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Title of Journal: Urban Ecosyst

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Abbravation: Urban Ecosystems

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Springer US

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DOI

10.1002/asna.19071741002

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1573-1642

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Difficulties with estimating citywide urban fores

Authors: Jeffrey T Walton
Publish Date: 2008/01/08
Volume: 11, Issue: 1, Pages: 81-90
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Abstract

Two datasets of percent urban tree canopy cover were compared The first dataset was based on a 1991 AVHRR forest density map The second was the US Geological Survey’s National Land Cover Database NLCD 2001 subpixel tree canopy A comparison of these two tree canopy layers was conducted in 36 census designated places of western New York State Reference data generated by photointerpreting the tree cover on 1994 and 2002 orthoimages were compared on a citywide basis to estimates of the tree cover derived from the AVHRR and NLCD tree canopy maps Comparison of the AVHRRbased estimate with the 1994 photointerpreted reference showed low accuracy and high variability The comparison between the NLCDderived estimate and 2002 photointerpreted values had higher accuracy but shows a consistent under prediction bias for all tree cover values In comparing the two photointerpreted reference sets little actual change was detected for this study region Assessing change using differences between the imagerybased AVHRR and NLCD urban tree cover datasets is shown to lead to erroneous resultsThe work of Jayme Rapp who did the photo interpretation and Brett Kelly who has helped develop the NLCD tree canopy layer for zone 63 both students at the State University of New York—College of Environmental Science and Forestry SUNYESF is gratefully acknowledged David J Nowak USDA Forest Service and Stephen V Stehman SUNYESF reviewed an early version of the manuscript and provided many helpful suggestions This work was done in cooperation with USGS EROS Data Center and many other cooperators Funding for this project was provided in part by the USDA Forest Service’s RPA Assessment Staff and State Private Forestry’s Urban and Community Forestry Program Data analysis for this project was done in part using the open source statistical software R R Development Core Team 2007 The use of trade firm or corporation names in this article is for the information and convenience of the reader Such use does not constitute an official endorsement or approval by the United States Department of Agriculture or Forest Service of any product or service to the exclusion of others that may be suitable


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