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Dokumenttyp
Journal Article

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85162199358
WOS Core Collection: WOS:001006363300001

Interne Identnummern
RWTH-2023-05053
Datensatz-ID: 957986

Beteiligte Länder
France, Germany

Lizenzstatus der Zeitschrift

 GO


Related:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Dissertation / PhD Thesis  ;  ;
Unlocking pattern extraction from geospatial big data - methodological innovations in remote sensing and geospatial analysis for environmental and geoarchaeological research
Aachen : RWTH Aachen University 1 Online-Ressource : Illustrationen () [10.18154/RWTH-2024-00528] = Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2024  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS


Medline ; Creative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0 ; OpenAccess ; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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The record appears in these collections:
Document types > Articles > Journal Articles
Faculty of Georesources and Materials Engineering (Fac.5) > Division of Earth Sciences and Geography
Faculty of Civil Engineering (Fac.3)
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 Record created 2023-05-08, last modified 2025-10-09


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