Research Papers

High-resolution tree canopy mapping for New York City using LIDAR and object-based image analysis

[+] Author Affiliations
Sean W. MacFaden, Jarlath P.M. O’Neil-Dunne, Anna R. Royar

University of Vermont, Spatial Analysis Laboratory, Rubenstein School of Environment and Natural Resources, 81 Carrigan Drive, Burlington, Vermont 05405

Jacqueline W.T. Lu

NYC Department of Parks & Recreation, Forestry, Horticulture & Natural Resources, Olmsted Center, Flushing Meadow Corona Park, Flushing, New York 11368

Andrew G. Rundle

Columbia University, Mailman School of Public Health, 622 West 168th Street, New York, New York 10032

J. Appl. Remote Sens. 6(1), 063567 (Sep 12, 2012). doi:10.1117/1.JRS.6.063567
History: Received January 4, 2012; Revised July 18, 2012; Accepted July 26, 2012
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Abstract.  Urban tree canopy is widely believed to have myriad environmental, social, and human-health benefits, but a lack of precise canopy estimates has hindered quantification of these benefits in many municipalities. This problem was addressed for New York City using object-based image analysis (OBIA) to develop a comprehensive land-cover map, including tree canopy to the scale of individual trees. Mapping was performed using a rule-based expert system that relied primarily on high-resolution LIDAR, specifically its capacity for evaluating the height and texture of aboveground features. Multispectral imagery was also used, but shadowing and varying temporal conditions limited its utility. Contextual analysis was a key part of classification, distinguishing trees according to their physical and spectral properties as well as their relationships to adjacent, nonvegetated features. The automated product was extensively reviewed and edited via manual interpretation, and overall per-pixel accuracy of the final map was 96%. Although manual editing had only a marginal effect on accuracy despite requiring a majority of project effort, it maximized aesthetic quality and ensured the capture of small, isolated trees. Converting high-resolution LIDAR and imagery into usable information is a nontrivial exercise, requiring significant processing time and labor, but an expert system–based combination of OBIA and manual review was an effective method for fine-scale canopy mapping in a complex urban environment.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Sean W. MacFaden ; Jarlath P.M. O’Neil-Dunne ; Anna R. Royar ; Jacqueline W.T. Lu and Andrew G. Rundle
"High-resolution tree canopy mapping for New York City using LIDAR and object-based image analysis", J. Appl. Remote Sens. 6(1), 063567 (Sep 12, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063567


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