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Linearized Vegetation Indices

  • Cem Ünsalan
  • Kim L. Boyer
Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Abstract

Most remote sensing satellite sensors offer multispectral images besides panchromatic images. This multispectral information is extremely valuable to detect various objects in the image. In this book, we summarize the multispectral information via vegetation and shadow–water indices. In the following chapters, we benefit from these indices in land use classification and house and street network detection. In this chapter, we consider the popular vegetation index based on the above observations, the normalized difference vegetation index (NDVI). Although there have been many indices proposed in the literature, theNDVI remains one of the most popular in remote sensing applications. We first introduce a statistical framework for theNDVI. We then propose a solution to the nonlinearity (saturation) problem based on this statistical explanation. For completeness, we then apply the same framework to the 3D and 4D feature spaces of blue, green, red, and near-infrared bands.

Keywords

Normalize Difference Vegetation Index Vegetation Index Leaf Area Index Statistical Framework Multispectral Image 
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-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Electrical and Electronics EngineeringYeditepe UniversityKayisdagiTurkey
  2. 2.Dept. Electrical, Comp. & Systems Eng.Rensselaer Polytechnic InstituteTroyUSA

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