Title
Designing optimal spectral indexes for remote sensing applications
Abstract
Satellite remote sensing data constitute a significant potential source of information on our environment, provided they can be adequately interpreted. Vegetation indexes, a subset of the class of spectral indexes, represent one of the most commonly used approaches to analyze data in the optical domain. An optimal spectral index is very sensitive to the desired information (e.g. the amount of vegetation), and as insensitive as possible to perturbing factors (such as soil color changes or atmospheric effects). Since both the desired signal and the perturbing factors vary spectrally, and since the instruments themselves only provide data for particular spectral bands, optimal indexes should be designed for specific applications and particular instruments. This paper describes a rational approach to the design of an optimal index to estimate vegetation properties on the basis of the red and near-infrared reflectances of the AVHRR instrument, taking into account the perturbing effects of soil brightness changes, atmospheric absorption and scattering. The rationale behind the Global Environment Monitoring index (GEMI) is explained, and this index is proposed as an alternative to the Normalized Difference Vegetation Index (NDVI) for global applications. The techniques described here are generally applicable to any multispectral sensor and application
Year
DOI
Venue
1996
10.1109/36.536541
Geoscience and Remote Sensing, IEEE Transactions
Keywords
Field
DocType
geophysical techniques,infrared imaging,remote sensing,AVHRR,GEMI,Global Environment Monitoring index,IR imaging,NDVI,Normalized Difference Vegetation Index,geophysical measurement technique,infrared reflectance,multispectral remote sensing,optical imaging,optimal spectral index,satellite remote sensing,vegetation index,vegetation mapping,visible region
Vegetation,Spectral index,Remote sensing,Multispectral image,Remote sensing application,Normalized Difference Vegetation Index,Multispectral pattern recognition,Spectral bands,Brightness,Mathematics
Journal
Volume
Issue
ISSN
34
5
0196-2892
Citations 
PageRank 
References 
23
11.08
1
Authors
2
Name
Order
Citations
PageRank
Michel M. Verstraete129895.50
B. Pinty211732.67