Gina Cavan

Dr. Gina Cavan

Manchester Metropolitan University, UK
orcid

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2015 in Progress in Planning
Verified
Journal Article
Open access
JCJeremy Graham Carter
Jeremy Graham Carter
GCGina Cavan
Gina Cavan
ACAngela Connelly
Angela Connelly
SGSimon Guy
Simon Guy
JHJohn Handley
John Handley
AKAleksandra Kazmierczak
Aleksandra Kazmierczak

1 November 2011 in Landscape and Urban Planning
Verified
Journal Article
Closed access
AKAleksandra Kaźmierczak
Aleksandra Kaźmierczak
GCGina Cavan
Gina Cavan

1 February 2016 in Agricultural and Forest Meteorology
Verified
Journal Article
Closed access
FKFanhua Kong
Fanhua Kong
WYWeijiao Yan
Weijiao Yan
GZGuang Zheng
Guang Zheng
HYHaiwei Yin
Haiwei Yin
GCGina Cavan
Gina Cavan
LCLiang Cheng
Liang Cheng

1 January 2014 in Urban Forestry & Urban Greening
Verified
Journal Article
Closed access
FKFanhua Kong
Fanhua Kong
HYHaiwei Yin
Haiwei Yin
CWCuizhen Wang
Cuizhen Wang
GCGina Cavan
Gina Cavan
PJPhilip James
Philip James

25 January 2018 in Land
Verified
Journal Article
Open access
PDF file
MDMatthew Dennis
Matthew Dennis
DBDavid Barlow
David Barlow
GCGina Cavan
Gina Cavan
PCPenny A Cook
Penny A Cook
AGAnna Gilchrist
Anna Gilchrist
SLSarah Lindley
Sarah Lindley
Common approaches to mapping green infrastructure in urbanised landscapes invariably focus on measures of land use or land cover and associated functional or physical traits. However, such one-dimensional perspectives do not accurately capture the character and complexity of the landscapes in which urban inhabitants live. The new approach presented in this paper demonstrates how open-source, high spatial and temporal resolution data with global coverage can be used to measure and represent the landscape qualities of urban environments. Through going beyond simple metrics of quantity, such as percentage green and blue cover, it is now possible to explore the extent to which landscape quality helps to unpick the mixed evidence presented in the literature on the benefits of urban nature to human well-being. Here we present a landscape approach, employing remote sensing, GIS and data reduction techniques to map urban green infrastructure elements in a large U.K. city region. Comparison with existing urban datasets demonstrates considerable improvement in terms of coverage and thematic detail. The characterisation of landscapes, using census tracts as spatial units, and subsequent exploration of associations with social–ecological attributes highlights the further detail that can be uncovered by the approach. For example, eight urban landscape types identified for the case study city exhibited associations with distinct socioeconomic conditions accountable not only to quantities but also qualities of green and blue space. The identification of individual landscape features through simultaneous measures of land use and land cover demonstrated unique and significant associations between the former and indicators of human health and ecological condition. The approach may therefore provide a promising basis for developing further insight into processes and characteristics that affect human health and well-being in urban areas, both in the United Kingdom and beyond.

30 December 2010 in Climate Research
Verified
Journal Article
Closed access
KAK Albertson
K Albertson
JAJ Aylen
J Aylen
GCGina Cavan
Gina Cavan
JMJ McMorrow
J McMorrow