LANDSLIDE DETECTION AND MONITORING TECHNIQUES: A BIBLIOMETRIC ANALYSIS AND FUTURE DIRECTIONS

The devastating consequences of landslides demand rigorous assessment and effective management strategies to minimise risks. In this context, landslide detection and monitoring are crucial in identifying potential hazards and implementing proactive mitigation measures. This study uses the Scopus database to present a bibliometric analysis of 1,112 peer-reviewed journal articles on landslide detection and monitoring techniques published between 2002 and 2022. The analysis reveals a remarkable surge in publications, from 4 in 2002 to 180 in 2022, with the last five years (2018-2022) accounting for over 60% of the total publications. Over 3,259 unique researchers from 75 countries contributed to this field, with a significant portion originating from Asia, Europe, and North America. China and Italy emerged as the leading countries, producing over half of the articles. Nicola Casagli, from Italy, authored the most publications and garnered the highest number of citations. Remote Sensing emerged as the most preferred journal for authors, while Landslides garnered the highest total citations, and Geomorphology has the most normalised citations per article. The Chinese Academy of Sciences, China University of Geosciences, and the University of Florence in Italy were the most productive research institutions. The Natural Science Foundation of China (NSFC) emerged as the top funding agency. “Landslide”, “landslide monitoring”, and “early warning systems” were the top three most frequently used keywords. Keyword analysis identified landslide detection and monitoring advancements in remote sensing, analytical methods, and in-situ techniques. Co-occurrence analysis of trending research terms highlighted three distinct thematic clusters: remotely sensed data with machine learning and image analysis for landslide detection, field instrumentation for continuous deformation monitoring, and development of early warning systems for landslide hazard assessment and mitigation.

Authors

Publication Details

Journal
Suranaree Journal of Science and Technology
Published
2024-10-28
DOI
https://doi.org/10.55766/sujst-2024-04-e03362
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

LANDSLIDE DETECTION AND MONITORING TECHNIQUES: A BIBLIOMETRIC ANALYSIS AND FUTURE DIRECTIONS

Hassan Khan, Afiqah Ismail, Ahmad Safuan A. Rashid
Suranaree Journal of Science and Technology
Landslides and related hazards
article

LANDSLIDE DETECTION AND MONITORING TECHNIQUES: A BIBLIOMETRIC ANALYSIS AND FUTURE DIRECTIONS

Hassan Khan, Afiqah Ismail, Ahmad Safuan A. Rashid
article en

Abstract

The devastating consequences of landslides demand rigorous assessment and effective management strategies to minimise risks. In this context, landslide detection and monitoring are crucial in identifying potential hazards and implementing proactive mitigation measures. This study uses the Scopus database to present a bibliometric analysis of 1,112 peer-reviewed journal articles on landslide detection and monitoring techniques published between 2002 and 2022. The analysis reveals a remarkable surge in publications, from 4 in 2002 to 180 in 2022, with the last five years (2018-2022) accounting for over 60% of the total publications. Over 3,259 unique researchers from 75 countries contributed to this field, with a significant portion originating from Asia, Europe, and North America. China and Italy emerged as the leading countries, producing over half of the articles. Nicola Casagli, from Italy, authored the most publications and garnered the highest number of citations. Remote Sensing emerged as the most preferred journal for authors, while Landslides garnered the highest total citations, and Geomorphology has the most normalised citations per article. The Chinese Academy of Sciences, China University of Geosciences, and the University of Florence in Italy were the most productive research institutions. The Natural Science Foundation of China (NSFC) emerged as the top funding agency. “Landslide”, “landslide monitoring”, and “early warning systems” were the top three most frequently used keywords. Keyword analysis identified landslide detection and monitoring advancements in remote sensing, analytical methods, and in-situ techniques. Co-occurrence analysis of trending research terms highlighted three distinct thematic clusters: remotely sensed data with machine learning and image analysis for landslide detection, field instrumentation for continuous deformation monitoring, and development of early warning systems for landslide hazard assessment and mitigation.

Suranaree Journal of Science and TechnologyVol. 31(4)
Openalex Percentile: Top 72%
Landslides and related hazards
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

LANDSLIDE DETECTION AND MONITORING TECHNIQUES: A BIBLIOMETRIC ANALYSIS AND FUTURE DIRECTIONS — Hassan Khan, Afiqah Ismail, et al. · Suranaree Journal of Science and Technology (2024) | TGRS Research Map | TGRS