Rationale and Conceptual Framework for Classification Approaches to Assess Forest Resources and Properties

  • Janet Franklin
  • John Rogan
  • Stuart R. Phinn
  • Curtis E. Woodcock
Chapter

Abstract

Classification has been an important tool in digital image analysis for land resources applications since early Landsat missions when it was recognized that multispectral digital images are composed of multivariate measurement vectors for each and every pixel. The hundreds of thousands of such vectors typically making up an image could be treated as class descriptors, and the spectral bands as explanatory variables related to categories of interest in the image. This is an application of the more general methodology of classification or pattern recognition (Ripley 1996). This Chapter provides a conceptual framework for selecting appropriate classification approaches to assess forest resources and forest (canopy, stand, and landscape) properties. It is beyond the scope of this Chapter to provide a comprehensive review of recent literature on image classification. S. E. Franklin (2001) provided an excellent overview of classification for the remote sensing of forests, and we use that work as a point of departure. Textbooks such as those by Jensen (1996) and Schowengerdt (1997) provide comprehensive explanations of the general problem of classification in remote sensing. Several recent reviews also outline advances in the use of classification in forest remote sensing Wulder 1998, Trietz and Howarth 1999, Lucas et al. in press, Woodcock in press).

Keywords

Land Cover Remote Sensing Forest Type Synthetic Aperture Radar Classification Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Janet Franklin
    • 1
  • John Rogan
    • 1
  • Stuart R. Phinn
    • 2
  • Curtis E. Woodcock
    • 3
  1. 1.Department GeographySan Diego State UniversitySan DiegoUSA
  2. 2.School of Geography, Planning & ArchitectureUniversity of QueenslandBrisbaneAustralia
  3. 3.Department GeographyBoston UniversityBostonUSA

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