scholarly journals Clusters versus FPGAs for spectral mixture analysis-based lossy hyperspectral data compression

2008 ◽  
Author(s):  
Antonio J. Plaza
Keyword(s):  
Data Compression ◽  
Hyperspectral Data ◽  
Spectral Mixture Analysis ◽  
Mixture Analysis ◽  
Spectral Mixture

End-member identification and spectral mixture analysis of CRISM hyperspectral data: A case study on southwest Melas Chasma, Mars

2016 ◽  
Vol 121 (10) ◽  
pp. 2004-2036 ◽  
Author(s):  
Yang Liu ◽  
Timothy D. Glotch ◽  
Noel A. Scudder ◽  
Meredith L. Kraner ◽  
Thomas Condus ◽  
...  
Keyword(s):  
Hyperspectral Data ◽  
Spectral Mixture Analysis ◽  
Mixture Analysis ◽  
Spectral Mixture ◽  
Melas Chasma

scholarly journals Frost Damage Assessment in Wheat Using Spectral Mixture Analysis

2019 ◽  
Vol 11 (21) ◽  
pp. 2476 ◽  
Author(s):  
Glenn J. Fitzgerald ◽  
Eileen M. Perry ◽  
Ken C. Flower ◽  
J. Nikolaus Callow ◽  
Bryan Boruff ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Crop Protection ◽  
Frost Damage ◽  
Hyperspectral Data ◽  
Spectral Mixture Analysis ◽  
Mixture Analysis ◽  
Data Set ◽  
Spectral Libraries ◽  
Spectral Mixture

Frost damage to broadacre crops can cause up to an 85% loss in productivity. Although growers have few options for crop protection from frost, a rapid method for assessing frost-induced sterility would allow for timely management decisions (e.g., cutting for hay and altering marketing strategies). Spectral mixture analysis (SMA) has shown success in mapping landscape components and was used with hyperspectral data collected on the canopy, heads, and leaves of wheat at different sites to determine if this could quantify frost damage. Spectral libraries were assembled from canopy components collected from local field sites to generate spectral libraries for SMA from which a series of fraction sets was derived. The frost (Fr) fraction was then used to estimate final yield as a means of measuring frost damage. The best-fitting Fr fractions to yield were derived from the same data set as the source Fr spectra, and these ranged over R2 = 0.58–0.75 at the canopy scale. It was clear that spectral signatures need to be collected at scale to assess frost damage. While Fr fractions were able to estimate yield there was no “universal” endmember set from which a Fr fraction could be derived. The normalized difference vegetation index (NDVI) was not able to estimate frost damage consistently. Future work requires determining whether there is a “universal” set of endmembers and a minimum set of targeted wavebands that could lead to multispectral instruments for frost assessment for use in ground and aerial sensors.

Mapping two Eucalyptus subgenera using multiple endmember spectral mixture analysis and continuum-removed imaging spectrometry data

2011 ◽  
Vol 115 (5) ◽  
pp. 1115-1128 ◽  
Author(s):  
Kara N. Youngentob ◽  
Dar A. Roberts ◽  
Alex A. Held ◽  
Philip E. Dennison ◽  
Xiuping Jia ◽  
...  
Keyword(s):  
Spectral Mixture Analysis ◽  
Mixture Analysis ◽  
Imaging Spectrometry ◽  
Spectral Mixture
Sign in / Sign up

Export Citation Format

Share Document