Sustainability 2016, 8(4), 296; doi:10.3390/su8040296
Author
1
Landscape Architecture Program, Arizona State University, PO Box 871605, Tempe, AZ 85287-1605, USA
2
Landscape Architecture Program, Virginia Polytechnic Institute and State University, 120 F Burruss Hall (0190), Blacksburg, VA 24061, USA
3
USDA Forest Service, Northern Research Station, 5 Moon Library, SUNY-ESF, Syracuse, NY 13215, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Tan Yigitcanlar
Received: 5 February 2016 / Revised: 17 March 2016 / Accepted: 18 March 2016 / Published: 23 March 2016
Abstract
Using the City of Roanoke, Virginia as a study site, this paper quantifies the forest structure, ecosystem services and values of vacant and residential land. Single family residential land had more trees (1,683,000) than vacant land (210,000) due largely to the differences in land area (32.44 km2 of vacant land vs. 57.94 km2 residential). While the percentage of tree coverage was almost identical across land uses (30.6% in vacant to 32.3% in residential), the number of trees per ha is greater on residential land (290.3) than on vacant land (63.4). The average healthy leaf surface area on individual trees growing on vacant land was greater than that of individual trees on residential land. The fact that trees in vacant land were found to provide more ecosystem services per tree than residential trees was attributed to this leaf area difference. Trees on vacant land are growing in more natural conditions and there are more large trees per ha. Assessing the forest structure and ecosystem services of Roanoke’s vacant and residential land provides a picture of the current extent and condition of the vacant and residential land. Understanding these characteristics provides the information needed for improved management and utilization of urban vacant land and estimating green infrastructure value. View Full-Text
Keywords: urban forestry; ecosystem services; green infrastructure
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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