Results 191 to 200 of about 1,373 (228)

Ecosystem metabolism and nitrogen budget of a glacial Fjord in the Arctic. [PDF]

Sci Rep
Duarte P, Castro de la Guardia L, Assmy P, Wold A, Fransson A, Chierici M, Bailey A, Hodson A, Alexander A, Magalhães C, Gabrielsen GW, Albretsen J, Frank L, Tripathy SC, Smerdou C, Gordillo FJL, Cobos P, Velázquez D, Convey P, De Rovere F, Hop H.   +20 more
europepmc   +1 more source

Coupling observational methods and the DayCent model to improve examinations of N₂O production pathways. [PDF]

Nutr Cycl Agroecosyst
Rainford SK, Havsteen JC, Mohn J, Ammann C, Keel SG.   +4 more
europepmc   +1 more source

Probabilistic Generative Model for Hyperspectral Unmixing Accounting for Endmember Variability

IEEE Transactions on Geoscience and Remote Sensing, 2022
The complex nature of hyperspectral images makes the analysis of spectral signatures a challenging task in remote sensing. For quantitative analysis, spectral unmixing is a well-established and effective tool to analyze the spectra and spatial ...
Shuaikai Shi, Min Zhao, Yoann Altmann
exaly   +3 more sources

Sum-Product Unmixing for Hyperspectral Analysis With Endmember Variability

IEEE Geoscience and Remote Sensing Letters, 2018
Models of endmember variability capture the notion that multiple spectra may represent a single class or material, and while these models are physically realistic, they often give rise to excessive computational complexity during the spectral unmixing process.
Charan Puladas, Katie Hossler, Joshua N. Ash   +2 more
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A Novel Endmember Bundle Extraction and Clustering Approach for Capturing Spectral Variability Within Endmember Classes

IEEE Transactions on Geoscience and Remote Sensing, 2016
Spectral variability, unrelated to the purity of endmembers, can change the geometry of the dataspace and affect conventional methods used to identify endmembers. Several methods have been developed to identify and extract endmember bundles representing the spectral variability within each endmember class.
Tatsumi Uezato, Richard J Murphy, Arman Melkumyan   +2 more
exaly   +2 more sources

Endmember variability in Spectral Mixture Analysis: A review

Remote Sensing of Environment, 2011
The composite nature of remotely sensed spectral information often masks diagnostic spectral features and hampers the detailed identification and mapping of targeted constituents of the earth's surface. Spectral Mixture Analysis (SMA) is a well established and effective technique to address this mixture problem.
Ben Somers, Gregory P Asner, Laurent Tits   +2 more
exaly   +2 more sources

Endmember orthonormal mapping in hyperspectral mixture analysis to address endmember variability

Earth Science Informatics, 2016
Spectral unmixing estimates the abundance of each endmember at every pixel of a hyperspectral image. Each material in traditional unmixing algorithms is represented through a constant spectral signature. However, endmember variability always exists due to environmental, atmospheric, and temporal conditions, which leads to poor accuracy of the estimated
Ali Jafari, Reza Safabakhsh, Mohammad Mehdi Ebadzadeh   +2 more
exaly   +2 more sources

Endmember extraction analysis considering endmember variability

2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013
In recent years, several kinds of endmember extraction algorithms have been proposed from hyperspectral data set which extracts/selects one single standard endmember spectrum for each existing endmember class or scene component. In this article, endmember variability is considered to the mixture spectrum analysis by representing each endmember by a set
Mingming Xu, Liangpei Zhang, Bo Du
exaly   +2 more sources

Endmember Variability in Hyperspectral Analysis: Addressing Spectral Variability During Spectral Unmixing

IEEE Signal Processing Magazine, 2014
Variable illumination and environmental, atmospheric, and temporal conditions cause the measured spectral signature for a material to vary within hyperspectral imagery. By ignoring these variations, errors are introduced and propagated throughout hyperspectral image analysis.
Alina Zare, K C Ho
exaly   +2 more sources

Bayesian Unmixing of Hyperspectral Image Sequence With Composite Priors for Abundance and Endmember Variability

IEEE Transactions on Geoscience and Remote Sensing, 2022
International audienceA hyperspectral image sequence can be obtained at different time in the same region from a hyperspectral sensor. The environmental change usually leads to variation in endmember reflectance, which has an important influence on ...
Hongyi Liu, Zebin Wu, Qian Du
exaly   +2 more sources