Big Earth data processing using machine learning for integrated mapping of the dead sea fault, Jordan
In this research, an integrated framework on the big Earth data analysis has been developed in the context of the geomorphology of Jordan. The research explores the correlation between several thematic datasets, including machine learning and multidisciplinary geospatial data. GIS mapping is widely...
Saved in:
Main Author: | Polina Lemenkova |
---|---|
Format: | Article |
Language: | English |
Published: |
Faculty of Forestry, University of Banja Luka
2021-12-01
|
Series: | Glasnik Šumarskog Fakulteta Univerziteta u Banjoj Luci |
Subjects: | |
Online Access: | http://filozofskopisanje.com/ojs_test/index.php/gsfbl/article/view/242 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Machine learning methods of satellite image analysis for mapping geologic landforms in Niger: A comparison of the Aïr mountains, Niger River basin and Djado Plateau
by: Lemenkova Polina
Published: (2024-01-01) -
Estimating Seafloor Topography of the South China Sea Using SWOT Wide-Swath Altimetry Data
by: Fengshun Zhu, et al.
Published: (2025-01-01) -
The relevance of the Dead Sea Scrolls for New Testament interpretation with a bibliographical appendix
by: J. Frey
Published: (2003-12-01) -
GIS-Driven mineral exploration: Enhancing geological insight through aeromagnetic integration
by: Benyas Kawtar, et al.
Published: (2025-01-01) -
Function of Simile in Symphony “The Dead”
by: Alireza Asadi, et al.
Published: (2019-06-01)