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 …

Influence of atmospheric modeling on spectral target detection through forward modeling approach in multi-platform remote sensing data

SS Jha, RR Nidamanuri, EJ Ientilucci - ISPRS Journal of Photogrammetry …, 2022 - Elsevier
Identifying objects or pixels of interest that are few in numbers and sparsely populated in
imagery is referred to as target detection. Traditionally, the inverse modeling (IM) approach …

The potential for Landsat-based bathymetry in Canada

A Knudby, SK Ahmad, C Ilori - Canadian Journal of Remote …, 2016 - Taylor & Francis
Accurate bathymetric information is fundamental to safe maritime navigation and
infrastructure development in the coastal zone, but it is expensive to acquire with traditional …

Multi-temporal RapidEye Tasselled Cap data for land cover classification

C Raab, B Tonn, M Meißner, N Balkenhol… - European Journal of …, 2019 - Taylor & Francis
Land cover map** can be seen as a key element to understand the spatial distribution of
habitats and thus to sustainable management of natural resources. Multi-temporal remote …

Evaluation of multi-temporal and multi-sensor atmospheric correction strategies for land-cover accounting and monitoring in Ireland

C Raab, B Barrett, F Cawkwell, S Green - Remote Sensing Letters, 2015 - Taylor & Francis
Accurate atmospheric correction is an important preprocessing step for studies of multi-
temporal land-cover map** using optical satellite data. Model-based surface reflectance …

Pre-processing of remotely sensed imagery

P Bunting - The Roles of Remote Sensing in Nature Conservation …, 2017 - Springer
A common obstacle to the use of remote sensing data for nature conservation is the difficulty
in obtaining or generating data that are pre-processed to a standard that gives confidence in …

Spectral variability in hyperspectral unmixing: Multiscale, tensor, and neural network-based approaches

RA Borsoi - 2021 - theses.hal.science
The spectral signatures of the materials contained in hyperspectral images, also called
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …

[PERNYATAAN][C] Introduction to ARCSI for generating Analysis Ready Data (ARD)

P Bunting - 2017 - ACSEM/Aberystwyth University …