Evolution and State-of-the-Art Technologies for Landslide Geospatial Monitoring: Classification, Method Suitability, and Monitoring Design Framework

Geospatial monitoring is crucial for landslide research and hazard mitigation. This paper provides a comprehensive overview of contemporary landslide monitoring methods and lays the groundwork for a unified monitoring framework. An in-depth bibliometric analysis and critical review of state-of-the-art approaches developed over the past decade are presented. The study proposes a new classification and systematization of geospatial monitoring methods based on dimensionality (1D, 2D, and 3D) and referencing approach (absolute or relative). The reviewed methods include geodetic techniques, photogrammetry, laser scanning, global satellite navigation systems, UAVs, radar interferometry, and various sensors. The operational characteristics, advantages, and limitations of the existing methods are analyzed with respect to monitoring accuracy, spatial coverage, temporal resolution, and applicability to different deformation conditions. A comparative analysis and systematization of monitoring methods according to landslide velocity classes are presented. This framework links achievable observation accuracy and monitoring frequency to landslide dynamics. Based on the analysis, a refined workflow for geospatial landslide monitoring is proposed. The workflow integrates monitoring design, observation network configuration, data integration, statistical analysis, and forecasting stages. The analysis indicates that effective landslide monitoring requires integrated multi-sensor systems. Future developments are expected to focus on geospatial and non-geospatial data integration, monitoring automation, and next-generation monitoring system design.

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Publication Details

Journal
Remote Sensing
Published
2026-07-01
DOI
https://doi.org/10.3390/rs18132127
Primary Topic
Landslides and related hazards
Type
article
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article

Evolution and State-of-the-Art Technologies for Landslide Geospatial Monitoring: Classification, Method Suitability, and Monitoring Design Framework

Md Masudur Rahman, Anzhelika Kamza, Роман Володимирович Шульц, Muhammad Usman et al.
Remote Sensing
Landslides and related hazards
article

Evolution and State-of-the-Art Technologies for Landslide Geospatial Monitoring: Classification, Method Suitability, and Monitoring Design Framework

Md Masudur Rahman, Anzhelika Kamza, Роман Володимирович Шульц, Muhammad Usman, Elmira Orynbassarova, Ф.А. Илиуф, Saniya Beisenbayeva
article en

Abstract

Geospatial monitoring is crucial for landslide research and hazard mitigation. This paper provides a comprehensive overview of contemporary landslide monitoring methods and lays the groundwork for a unified monitoring framework. An in-depth bibliometric analysis and critical review of state-of-the-art approaches developed over the past decade are presented. The study proposes a new classification and systematization of geospatial monitoring methods based on dimensionality (1D, 2D, and 3D) and referencing approach (absolute or relative). The reviewed methods include geodetic techniques, photogrammetry, laser scanning, global satellite navigation systems, UAVs, radar interferometry, and various sensors. The operational characteristics, advantages, and limitations of the existing methods are analyzed with respect to monitoring accuracy, spatial coverage, temporal resolution, and applicability to different deformation conditions. A comparative analysis and systematization of monitoring methods according to landslide velocity classes are presented. This framework links achievable observation accuracy and monitoring frequency to landslide dynamics. Based on the analysis, a refined workflow for geospatial landslide monitoring is proposed. The workflow integrates monitoring design, observation network configuration, data integration, statistical analysis, and forecasting stages. The analysis indicates that effective landslide monitoring requires integrated multi-sensor systems. Future developments are expected to focus on geospatial and non-geospatial data integration, monitoring automation, and next-generation monitoring system design.

Remote SensingVol. 18(13)
King Fahd University of Petroleum and Minerals (SA), Satbayev University (KZ), Pabna University of Science and Technology (BD)
Openalex Percentile: Top 5%
Landslides and related hazards
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