Nitrogen (N) is considered as one of the most important plant macronutrients and proper
management of N therefore is a pre-requisite for modern agriculture. Continuous satellite …

In recent years, deep learning (DL), a rebranding of neural networks (NNs), has risen to the
top in numerous areas, namely computer vision (CV), speech recognition, and natural …

Hyperspectral imagery collected from airborne or satellite sources inevitably suffers from
spectral variability, making it difficult for spectral unmixing to accurately estimate abundance …

Biodiversity is essential to healthy ecosystem function, influencing productivity and
resilience to disturbance. Biodiversity loss endangers essential ecosystem services and …

Vegetation cover fraction (fCover) and related quantities are basic yet critical vegetation
structure variables in various disciplines and applications. Ground-and aerial-based …

Background Due to their high protein content, nuts (almond, walnut, and pistachio) are
among the main substitutes for meat, with a growing share of the food basket in the United …

Land cover classification of Landsat images is one of the most important applications
developed from Earth observation satellites. The last four decades were marked by different …

Hyperspectral unmixing has been an important technique that estimates a set of
endmembers and their corresponding abundances from a hyperspectral image (HSI) …

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

In hyperspectral unmixing, the prevalent model used is the linear mixing model, and a large
variety of techniques based on this model has been proposed to obtain endmembers and …