Title
A Remote Sensing Based Vegetation Classification Logic for Global Land Cover Analysis
Document Type
Article
Publication Title
Remote Sensing of Environment
Publication Date
1-1995
Volume
51
Issue
1
First Page
39
Last Page
48
Abstract
This article proposes a simple new logic for classifying global vegetation. The critical features of this classification are that 1) it is based on simple, observable, unambiguous characteristics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation, 2) the structural characteristics are remotely sensible so that repeatable and efficient global reclassifications of existing vegetation will be possible, and 3) the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km AVHRR normalized difference vegetation index database. Procedures for solving critical remote sensing problems needed to implement the classification are discussed. Also, some inferences from this classification to advanced vegetation biophysical variables such as specific leaf area and photosynthetic capacity useful to global biogeochemical modeling are suggested.
DOI
http://dx.doi.org/10.1016/0034-4257(94)00063-S
Rights
© 1995 Elsevier
Recommended Citation
Running, S. W., Loveland T. R., Pierce L. L., Nemani R. R., and Hunt Jr. E. R. (1995). A Remote Sensing Based Vegetation Classification Logic for Global Land Cover Analysis. Remote Sensing of Environment: 51(1), 39-48, doi: http://dx.doi.org/10.1016/0034-4257(94)00063-S