Detection of early plant stress responses in hyperspectral images-Reference-Cited by-同舟云学术

Detection of early plant stress responses in hyperspectral images

Published:2014-07 Issue: Volume:93 Page:98-111
ISSN:0924-2716
Container-title:ISPRS Journal of Photogrammetry and Remote Sensing
language:en
Short-container-title:ISPRS Journal of Photogrammetry and Remote Sensing

Author:

Behmann Jan,Steinrücken Jörg,Plümer Lutz

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference82 articles.

1. Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Süsstrunk, S., 2010. Slic Superpixels. Technical Report 149300, EPFL Technical Report No. 149300.

2. Categorical Data Analysis;Agresti,2002

3. Hyperspectral remote sensing of plant pigments;Blackburn;J. Exp. Bot.,2007

4. Plant productivity and environment;Boyer;Science,1982

5. On the relation between NDVI, fractional vegetation cover, and leaf area index;Carlson;Remote Sens. Environ.,1997

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