Optimizing Land Use Classification Using Google Earth Engine: A Comparative Analysis of Machine Learning Algorithms

Sultan, Mubbashra; Saleous, Nazmi; Issa, Salem; Dahy, Basam; Sami, Mabrouk

doi:https://doi.org/10.5194/isprs-annals-X-G-2025-863-2025

Articles | Volume X-G-2025

https://doi.org/10.5194/isprs-annals-X-G-2025-863-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/isprs-annals-X-G-2025-863-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume X-G-2025

14 Jul 2025

| 14 Jul 2025

Optimizing Land Use Classification Using Google Earth Engine: A Comparative Analysis of Machine Learning Algorithms

Mubbashra Sultan, Nazmi Saleous, Salem Issa, Basam Dahy, and Mabrouk Sami

Metrics will be available soon.

Latest update: 14 Jul 2025

The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.

Useful Links

Useful External Links

Our Contact

ISPRS
c/o
Leibniz University Hannover
Institute of Photogrammetry and GeoInformation
Nienburger Str. 1
D-30167 Hannover
GERMANY
Email: isprs-sg@isprs.org