Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community
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 …
top in numerous areas, namely computer vision (CV), speech recognition, and natural …
Crop nitrogen monitoring: Recent progress and principal developments in the context of imaging spectroscopy missions
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 …
management of N therefore is a pre-requisite for modern agriculture. Continuous satellite …
An augmented linear mixing model to address spectral variability for hyperspectral unmixing
Hyperspectral imagery collected from airborne or satellite sources inevitably suffers from
spectral variability, making it difficult for spectral unmixing to accurately estimate abundance …
spectral variability, making it difficult for spectral unmixing to accurately estimate abundance …
Remote sensing of terrestrial plant biodiversity
Biodiversity is essential to healthy ecosystem function, influencing productivity and
resilience to disturbance. Biodiversity loss endangers essential ecosystem services and …
resilience to disturbance. Biodiversity loss endangers essential ecosystem services and …
Developments in Landsat land cover classification methods: A review
D Phiri, J Morgenroth - Remote Sensing, 2017 - mdpi.com
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 …
developed from Earth observation satellites. The last four decades were marked by different …
Spectral variability in hyperspectral data unmixing: A comprehensive review
The spectral signatures of the materials contained in hyperspectral images, also called
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …
A comprehensive review of remote sensing platforms, sensors, and applications in nut crops
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 …
among the main substitutes for meat, with a growing share of the food basket in the United …
Hyperspectral unmixing based on nonnegative matrix factorization: A comprehensive review
Hyperspectral unmixing has been an important technique that estimates a set of
endmembers and their corresponding abundances from a hyperspectral image (HSI) …
endmembers and their corresponding abundances from a hyperspectral image (HSI) …
A review of nonlinear hyperspectral unmixing methods
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 …
variety of techniques based on this model has been proposed to obtain endmembers and …
Review of ground and aerial methods for vegetation cover fraction (fCover) and related quantities estimation: definitions, advances, challenges, and future …
Vegetation cover fraction (fCover) and related quantities are basic yet critical vegetation
structure variables in various disciplines and applications. Ground-and aerial-based …
structure variables in various disciplines and applications. Ground-and aerial-based …