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Climate-informed urban design via probabilistic acceptability criterion and Sharpe ratio selection
We develop a new framework for selecting an urban design which performs best from an Outdoor Thermal Comfort (OTC) perspective, while taking into account the uncertainty in the OTC preference of individuals. To this end, we first present and develop the notion of Probabilistic Acceptability Criterio...
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| Published in: | Environment, development and sustainability development and sustainability, 2022, Vol.24 (1), p.617-645 |
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| container_title | Environment, development and sustainability |
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| creator | Nevat, Ido |
| description | We develop a new framework for selecting an urban design which performs best from an Outdoor Thermal Comfort (OTC) perspective, while taking into account the uncertainty in the OTC preference of individuals. To this end, we first present and develop the notion of
Probabilistic Acceptability Criterion
(PAC) which is a new method to quantify people’s satisfaction of OTC values, based on data collected from a survey. We develop the PAC for both regression and classification models which are most common statistical analysis methods in the literature. Next, based on the PAC, we develop a new approach to scoring each of the urban designs, based on
Binary Probabilistic Impact Function
, which extends the widely used
deterministic impact function
. We show that the score is a random variable which follows a
Poisson-Binomial
distribution and characterise its parameters. We then use those results and present a new approach for scoring of the urban designs that is based on the
Sharpe ratio
, which is a widely used metric in financial applications. Our framework is the first model which provides urban designers the ability to evaluate the quality of their urban designs from an OTC point of view, while taking the uncertainty into account in a holistic and rigorous way. We illustrate our framework by applying it to a real case study in Singapore. |
| doi_str_mv | 10.1007/s10668-021-01460-7 |
| format | article |
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Probabilistic Acceptability Criterion
(PAC) which is a new method to quantify people’s satisfaction of OTC values, based on data collected from a survey. We develop the PAC for both regression and classification models which are most common statistical analysis methods in the literature. Next, based on the PAC, we develop a new approach to scoring each of the urban designs, based on
Binary Probabilistic Impact Function
, which extends the widely used
deterministic impact function
. We show that the score is a random variable which follows a
Poisson-Binomial
distribution and characterise its parameters. We then use those results and present a new approach for scoring of the urban designs that is based on the
Sharpe ratio
, which is a widely used metric in financial applications. Our framework is the first model which provides urban designers the ability to evaluate the quality of their urban designs from an OTC point of view, while taking the uncertainty into account in a holistic and rigorous way. We illustrate our framework by applying it to a real case study in Singapore.</description><identifier>ISSN: 1387-585X</identifier><identifier>EISSN: 1573-2975</identifier><identifier>DOI: 10.1007/s10668-021-01460-7</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Acceptability ; Acceptance criteria ; Binomial distribution ; Classification ; Design ; Earth and Environmental Science ; Ecology ; Economic Geology ; Economic Growth ; Environment ; Environmental Economics ; Environmental Management ; Over the counter sales ; Probability ; Random variables ; Regression analysis ; Statistical analysis ; Statistical methods ; Sustainable Development ; Thermal comfort ; Uncertainty ; Urban areas ; Urban planning</subject><ispartof>Environment, development and sustainability, 2022, Vol.24 (1), p.617-645</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2021</rights><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-f20b087b540f9b6e90cbab9e74308356204653ea176b442f7cb64664c1161ae43</citedby><cites>FETCH-LOGICAL-c319t-f20b087b540f9b6e90cbab9e74308356204653ea176b442f7cb64664c1161ae43</cites><orcidid>0000-0003-1567-3446</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2617591548/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2617591548?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>315,786,790,11715,12874,27957,27958,33258,36095,44398,75252</link.rule.ids></links><search><creatorcontrib>Nevat, Ido</creatorcontrib><title>Climate-informed urban design via probabilistic acceptability criterion and Sharpe ratio selection</title><title>Environment, development and sustainability</title><addtitle>Environ Dev Sustain</addtitle><description>We develop a new framework for selecting an urban design which performs best from an Outdoor Thermal Comfort (OTC) perspective, while taking into account the uncertainty in the OTC preference of individuals. To this end, we first present and develop the notion of
Probabilistic Acceptability Criterion
(PAC) which is a new method to quantify people’s satisfaction of OTC values, based on data collected from a survey. We develop the PAC for both regression and classification models which are most common statistical analysis methods in the literature. Next, based on the PAC, we develop a new approach to scoring each of the urban designs, based on
Binary Probabilistic Impact Function
, which extends the widely used
deterministic impact function
. We show that the score is a random variable which follows a
Poisson-Binomial
distribution and characterise its parameters. We then use those results and present a new approach for scoring of the urban designs that is based on the
Sharpe ratio
, which is a widely used metric in financial applications. Our framework is the first model which provides urban designers the ability to evaluate the quality of their urban designs from an OTC point of view, while taking the uncertainty into account in a holistic and rigorous way. 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Probabilistic Acceptability Criterion
(PAC) which is a new method to quantify people’s satisfaction of OTC values, based on data collected from a survey. We develop the PAC for both regression and classification models which are most common statistical analysis methods in the literature. Next, based on the PAC, we develop a new approach to scoring each of the urban designs, based on
Binary Probabilistic Impact Function
, which extends the widely used
deterministic impact function
. We show that the score is a random variable which follows a
Poisson-Binomial
distribution and characterise its parameters. We then use those results and present a new approach for scoring of the urban designs that is based on the
Sharpe ratio
, which is a widely used metric in financial applications. Our framework is the first model which provides urban designers the ability to evaluate the quality of their urban designs from an OTC point of view, while taking the uncertainty into account in a holistic and rigorous way. We illustrate our framework by applying it to a real case study in Singapore.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10668-021-01460-7</doi><tpages>29</tpages><orcidid>https://orcid.org/0000-0003-1567-3446</orcidid></addata></record> |
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| ispartof | Environment, development and sustainability, 2022, Vol.24 (1), p.617-645 |
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| source | EBSCOhost Business Source Ultimate; International Bibliography of the Social Sciences (IBSS); ABI/INFORM Global; Springer Link |
| subjects | Acceptability Acceptance criteria Binomial distribution Classification Design Earth and Environmental Science Ecology Economic Geology Economic Growth Environment Environmental Economics Environmental Management Over the counter sales Probability Random variables Regression analysis Statistical analysis Statistical methods Sustainable Development Thermal comfort Uncertainty Urban areas Urban planning |
| title | Climate-informed urban design via probabilistic acceptability criterion and Sharpe ratio selection |
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