AndalUnmixingRGB is a Sentinel-2 satellite digital RGB imagery enriched with environmental ancillary data and designed for blind spectral unmixing using deep learning. Generally, spectral unmixing involves two main tasks: spectral signature identification of different available land use/cover types in the analyzed hyperspectral or multispectral imagery (endmember identification task) and their respective proportions measurement (abundance estimation task).

DOI Link: 
10.21227/y355-9h30
Read more

Dataset Files

You must be an IEEE Dataport Subscriber to access these files. Subscribe now or login.

[1] Yassir Benhammou, José Rodríguez-Ortega, Domingo Alcaraz-Segura, Siham Tabik, "AndalUnmixingRGB: A dataset of Sentinel-2 RGB imagery acquired in Andalusia region of Spain, enriched with environmental ancillary data and annotated for blind Spectral Unmixing using Deep Learning (License CC BY 4.0)", IEEE Dataport, 2023. [Online]. Available: http://dx.doi.org/10.21227/y355-9h30. Accessed: Feb. 10, 2025.
@data{y355-9h30-23,
doi = {10.21227/y355-9h30},
url = {http://dx.doi.org/10.21227/y355-9h30},
author = {Yassir Benhammou; José Rodríguez-Ortega; Domingo Alcaraz-Segura; Siham Tabik },
publisher = {IEEE Dataport},
title = {AndalUnmixingRGB: A dataset of Sentinel-2 RGB imagery acquired in Andalusia region of Spain, enriched with environmental ancillary data and annotated for blind Spectral Unmixing using Deep Learning (License CC BY 4.0)},
year = {2023} }
TY - DATA
T1 - AndalUnmixingRGB: A dataset of Sentinel-2 RGB imagery acquired in Andalusia region of Spain, enriched with environmental ancillary data and annotated for blind Spectral Unmixing using Deep Learning (License CC BY 4.0)
AU - Yassir Benhammou; José Rodríguez-Ortega; Domingo Alcaraz-Segura; Siham Tabik
PY - 2023
PB - IEEE Dataport
UR - 10.21227/y355-9h30
ER -
Yassir Benhammou, José Rodríguez-Ortega, Domingo Alcaraz-Segura, Siham Tabik. (2023). AndalUnmixingRGB: A dataset of Sentinel-2 RGB imagery acquired in Andalusia region of Spain, enriched with environmental ancillary data and annotated for blind Spectral Unmixing using Deep Learning (License CC BY 4.0). IEEE Dataport. http://dx.doi.org/10.21227/y355-9h30
Yassir Benhammou, José Rodríguez-Ortega, Domingo Alcaraz-Segura, Siham Tabik, 2023. AndalUnmixingRGB: A dataset of Sentinel-2 RGB imagery acquired in Andalusia region of Spain, enriched with environmental ancillary data and annotated for blind Spectral Unmixing using Deep Learning (License CC BY 4.0). Available at: http://dx.doi.org/10.21227/y355-9h30.
Yassir Benhammou, José Rodríguez-Ortega, Domingo Alcaraz-Segura, Siham Tabik. (2023). "AndalUnmixingRGB: A dataset of Sentinel-2 RGB imagery acquired in Andalusia region of Spain, enriched with environmental ancillary data and annotated for blind Spectral Unmixing using Deep Learning (License CC BY 4.0)." Web.
1. Yassir Benhammou, José Rodríguez-Ortega, Domingo Alcaraz-Segura, Siham Tabik. AndalUnmixingRGB: A dataset of Sentinel-2 RGB imagery acquired in Andalusia region of Spain, enriched with environmental ancillary data and annotated for blind Spectral Unmixing using Deep Learning (License CC BY 4.0) [Internet]. IEEE Dataport; 2023. Available from : http://dx.doi.org/10.21227/y355-9h30
Yassir Benhammou, José Rodríguez-Ortega, Domingo Alcaraz-Segura, Siham Tabik. "AndalUnmixingRGB: A dataset of Sentinel-2 RGB imagery acquired in Andalusia region of Spain, enriched with environmental ancillary data and annotated for blind Spectral Unmixing using Deep Learning (License CC BY 4.0)." doi: 10.21227/y355-9h30