Title :
Linearized vegetation indices using a formal statistical framework
Author :
Ünsalan, Cem ; Boyer, Kim L.
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
Abstract :
Vegetation indices have been used extensively to estimate the vegetation density from satellite and airborne images for many years. In this paper, we first focus on one of the most popular vegetation indices, the normalized difference vegetation index (NDVI) by J. W. Rouse (1974) and introduce a statistical framework to analyze it. We propose a solution to the saturation problem of this index based on our statistical framework. We investigate the relationship of this index with the ratio vegetation index (RVI) by C. F. Jordan (1969), another popular measure. Using the established statistical framework, we introduce new vegetation indices using blue and green bands in addition to the red and the near-infrared.
Keywords :
data analysis; image processing; remote sensing; statistical analysis; NDVI; RVI; airborne images; formal statistical framework; linearized vegetation; normalized difference vegetation index; ratio vegetation index; satellite images; saturation problem; vegetation density; vegetation indices; Covariance matrix; Laboratories; Principal component analysis; Random variables; Remote sensing; Satellites; Signal analysis; State estimation; Stress; Vegetation mapping;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International
Print_ISBN :
0-7803-7929-2
DOI :
10.1109/IGARSS.2003.1293985
