Evidence map›Paper›PMID 39922886›Full record

ArticleScientific reports2025

Rapid landslide detection from free optical satellite imagery using a robust change detection technique.

Rosa Coluzzi, Angela Perrone, Caterina Samela, Vito Imbrenda, Salvatore Manfreda, Letizia Pace, Maria Lanfredi

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Rosa ColuzziInstitute of Methodologies for Environmental Analysis, National Research Council of Italy (IMAA-CNR), 85050, Tito Scalo, PZ, Italy.
Angela PerroneInstitute of Methodologies for Environmental Analysis, National Research Council of Italy (IMAA-CNR), 85050, Tito Scalo, PZ, Italy. angela.perrone@cnr.it.
Caterina SamelaInstitute of Methodologies for Environmental Analysis, National Research Council of Italy (IMAA-CNR), 85050, Tito Scalo, PZ, Italy.
Vito ImbrendaInstitute of Methodologies for Environmental Analysis, National Research Council of Italy (IMAA-CNR), 85050, Tito Scalo, PZ, Italy.
Salvatore ManfredaDepartment of Civil, Building and Environmental Engineering, University of Naples Federico II, 80125, Naples, Italy.
Letizia PaceDepartment of Earth and Geoenvironmental Sciences, University of Bari Aldo Moro, 70125, Bari, Italy.
Maria LanfrediInstitute of Methodologies for Environmental Analysis, National Research Council of Italy (IMAA-CNR), 85050, Tito Scalo, PZ, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last decades, the availability of multi-source, multi-scale, and multi-resolution remote sensing data and the consequent progress of processing techniques brought a significant positive impact for landslide detection. As a result, nowadays also public institutions dealing with geo-hazard management worldwide regularly use satellite data and products in landslide investigations. Due to the complexity of the phenomenon which might involve the displacement of massive rocks, soil, and both wet and dry vegetation from hillslopes, and the significant impact on the safety of the population and road infrastructure, the development of specific procedures for the rapid detection of landslides is extremely challenging. This is particularly important in the first phases of landslide risk management to evaluate the extension of the area involved by the movement and proceed with an initial delimitation of the so-called alarm zone, where preventive evacuation must be applied. In this study, the wide-ranging Tasseled Cap Transformation (TCT) is proposed as a not-sophisticated and rapid method able to detect different land-change features simultaneously by processing only two (pre- and post-event) Sentinel-2 images. The RGB color composite image obtained by stacking δTCT

Indexed as

Change detectionLandslide detectionOptical imagesSentinel2Tasseled cap transformation (TCT)

Identifiers

PMID39922886
PMCPMC11807160

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