The spectral signatures of the materials contained in hyperspectral images, also called
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …

Owing to the rapid development of sensor technology, hyperspectral (HS) remote sensing
(RS) imaging has provided a significant amount of spatial and spectral information for the …

Normalized difference vegetation index (NDVI) of highly dense vegetation (NDVI v) and bare
soil (NDVI s), identified as the key parameters for Fractional Vegetation Cover (FVC) …

Hyperspectral unmixing while considering endmember variability is usually performed by
the normal compositional model, where the endmembers for each pixel are assumed to be …

Bamboo forest has great potential in climate change mitigation. However, the spatiotemporal
pattern of carbon storage of global bamboo forest is still cannot be accurately estimated …

The vegetation index-based (VI-based) mixture model is widely used to derive green
fractional vegetation cover (FVC) from remotely sensed data. Two critical parameters of the …

Sparse hyperspectral unmixing has attracted increasing investigations during the past
decade. Recent research has indicated that library pruning algorithms can significantly …

In this paper, we consider the problem of unmixing a time series of hyperspectral images.
We propose a dynamical model based on linear mixing processes at each time instant. The …

Spectral variability is one of the major issues when conducting hyperspectral unmixing.
Within a given image composed of some elementary materials (herein referred to as …

Hyperspectral images (HSIs) contain many levels of spatial structures, and thus, feature
extraction techniques have been broadly studied in hyperspectral data processing to mine …