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Doctoral thesis, 2021

Residential urban forest assessment methodologies : a management perspective

Klobucar, Blaz

Abstract

Many urban trees are located on private property in residential areas, but these trees are infrequently included in urban forest strategies and plans, meaning that for most local governments, the complete urban residential tree population, its potential for supplying ecosystem services and its dynamics are unknown.
This thesis examined the assessment methodologies of ecosystem services provided by trees in the attempt to provide valuable information about residential trees. The abundance of trees on individual residential properties was tested against potential decision-driving variables, collected using field work, remote sensing, questionnaire surveys and spatial property information.
While residents reported positive attitudes to trees and benefits they provide, this did not necessarily result in greater tree abundance on individual properties. It was found that long-term of validation of sampling methods is required for monitoring of urban trees. Remote sensing could be seen as a reliable and non-invasive way to determine canopy cover using publicly available information in residential areas.
This thesis improved understanding of residential urban trees and the ecosystem services they provide as the part of the urban forest. These assessment should include social and spatial variables influencing their development to allow residential trees to become integrated into local governance arrangement structure in order to develop informed management approaches for the entire urban forest.

Keywords

urban forestry; urban trees; ecosystem services; residential trees; governance; management; canopy cover; remote sensing

Published in

Acta Universitatis Agriculturae Sueciae
2021, number: 2021:45
ISBN: 978-91-7760-768-7, eISBN: 978-91-7760-769-4
Publisher: Department of Landscape Architecture, Planning and Management, Swedish University of Agricultural Sciences

Authors' information

UKÄ Subject classification

Landscape Architecture
Forest Science

URI (permanent link to this page)

https://res.slu.se/id/publ/111804