digital workflow, based on ecological key indicator criteria. Grasshopper and Python parametric platforms were used to translate the criteria into quantitative spatial metrics. This study demonstrates optimized biomass measurement in two urban scales in line with the SITES rating system for landscape development: (XS) site development and (XL) neighborhood scale. The measured biomass density is used as a positive indication of ecosystem services capacity in the development site. The framework's quantitative workflow contributes to additional spatial feedbacks compared to the original numeric-based rating system method. Through these, composition and configuration metrics such as ecological connectivity, edge contrast, and patch shape can be visualized, measured, and compared. The metrics, which indicate performance characteristics of the design, generate new opportunities for data-rich sustainability evaluations of urban landscapes, using a single computer-aided workflow. |
| keywords |
Sustainable development; Urban landscape |
| series |
eCAADe |
| email |
|
| full text |
 file.pdf (3,674,986 bytes) |
| references |
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|
Azzari, G and Lobell, DB (2017)
 Landsat-based classification in the cloud: An opportunity for a paradigm shift in land cover monitoring
, Remote Sensing of Environment, 202, pp. 64-74
|
|
|
|
|
Azzari, G, Jain, M and Lobell, DB (2017)
Towards fine resolution global maps of crop yields: Testing multiple methods and satellites in three countries
, Remote Sensing of Environment, 202, pp. 129-141
|
|
|
|
|
Barbosa, O, Tratalos, JA, Armsworth, PR, Davies, RG, Fuller, RA, Johnson, P and Gaston, KJ (2007)
Who benefits from access to green space? A case study from Sheffield, UK
, Landscape and Urban Planning, 83(2), pp. 187-195
|
|
|
|
|
Batty, M (2013)
Big data, smart cities and city planning.
, Dialogues in human geography, 3(3), pp. 274-279
|
|
|
|
|
Bibri, SE and Krogstie, J (2017)
Smart sustainable cities of the future: An extensive interdisciplinary literature review
, Sustainable Cities and Society, 31, pp. 183-212
|
|
|
|
|
Biswas, T and Krishnamurti, R (2012)
Data Sharing for Sustainable Building Assessment
, International Journal of Architectural Computing, 10(4), pp. 555-574
|
|
|
|
|
Botequilha Leit\~ao, A and Ahern, J (2002)
Applying landscape ecological concepts and metrics in sustainable landscape planning
, Landscape and Urban Planning, 59, pp. 65-93
|
|
|
|
|
BRE Group, BREEAM (2012)
BREEAM Communities technical manual - breeam_communities
, BRE Group
|
|
|
|
|
Brown, RD and Corry, RC (2011)
Evidence-based landscape architecture: The maturing of a profession
, Landscape and Urban Planning, 100(4), pp. 327-329
|
|
|
|
|
CEEQUAL, CEEQUAL (2008)
Sustainability Assessments and Awards for Civil Engineering, Infrastructure, Landscaping and the Public Realm Version 4
, CEEQUAL
|
|
|
|
|
Corry, RC and Nassauer, JI (2005)
Limitations of using landscape pattern indices to evaluate the ecological consequences of alternative plans and designs
, Landscape and Urban Planning, 72, pp. 265-280
|
|
|
|
|
Diao, M, Zhu, Y, Ferreira, J and Ratti, C (2016)
Inferring individual daily activities from mobile phone traces: A Boston example
, Environment and Planning B: Planning and Design, 43(5), pp. 920-940
|
|
|
|
|
Eberenz, J, Verbesselt, J, Herold, M, Tsendbazar, NE, Sabatino, G and Rivolta, G (2016)
Evaluating the potential of proba-v satellite image time series for improving lc classification in semi-arid african landscapes
, Remote Sensing, 8(12), p. 987
|
|
|
|
|
Georgi, C, Spengler, D, Itzerott, S and Kleinschmit, B (2018)
Automatic delineation algorithm for site-specific management zones based on satellite remote sensing data
, Precision Agriculture, 19, pp. 684-707
|
|
|
|
|
Grobman, YJ, Kozlovsky, R, Levy, H, Grobman, YJ, Kozlovsky, R, A, HL and Grobman, YJ (2017)
A multifunctional computational approach to waterfront design
, Architectural Science Review, 60(November), pp. 446-459
|
|
|
|
|
Institute for Sustainable Infrastructure, ISI (2018)
ENVISION SUSTAINABLE INFRASTRUCTURE FRAMEWORK VERSION 3
, Institute for Sustainable Infrastructure Washington, DC, Washington DC
|
|
|
|
|
Kitchin, R (2014)
The real-time city? Big data and smart urbanism
, GeoJournal, 79(1), pp. 1-14
|
|
|
|
|
Liu, L, Coops, NC, Aven, NW and Pang, Y (2017)
Mapping urban tree species using integrated airborne hyperspectral and LiDAR remote sensing data
, Remote Sensing of Environment, 200, pp. 170-182
|
|
|
|
|
Lu, X, Wrathall, DJ, Sundsoy, PR, Nadiruzzaman, M, Wetter, E, Iqbal, A, Qureshi, T, Tatem, AJ, Canright, GS, Engo-monsen, K and Bengtsson, L (2016)
Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen
, Climatic Change, 138(3-4), pp. 505-519
|
|
|
|
|
McGarigal, K. and Marks, B. J. (1995)
FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure
, General Technical Report - US Department of Agriculture, Forest Service
|
|
|
|
| last changed |
2022/06/07 07:57 |
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