PRISMA hyperspectral data for lithological mapping in the Egyptian Eastern Desert: Evaluating the support vector machine, random forest, and XG boost machine learning algorithms-Reference-Cited by-同舟云学术

PRISMA hyperspectral data for lithological mapping in the Egyptian Eastern Desert: Evaluating the support vector machine, random forest, and XG boost machine learning algorithms

Published:2023-10 Issue: Volume:161 Page:105652
ISSN:0169-1368
Container-title:Ore Geology Reviews
language:en
Short-container-title:Ore Geology Reviews

Author:

Shebl Ali^ORCID,Abriha Dávid,Fahil Amr S.,El-Dokouny Hanna A.,Elrasheed Abdelmajeed A.,Csámer Árpád

Publisher

Elsevier BV

Subject

Economic Geology,Geochemistry and Petrology,Geology

Reference75 articles.

1. Effective delineation of rare metal-bearing granites from remote sensing data using machine learning methods: A case study from the Umm Naggat Area, Central Eastern Desert, Egypt;Abdelkader;Ore Geol. Rev.,2022

2. Exploration of IOCG mineralizations using integration of space-borne remote sensing data with airborne geophysical data;Abdolmaleki;Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci.,2020

3. New Generation Hyperspectral Sensors DESIS and PRISMA Provide Improved Agricultural Crop Classifications;Aneece;Photogramm. Eng. Remote Sensing,2022

4. Mapping Structurally Controlled Alterations Sparked by Hydrothermal Activity in the Fatira–Abu Zawal Area, Eastern Desert, Egypt;Badawi;Acta Geologica Sinica (Eng),2023

5. Application of PRISMA satellite hyperspectral imagery to mineral alteration mapping at Cuprite, Nevada, USA;Bedini;J. Hyperspectral Remote Sens.,2022

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1. Analysis of Devanur and Manamedu Ophiolite Complexes in SGT, India: A detailed examination employing remote sensing techniques and Laboratory Spectral Signature investigations;Remote Sensing Applications: Society and Environment;2024-11

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3. PRISMA vs. Landsat 9 in lithological mapping − a K-fold Cross-Validation implementation with Random Forest;The Egyptian Journal of Remote Sensing and Space Sciences;2024-09

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5. A review on hyperspectral imagery application for lithological mapping and mineral prospecting: Machine learning techniques and future prospects;Remote Sensing Applications: Society and Environment;2024-08