Accuracy assessment of linear spectral mixture model due to terrain undulation

2008 ◽  
Author(s):  
Tianxing Wang ◽  
Songlin Chen ◽  
Ya Ma
Keyword(s):  
Mixture Model ◽  
Accuracy Assessment ◽  
Spectral Mixture

scholarly journals Wetland Mapping Using HJ-1A/B Hyperspectral Images and an Adaptive Sparse Constrained Least Squares Linear Spectral Mixture Model

2021 ◽  
Vol 13 (4) ◽  
pp. 751
Author(s):  
Xiaodong Na ◽  
Xingmei Li ◽  
Wenliang Li ◽  
Changshan Wu
Keyword(s):  
Least Squares ◽  
Mixture Model ◽  
Least Squares Method ◽  
Accuracy Assessment ◽  
Spectral Unmixing ◽  
Hyperspectral Images ◽  
Permafrost Degradation ◽  
Constrained Least Squares ◽  
Vegetation Communities ◽  
Spectral Mixture

In this study, we proposed an adaptive sparse constrained least squares linear spectral mixture model (SCLS-LSMM) to map wetlands in a sophisticated scene. It includes three procedures: (1) estimating the abundance based on sparse constrained least squares method with all endmembers in the spectral library, (2) selecting “active” endmember combinations for each pixel based on the estimated abundances and (3) estimating abundances based on the linear spectral unmixing algorithm only with the adaptively selected endmember combinations. The performances of the proposed SCLS-LSMM on wetland vegetation communities mapping were compared with the traditional full constrained least squares linear spectral mixture model (FCLS-LSMM) using HJ-1A/B hyperspectral images. The accuracy assessment results showed that the proposed SCLS-LSMM obtained a significantly better performance with a systematic error (SE) of –0.014 and a root-mean-square error (RMSE) of 0.087 for Reed marsh, and a SE of 0.004 and a RMSE of 0.059 for Weedy meadow, compared with the traditional FCLS-LSMM. The proposed methods improved the unmixing accuracies of wetlands’ vegetation communities and have the potential to understand the process of wetlands’ degradation under the impacts of climate changes and permafrost degradation.

Linear spectral mixture model as a tool for monitoring deforestation and timber exploitation in the Brazilian Amazon

2003 ◽  
Author(s):  
Joao R. dos Santos ◽  
Yosio E. Shimabukuro ◽  
Valdete Duarte ◽  
Paulo Mauricio Lima de Alencastro Graea ◽  
Patricia Guedes da Silva
Keyword(s):  
Mixture Model ◽  
Brazilian Amazon ◽  
Spectral Mixture

Spectral Mixture Model Inspired Network Architectures for Hyperspectral Unmixing

2020 ◽  
Vol 58 (10) ◽  
pp. 7418-7434
Author(s):  
Yuntao Qian ◽  
Fengchao Xiong ◽  
Qipeng Qian ◽  
Jun Zhou
Keyword(s):  
Mixture Model ◽  
Network Architectures ◽  
Hyperspectral Unmixing ◽  
Spectral Mixture

Predicting water content using linear spectral mixture model on soil spectra

2013 ◽  
Vol 7 (1) ◽  
pp. 073539 ◽  
Author(s):  
Huan Li ◽  
Changkuan Zhang ◽  
Ying Zhang ◽  
Dong Zhang ◽  
Jay Gao ◽  
...  
Keyword(s):  
Water Content ◽  
Mixture Model ◽  
Spectral Mixture
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