• Submit to Remote Sensing Login Register
• MDPI
• Journals A-Z
• For Authors
• For Editors
• About
• Open Access Policy

• Abstract
• Full-Text PDF [412 KB]

• Article Statistics
• Google Scholar
• Order Reprints

• Cite this article
• Export to BibTeX
• Export to EndNote

• [+] on DOAJ
• Wang, J
• Lang, PA.
• [+] on Google Scholar
• Wang, J
• Lang, PA.
• [+] on PubMed
• Wang, J
• Lang, PA.

•  CiteULike
•  Facebook
•  Mendeley
•  Twitter

This article is

• freely available
• re-usable

Remote Sens. 2009, 1(4), 1028-1042; doi:10.3390/rs1041028

Article

Detection of Cypress Canopies in the Florida Panhandle Using Subpixel Analysis and GIS

Jialing Wang ^1,*  and Paul A. Lang ²

¹ Department of Geography, Geology, and the Environment, 319 Advanced Technology and Science Hall, Slippery Rock University of Pennsylvania, Slippery Rock, PA 16057, USA ² U.S. Fish and Wildlife Service, Panama City Field Office, 1601 Balboa Avenue, Panama City, FL 32405, USA

* Author to whom correspondence should be addressed.

Received: 22 September 2009; in revised form: 27 October 2009 / Accepted: 13 November 2009 / Published: 17 November 2009

Download PDF Full-Text [412 KB, uploaded 17 November 2009 09:02 CET]

Abstract: In this study, multitemporal subpixel analysis was used to identify cypress canopies from Landsat 7 ETM+ imagery. One spring and one fall image were selected for each of two sites, an eastern one centered on Tallahassee, FL and a western one centered on Panama City, FL. Signatures derived from the two eastern images were applied on the two western images that served as the control images for accuracy assessment. Results indicated that multitemporal subpixel analysis greatly improved the classification accuracy and signatures developed from one scene could be used to the subpixel classification of another scene with caution.

Keywords: subpixel analysis; cypress; Florida Panhandle

Article Statistics

Cite This Article