Improving Remote Species Identification through Efficient Training Data Collection

Improving Remote Species Identification through Efficient Training Data Collection

Plant species identification and mapping based on remotely-sensed spectral signatures is a challenging task with the potential to contribute enormously to ecological studies. Success in this task rests upon the appropriate collection and use of costly field-based training data, and researchers are...

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Bibliographic Details
Main Authors: Claire A. Baldeck, Gregory P. Asner
Format: Article
Language:English
Published: MDPI AG 2014-03-01
Series:Remote Sensing
Subjects:
biodiversity
Carnegie Airborne Observatory
hyperspectral
imaging spectroscopy
species identification
support vector machine
Online Access:http://www.mdpi.com/2072-4292/6/4/2682

Internet

http://www.mdpi.com/2072-4292/6/4/2682

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