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Analysis of institutional authors

Martinez EAuthor

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October 21, 2021
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Proceedings Paper
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Landslide Susceptibility Model by Means of Remote Sensing Images and AutoML

Publicated to: Communications In Computer And Information Science. 1431 25-37 - 2021-01-01 1431(), DOI: 10.1007/978-3-030-86702-7_3

Authors:

Renza, D; Cárdenas, EA; Jaramillo, CM; Weber, SS; Martinez, E
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Affiliations

Univ Catolica Manizales, Manizales, Colombia - Author
Univ Mil Nueva Granada, Bogota, Colombia - Author
Univ Politecn Madrid, Madrid, Spain - Author
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Abstract

Hydrometeorological phenomena, including mass movements, are a frequent threat that can generate a great impact at different levels. In order to estimate the susceptibility to mass movements, this work contains a new proposal to estimate the susceptibility to mass movements using a supervised learning algorithm designed using AutoML (Automated machine learning). Pixel-level information from Sentinel-2 multispectral images was used to train the model, and an expert’s susceptibility map was used as labels.
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Keywords

autokerasautomlsusceptibilityAutokerasAutomlLandslideSusceptibility

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-28:

  • WoS: 4
  • Scopus: 4
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-28:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 11.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 11 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/92861/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 30
  • Downloads: 1
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Colombia; Granada.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: Last Author (MARTINEZ IZQUIERDO, M.ESTIBALIZ).

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Contextual narrative

This research proposes a new method to estimate susceptibility to mass movements using a supervised learning algorithm developed with AutoML. The model is trained on pixel-level information from Sentinel-2 multispectral images, utilizing an expert's susceptibility map as labels.

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