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Editorial

Landslide Research: State of the Art and Innovations

Department of Natural and Environmental Risks, Regional Agency for Environmental Protection of Piemonte (ARPA Piemonte), Via Pio VII 9, 10135 Torino, Italy
GeoHazards 2026, 7(2), 61; https://doi.org/10.3390/geohazards7020061
Submission received: 11 May 2026 / Accepted: 19 May 2026 / Published: 20 May 2026
(This article belongs to the Special Issue Landslide Research: State of the Art and Innovations)

Abstract

Landslides have always been one of the most harmful geological hazards in terms of human lives and economic loss worldwide. Landslides can develop in both continental and underwater environments characterized by the presence of slopes with devastating consequences on structures, infrastructure, economic activities, and communities. They can also occur in flat or sub-flat areas, such as sinkholes, a particularly insidious phenomenon in densely urbanized areas. For this reason, landslide research is a priority and requires a wide range of knowledge and expertise to describe them, characterize them, and address the related risk prevention and mitigation aspects due to the wide variety of phenomena in terms of typology and triggering conditions. The purpose of this Special Issue is to collect and group together quality scientific papers on these research fields and derive practical/operational applications. The topics related to this Special Issue therefore concern the innovative methodologies to achieve landslide identification, classification, characterization, and hazard/risk evaluation through geomorphological field surveys and studies; remote sensing applications; Geographic Information System (GIS) data mapping, processing and representation; the analysis of predisposing and triggering factors; landslide early warning system implementation; and the impact of current and future climate change scenarios on the evolution of these phenomena.
Keywords: slope processes; mass movements; natural hazards; rainfall thresholds; debris flows; machine learning; artificial intelligence; early warning systems; climate change; remote sensing; near-surface geophysics slope processes; mass movements; natural hazards; rainfall thresholds; debris flows; machine learning; artificial intelligence; early warning systems; climate change; remote sensing; near-surface geophysics
Graphical Abstract

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MDPI and ACS Style

Tiranti, D. Landslide Research: State of the Art and Innovations. GeoHazards 2026, 7, 61. https://doi.org/10.3390/geohazards7020061

AMA Style

Tiranti D. Landslide Research: State of the Art and Innovations. GeoHazards. 2026; 7(2):61. https://doi.org/10.3390/geohazards7020061

Chicago/Turabian Style

Tiranti, Davide. 2026. "Landslide Research: State of the Art and Innovations" GeoHazards 7, no. 2: 61. https://doi.org/10.3390/geohazards7020061

APA Style

Tiranti, D. (2026). Landslide Research: State of the Art and Innovations. GeoHazards, 7(2), 61. https://doi.org/10.3390/geohazards7020061

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