Next Article in Journal
Previous Article in Journal
Remote Sens. 2012, 4(6), 1741-1757; doi:10.3390/rs4061741
Article

Individual Urban Tree Species Classification Using Very High Spatial Resolution Airborne Multi-Spectral Imagery Using Longitudinal Profiles

*  and
Received: 10 April 2012; in revised form: 5 June 2012 / Accepted: 5 June 2012 / Published: 11 June 2012
View Full-Text   |   Download PDF [2595 KB, updated 19 June 2014; original version uploaded 19 June 2014]
Abstract: Individual tree species identification is important for urban forest inventory and ecology management. Recent advances in remote sensing technologies facilitate more detailed estimation of individual urban tree characteristics. This study presents an approach to improve the classification of individual tree species via longitudinal profiles from very high spatial resolution airborne imagery. The longitudinal profiles represent the side view tree shape, which play a very important role in individual tree species on-site identification. Decision tree classification was employed to conduct the final classification result. Using this profile approach, six major species (Maple, Ash, Birch, Oak, Spruce, Pine) of trees on the York University (Ontario, Canada) campus were successfully identified. Two decision trees were constructed, one knowledge-based and one derived from gain ratio criteria. The classification accuracy achieved were 84% and 86%, respectively.
Keywords: classification; urban; high spatial resolution; multi-spectral; longitudinal profiles; trees species; decision trees classification; urban; high spatial resolution; multi-spectral; longitudinal profiles; trees species; decision trees
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.

Export to BibTeX |
EndNote


MDPI and ACS Style

Zhang, K.; Hu, B. Individual Urban Tree Species Classification Using Very High Spatial Resolution Airborne Multi-Spectral Imagery Using Longitudinal Profiles. Remote Sens. 2012, 4, 1741-1757.

AMA Style

Zhang K, Hu B. Individual Urban Tree Species Classification Using Very High Spatial Resolution Airborne Multi-Spectral Imagery Using Longitudinal Profiles. Remote Sensing. 2012; 4(6):1741-1757.

Chicago/Turabian Style

Zhang, Kongwen; Hu, Baoxin. 2012. "Individual Urban Tree Species Classification Using Very High Spatial Resolution Airborne Multi-Spectral Imagery Using Longitudinal Profiles." Remote Sens. 4, no. 6: 1741-1757.


Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert