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Background <p>Landslide inventories are essential tools for emergency response, hazard assessment, and susceptibility mapping, especially following very hazardous events. On 15 September 2022, an extreme rainfall event affected the Misa River basin in the Marche region, Central-Eastern Italy, resulting in widespread hydrogeomorphological instability, including numerous landslides and debris flows. Understanding the distribution and characteristics of these failures is vital for post-event analysis and future risk mitigation.</p> Objectives <p>This study aims to develop a detailed post-event landslide inventory of the Misa basin and to analyze the spatial distribution, the main morphological features, and the environmental context of the triggered landslides. A further objective is to evaluate the impact of these landslides on the built environment, particularly roads and buildings.</p> Methods <p>The landslide inventory was created using four Very High-Resolution (VHR) satellite imagery datasets (spatial resolution ranging from 3 m to 0.4 m), acquired before and after the event. Semi-automatic approaches, including NDVI (Normalized Difference Vegetation Index) change detection and segmentation/classification, were employed to assist visual photointerpretation. Field surveys were carried out to validate and refine the mapped landslides. Each landslide was classified according to its type of movement. Additional analyses included spatial density mapping, shape characterization using a roundness index, and correlation with geological, geomorphological, land cover, and rainfall data.</p> Results <p>The final inventory comprises 805 landslides, categorized by movement type and spatially analyzed. The results highlight specific distribution patterns influenced by geomorphological and geological settings. A notable number of landslides affected infrastructure, with direct impacts recorded on both road networks and buildings. Morphometric analysis revealed variability in landslide shapes and sizes, reflecting diverse failure mechanisms triggered by the intense rainfall.</p> Conclusions <p>This study provides new insights into the dynamics of landslides induced by extreme meteorological events, which are becoming increasingly frequent in Mediterranean regions. The event-based inventory not only supports a better understanding of triggering and preparatory factors but also contributes to improving emergency planning and future landslide susceptibility assessments in similar settings.</p>

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Event-based landslide inventory through very high-resolution optical images and field surveys

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月8日

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  • P. Confuorto,
  • R. Franceschini,
  • L. Scarpitta,
  • N. Casagli,
  • S. Morelli,
  • F. Raspini,
  • V. Tofani,
  • S. Moretti

摘要

Background

Landslide inventories are essential tools for emergency response, hazard assessment, and susceptibility mapping, especially following very hazardous events. On 15 September 2022, an extreme rainfall event affected the Misa River basin in the Marche region, Central-Eastern Italy, resulting in widespread hydrogeomorphological instability, including numerous landslides and debris flows. Understanding the distribution and characteristics of these failures is vital for post-event analysis and future risk mitigation.

Objectives

This study aims to develop a detailed post-event landslide inventory of the Misa basin and to analyze the spatial distribution, the main morphological features, and the environmental context of the triggered landslides. A further objective is to evaluate the impact of these landslides on the built environment, particularly roads and buildings.

Methods

The landslide inventory was created using four Very High-Resolution (VHR) satellite imagery datasets (spatial resolution ranging from 3 m to 0.4 m), acquired before and after the event. Semi-automatic approaches, including NDVI (Normalized Difference Vegetation Index) change detection and segmentation/classification, were employed to assist visual photointerpretation. Field surveys were carried out to validate and refine the mapped landslides. Each landslide was classified according to its type of movement. Additional analyses included spatial density mapping, shape characterization using a roundness index, and correlation with geological, geomorphological, land cover, and rainfall data.

Results

The final inventory comprises 805 landslides, categorized by movement type and spatially analyzed. The results highlight specific distribution patterns influenced by geomorphological and geological settings. A notable number of landslides affected infrastructure, with direct impacts recorded on both road networks and buildings. Morphometric analysis revealed variability in landslide shapes and sizes, reflecting diverse failure mechanisms triggered by the intense rainfall.

Conclusions

This study provides new insights into the dynamics of landslides induced by extreme meteorological events, which are becoming increasingly frequent in Mediterranean regions. The event-based inventory not only supports a better understanding of triggering and preparatory factors but also contributes to improving emergency planning and future landslide susceptibility assessments in similar settings.