Mapping Urban Green Infrastructure: A Novel Landscape-Based Approach to Incorporating Land Use and Land Cover in the Mapping of Human-Dominated Systems

Matthew Dennis, David Barlow, Gina Cavan, Penny A. Cook, Anna Gilchrist, John Handley, Philip James, Jessica Thompson, Konstantinos Tzoulas, C. Philip Wheater and Sarah Lindley
Additional contact information
Matthew Dennis: School of Environment Education and Development, University of Manchester, Oxford Road, Manchester M13 9PL, UK
David Barlow: Manchester City Council, Manchester Town Hall, Albert Square, Manchester M60 2LA, UK
Gina Cavan: School of Science and the Environment, Manchester Metropolitan University, Oxford Road, Manchester M15 6BH, UK
Penny A. Cook: School of Health Sciences, University of Salford, The Crescent, Manchester M5 4WT, UK
Anna Gilchrist: School of Environment Education and Development, University of Manchester, Oxford Road, Manchester M13 9PL, UK
John Handley: School of Environment Education and Development, University of Manchester, Oxford Road, Manchester M13 9PL, UK
Philip James: School of Environment and Life Sciences, University of Salford, The Crescent, Manchester M5 4WT, UK
Jessica Thompson: City of Trees, 6 Kansas Avenue, Salford M50 2GL, UK
Konstantinos Tzoulas: School of Science and the Environment, Manchester Metropolitan University, Oxford Road, Manchester M15 6BH, UK
C. Philip Wheater: School of Science and the Environment, Manchester Metropolitan University, Oxford Road, Manchester M15 6BH, UK
Sarah Lindley: School of Environment Education and Development, University of Manchester, Oxford Road, Manchester M13 9PL, UK

Land, 2018, vol. 7, issue 1, 1-25

Abstract: 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.

Keywords: health and well-being; GIS; remote sensing; urban ecosystems; social–ecological systems (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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