A new perspective on geohazards assessment: leveraging gigapixel imaging technique

The growing frequency of geohazards such as landslides, rockfalls, and slope instabilities, often intensified by climate change and human activities, underscores the urgent need for effective assessment and monitoring tools. Conventional remote sensing techniques like LiDAR, aerial photogrammetry, and satellite interferometry (InSAR) often rely on substantial financial and technical resources, which limit their accessibility. In response, Gigapixel imaging emerges as an innovative and cost-effective alternative, offering ultra-high-resolution visual data to support geohazard assessment while raising awareness among stakeholders and the public. The system used captures hundreds of partially overlapping images in sequence using a robotic head, effectively minimizing parallax errors. With accurate image stitching, it becomes possible to reconstruct an exceptionally detailed 2D gigapixel image. Also, the use of well-known photogrammetric technique allows the generation of 3D models from very high-quality images obtaining Very-High Resolution products. The CDRI’s fellowship GIGA2 - Gigapixel Imaging for Geohazards Assessment and Awareness is aimed at exploring the practical implications of integrating Gigapixel imaging into geohazard monitoring. Beyond its technical advantages, it promotes inclusivity in geoscience by providing an accessible and impactful tool for communicating risks and fostering preparedness. By bridging the gap between advanced technology and practical applications, Gigapixel imaging offers a promising pathway for enhancing geohazard assessment and resilience in vulnerable areas.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-15
DOI
https://doi.org/10.5281/zenodo.15425893
Primary Topic
Viral Infectious Diseases and Gene Expression in Insects
Type
article
Field-Weighted Citation Impact
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article

A new perspective on geohazards assessment: leveraging gigapixel imaging technique

Zenodo (CERN European Organization for Nuclear Research)
Viral Infectious Diseases and Gene Expression in Insects
article

A new perspective on geohazards assessment: leveraging gigapixel imaging technique

article en

Abstract

The growing frequency of geohazards such as landslides, rockfalls, and slope instabilities, often intensified by climate change and human activities, underscores the urgent need for effective assessment and monitoring tools. Conventional remote sensing techniques like LiDAR, aerial photogrammetry, and satellite interferometry (InSAR) often rely on substantial financial and technical resources, which limit their accessibility. In response, Gigapixel imaging emerges as an innovative and cost-effective alternative, offering ultra-high-resolution visual data to support geohazard assessment while raising awareness among stakeholders and the public. The system used captures hundreds of partially overlapping images in sequence using a robotic head, effectively minimizing parallax errors. With accurate image stitching, it becomes possible to reconstruct an exceptionally detailed 2D gigapixel image. Also, the use of well-known photogrammetric technique allows the generation of 3D models from very high-quality images obtaining Very-High Resolution products. The CDRI’s fellowship GIGA2 - Gigapixel Imaging for Geohazards Assessment and Awareness is aimed at exploring the practical implications of integrating Gigapixel imaging into geohazard monitoring. Beyond its technical advantages, it promotes inclusivity in geoscience by providing an accessible and impactful tool for communicating risks and fostering preparedness. By bridging the gap between advanced technology and practical applications, Gigapixel imaging offers a promising pathway for enhancing geohazard assessment and resilience in vulnerable areas.

Zenodo (CERN European Organization for Nuclear Research)
Istituto Superiore per la Protezione e la Ricerca Ambientale (IT)
Climate action
Openalex Percentile: Top 56%
Viral Infectious Diseases and Gene Expression in Insects
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