Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community

JE Ball, DT Anderson, CS Chan - Journal of applied remote …, 2017 - spiedigitallibrary.org
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 …

Crop nitrogen monitoring: Recent progress and principal developments in the context of imaging spectroscopy missions

K Berger, J Verrelst, JB Féret, Z Wang… - Remote Sensing of …, 2020 - Elsevier
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 …

An augmented linear mixing model to address spectral variability for hyperspectral unmixing

D Hong, N Yokoya, J Chanussot… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Hyperspectral imagery collected from airborne or satellite sources inevitably suffers from
spectral variability, making it difficult for spectral unmixing to accurately estimate abundance …

Remote sensing of terrestrial plant biodiversity

R Wang, JA Gamon - Remote Sensing of Environment, 2019 - Elsevier
Biodiversity is essential to healthy ecosystem function, influencing productivity 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 …

Spectral variability in hyperspectral data unmixing: A comprehensive review

RA Borsoi, T Imbiriba, JCM Bermudez… - … and remote sensing …, 2021 - ieeexplore.ieee.org
The spectral signatures of the materials contained in hyperspectral images, also called
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …

A comprehensive review of remote sensing platforms, sensors, and applications in nut crops

H Jafarbiglu, A Pourreza - Computers and Electronics in Agriculture, 2022 - Elsevier
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 …

Hyperspectral unmixing based on nonnegative matrix factorization: A comprehensive review

XR Feng, HC Li, R Wang, Q Du, X Jia… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Hyperspectral unmixing has been an important technique that estimates a set of
endmembers and their corresponding abundances from a hyperspectral image (HSI) …

A review of nonlinear hyperspectral unmixing methods

R Heylen, M Parente, P Gader - IEEE Journal of Selected …, 2014 - ieeexplore.ieee.org
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 …

Review of ground and aerial methods for vegetation cover fraction (fCover) and related quantities estimation: definitions, advances, challenges, and future …

L Li, X Mu, H Jiang, F Chianucci, R Hu, W Song… - ISPRS Journal of …, 2023 - Elsevier
Vegetation cover fraction (fCover) and related quantities are basic yet critical vegetation
structure variables in various disciplines and applications. Ground-and aerial-based …