Fifty years of geomorphology research: a topic modeling analysis of global trends (1975-2025)
EARTH SCIENCE INFORMATICS, cilt.19, sa.11, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 19 Sayı: 11
- Basım Tarihi: 2026
- Doi Numarası: 10.1007/s12145-026-02253-0
- Dergi Adı: EARTH SCIENCE INFORMATICS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Geobase, INSPEC, Academic Search Ultimate (EBSCO), Natural Science Collection (ProQuest), Earth, Atmospheric, & Aquatic Science Collection (ProQuest), Technology Collection (ProQuest)
- Hatay Mustafa Kemal Üniversitesi Adresli: Evet
Özet
This study offers a topic modeling of geomorphology based research from 1975 to 2025 using the Web of Science (WoS) and Scopus databases. Given its scope, this study represents one of the most comprehensive machine learning based topic modeling analyses of the geomorphology literature to date. The study used the Orange Data Mining software, with Latent Dirichlet Allocation (LDA) for topic modeling and Hierarchical Clustering for thematic categorization. 30,397 articles were analyzed. The results identified 14 main topics. Among these, Fluvial Geomorphology, Geomorphological Analysis, and Modeling were the most extensively studied. Conversely, Coastal Geomorphology, Glacial Geomorphology, and Mass Movement are among the least represented categories within the geomorphology labeled corpus. Interestingly, Karst Geomorphology, which has been actively studied from the past to the present, also ranks among the least represented topics in the literature. The increased focus on certain topics coincides with challenges related to global climate change and natural disasters, as well as concerns over rising temperatures and drought. As a text mining study, however, our analysis treats these as cooccurring contextual factors rather than established causal drivers. Additionally, modern technological advancements, including high resolution data, orthomosaic imagery, satellite data, and surface modeling techniques, have played a key role in this shift. From this perspective, geomorphology continues to contribute significantly to understanding hydrometeorological and geological disasters, accounting for both morphological processes and human impacts in the context of global climate change.