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Visualization analysis of rainfall-induced landslides hazards based on remote sensing and geographic information system-an overview.

Authors :
Yang, Zhengli
Lu, Heng
Zhang, Zhijie
Liu, Chao
Nie, Ruihua
Zhang, Wanchang
Fan, Gang
Chen, Chen
Ma, Lei
Dai, Xiaoai
Zhang, Min
Zhang, Donghui
Source :
International Journal of Digital Earth. Jan2023, Vol. 16 Issue 1, p2374-2402. 29p.
Publication Year :
2023

Abstract

In recent years, RS and GIS technologies have played an increasingly important role in various aspects of rainfall induced landslide research. In order to systematically understand their application situation, this paper extensively used various visualization analysis technologies for in-depth analysis of 1,161 documents collected by the WOS data platform in the past 27 years by combining quantitative and qualitative methods. Then, this article focuses on sub domain analysis from four aspects: landslide detection and monitoring, prediction models, sensitivity mapping, and risk assessment. The study found that the number of literature in this field has steadily increased and is expected to continue to rise. This literature review has attracted widespread attention from the academic community, but it is challenging to meet research needs. Frequent and effective cooperation between countries, institutions, and authors is very beneficial for promoting progress in this field. The future development direction is a new intelligent hybrid model that integrates multiple research methods. This study can provide researchers in this field with the core research force, hot topic evolution, and future development trends of future rainfall-induced landslides and contribute to landslide prevention and control decision-making and achieving the United Nations'sustainable development goals. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17538947
Volume :
16
Issue :
1
Database :
Academic Search Index
Journal :
International Journal of Digital Earth
Publication Type :
Academic Journal
Accession number :
173778937
Full Text :
https://doi.org/10.1080/17538947.2023.2229797