Urban forest structure effects on property value

Studies have quantified urban forests using well established field sampling methods. Other studies have used hedonic regression with real estate prices and remotely sensed vegetation cover data in valuation models. However, remote sensing introduces unfamiliar perspectives since it changes the scale...

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Autores:
Tipo de recurso:
Fecha de publicación:
2015
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/27167
Acceso en línea:
https://doi.org/10.1016/j.ecoser.2014.05.002
https://repository.urosario.edu.co/handle/10336/27167
Palabra clave:
Cultural ecosystem services
Non-market valuation
Hedonic analyses
Urban ecosystems
Urban tree cover
Ecosystem service tradeoffs
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License
Restringido (Acceso a grupos específicos)
id EDOCUR2_9548869c0187faf7c83aae72e0ffcfa8
oai_identifier_str oai:repository.urosario.edu.co:10336/27167
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling 2d7c8bf2-67a1-46d2-a8e0-b82768ad86d9-1c6cc95bd-eb0a-47ca-9c1f-3de7288a49a7-1383a9ae4-d19b-4ab4-a86b-875fb2771725-12020-08-19T14:41:12Z2020-08-19T14:41:12Z2015-04-01Studies have quantified urban forests using well established field sampling methods. Other studies have used hedonic regression with real estate prices and remotely sensed vegetation cover data in valuation models. However, remote sensing introduces unfamiliar perspectives since it changes the scale and resolution perceived by humans. Real estate prices also fluctuate and are not regularly used in urban decision-making processes. This study values an urban forest cultural ecosystem service by integrating an explanatory hedonic regression model with randomly field-measured tree, shrub, and turf data from four cities across Florida, USA, during 2006–2009, and congruent parcel tract-level home attributes and appraised property values from single and multi-family units for 2008–2009. Results, on average, indicate trade-offs in that more trees with greater Leaf Area Indices (LAIs) add to property value, while biomass and tree–shrub cover have a neutral effect, and replacing tree with grass cover has lower value. On average, property value increased by $1586 per tree and $9348 per one-unit increase in LAI, while increasing maintained grass from 25% to 75% decreased home value by $271. Our ecological approach is an alternative, applied method that can be used by decision-makers for policy and cost–benefit analyses that calculate the stream of net benefits associated with urban forests.application/pdfhttps://doi.org/10.1016/j.ecoser.2014.05.002ISSN: 2212-0416https://repository.urosario.edu.co/handle/10336/27167engElsevier217209Ecosystem ServicesVol. 12Ecosystem Services, ISSN:2212-0416, Vol.12 (April, 2015); pp. 209-217https://www.sciencedirect.com/science/article/abs/pii/S2212041614000394Restringido (Acceso a grupos específicos)http://purl.org/coar/access_right/c_16ecEcosystem Servicesinstname:Universidad del Rosarioreponame:Repositorio Institucional EdocURCultural ecosystem servicesNon-market valuationHedonic analysesUrban ecosystemsUrban tree coverEcosystem service tradeoffsUrban forest structure effects on property valueEfectos de la estructura del bosque urbano en el valor de la propiedadarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Escobedo, Francisco J.Damian, Adams C.Timilsina, Nilesh10336/27167oai:repository.urosario.edu.co:10336/271672021-06-03 00:50:06.87https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv Urban forest structure effects on property value
dc.title.TranslatedTitle.spa.fl_str_mv Efectos de la estructura del bosque urbano en el valor de la propiedad
title Urban forest structure effects on property value
spellingShingle Urban forest structure effects on property value
Cultural ecosystem services
Non-market valuation
Hedonic analyses
Urban ecosystems
Urban tree cover
Ecosystem service tradeoffs
title_short Urban forest structure effects on property value
title_full Urban forest structure effects on property value
title_fullStr Urban forest structure effects on property value
title_full_unstemmed Urban forest structure effects on property value
title_sort Urban forest structure effects on property value
dc.subject.keyword.spa.fl_str_mv Cultural ecosystem services
Non-market valuation
Hedonic analyses
Urban ecosystems
Urban tree cover
Ecosystem service tradeoffs
topic Cultural ecosystem services
Non-market valuation
Hedonic analyses
Urban ecosystems
Urban tree cover
Ecosystem service tradeoffs
description Studies have quantified urban forests using well established field sampling methods. Other studies have used hedonic regression with real estate prices and remotely sensed vegetation cover data in valuation models. However, remote sensing introduces unfamiliar perspectives since it changes the scale and resolution perceived by humans. Real estate prices also fluctuate and are not regularly used in urban decision-making processes. This study values an urban forest cultural ecosystem service by integrating an explanatory hedonic regression model with randomly field-measured tree, shrub, and turf data from four cities across Florida, USA, during 2006–2009, and congruent parcel tract-level home attributes and appraised property values from single and multi-family units for 2008–2009. Results, on average, indicate trade-offs in that more trees with greater Leaf Area Indices (LAIs) add to property value, while biomass and tree–shrub cover have a neutral effect, and replacing tree with grass cover has lower value. On average, property value increased by $1586 per tree and $9348 per one-unit increase in LAI, while increasing maintained grass from 25% to 75% decreased home value by $271. Our ecological approach is an alternative, applied method that can be used by decision-makers for policy and cost–benefit analyses that calculate the stream of net benefits associated with urban forests.
publishDate 2015
dc.date.created.spa.fl_str_mv 2015-04-01
dc.date.accessioned.none.fl_str_mv 2020-08-19T14:41:12Z
dc.date.available.none.fl_str_mv 2020-08-19T14:41:12Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1016/j.ecoser.2014.05.002
dc.identifier.issn.none.fl_str_mv ISSN: 2212-0416
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/27167
url https://doi.org/10.1016/j.ecoser.2014.05.002
https://repository.urosario.edu.co/handle/10336/27167
identifier_str_mv ISSN: 2212-0416
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 217
dc.relation.citationStartPage.none.fl_str_mv 209
dc.relation.citationTitle.none.fl_str_mv Ecosystem Services
dc.relation.citationVolume.none.fl_str_mv Vol. 12
dc.relation.ispartof.spa.fl_str_mv Ecosystem Services, ISSN:2212-0416, Vol.12 (April, 2015); pp. 209-217
dc.relation.uri.spa.fl_str_mv https://www.sciencedirect.com/science/article/abs/pii/S2212041614000394
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
dc.rights.acceso.spa.fl_str_mv Restringido (Acceso a grupos específicos)
rights_invalid_str_mv Restringido (Acceso a grupos específicos)
http://purl.org/coar/access_right/c_16ec
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Elsevier
dc.source.spa.fl_str_mv Ecosystem Services
institution Universidad del Rosario
dc.source.instname.none.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.none.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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