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Abstract
As remote-sensing technology advances, high-resolution imagery, such as Quickbird and photography from the National Agriculture Imagery Program (NAIP), is becoming more readily available for use in forestry applications. Quickbird imagery is currently the highest resolution imagery commercially available. It consists of 2.44-m (8-ft) resolution multispectral bands ranging from blue to near infrared and a panchromatic band acquired simultaneously at 0.61-m (2-ft) resolution. In the near future, NAIP will provide annually updated, orthorectified, natural color, aerial photography at 1-m resolution across the continental United States. Our objective was to investigate two classification methods: an individual tree crown delineation and classification procedure and a technique using Feature Analyst software for classifying high-resolution Quickbird and NAIP photography. Both methods were found to be effective for discriminating different vegetation types using Quickbird and NAIP photography, although the Quickbird imagery proved to be superior to the NAIP photography according to visual and numerical assessments.
Parent Publication
Citation
Frescino, Tracey S.; Moisen, Gretchen G.; DeBlander, Larry; Guerin, Michel. 2007. The investigation of classification methods of high-resolution imagery. In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H., eds. Proceedings of the seventh annual forest inventory and analysis symposium; October 3-6, 2005; Portland, ME. Gen. Tech. Rep. WO-77. Washington, DC: U.S. Department of Agriculture, Forest Service: 161-169.
