Improving Porphyry Copper Prospectivity Mapping with Stacked Ensemble Machine Learning and Feature Contribution Analysis: A Case Study of the Eastern Sirjan 1:250,000 quadrangle map, Iran

Samiei, Mohammad Reza; Moradzadeh, Ali; Pahlavani, Parham; Ghezelbash, Reza

doi:10.5194/isprs-annals-X-4-W8-2025-661-2026

Articles | Volume X-4/W8-2025

https://doi.org/10.5194/isprs-annals-X-4-W8-2025-661-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/isprs-annals-X-4-W8-2025-661-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume X-4/W8-2025

29 May 2026

| 29 May 2026

Improving Porphyry Copper Prospectivity Mapping with Stacked Ensemble Machine Learning and Feature Contribution Analysis: A Case Study of the Eastern Sirjan 1:250,000 quadrangle map, Iran

Mohammad Reza Samiei, Ali Moradzadeh, Parham Pahlavani, and Reza Ghezelbash

Metrics will be available soon.

Latest update: 30 May 2026

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