Paper Info
Title
Hyperspectral indices and forest characteristics
Abstract
The quantification of forest characteristics at different scales is key to understanding how forest ecosystems function. Hyperspectral imagery may provide information to quantitatively estimate some biochemical (e.g. chlorophyll or nitrogen content), structural (e.g. leaf area index) or physiological (e.g. light use efficiency) forest characteristics at different scales, but this information is not easily retrievable. The simple reflectance index concept has been inherited from a long history of multispectral data analysis, and is commonly transposed to hyperspectral data. The design and use of such hyperspectral indices is questioned in this study.
Year
DOI
Venue
2012
10.1109/IGARSS.2012.6351971
Geoscience and Remote Sensing Symposium
Keywords
Field
DocType
vegetation,biochemical forest characteristic,forest characteristic quantification,forest ecosystems function,hyperspectral imagery,hyperspectral indices,multispectral data analysis,physiological forest characteristic,simple reflectance index concept,structural forest characteristic,calibration,hyperspectral,radiative transfer model,vegetation indices
Leaf area index,Vegetation,Computer science,Remote sensing,Hyperspectral imaging,Atmospheric radiative transfer codes,Forest ecology,Reflectivity,Multispectral data
Conference
ISSN
ISBN
Citations 
2153-6996 E-ISBN : 978-1-4673-1158-8
978-1-4673-1158-8
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Guerric le Maire1316.86
le Maire, G.2213.44