|
|
|
|
|
Giorgio Licciardi, Costantino Del Gaudio and Jocelyn Chanussot
Hyperspectral analysis is a well-established technique that can be suitably implemented in several application fields, including materials science. This approach allows us to deal with data samples containing spatial and spectral information at very high...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chang Huang, Yun Chen, Shiqiang Zhang, Linyi Li, Kaifang Shi and Rui Liu
Capturing the dynamics of a lake-water area using remotely sensed images has always been an essential task. Most of the fine spatial resolution data are unsuitable for this purpose because of their low temporal resolution and limited scene coverage. A Vi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jianhui Xu, Yi Zhao, Kaiwen Zhong, Huihua Ruan and Xulong Liu
Land surface characteristics, including soil type, terrain slope, and antecedent soil moisture, have significant impacts on surface runoff during heavy precipitation in highly urbanized areas. In this study, a Linear Spectral Mixture Analysis (LSMA) meth...
ver más
|
|
|
|
|
|
|
|
|
|
|
Uttam Kumar, Kumar S. Raja, Chiranjit Mukhopadhyay and T.V. Ramachandra
Signals acquired by sensors in the real world are non-linear combinations, requiring non-linear mixture models to describe the resultant mixture spectra for the endmember?s (pure pixel?s) distribution. This communication discusses inferring class fractio...
ver más
|
|
|
|
|
|