Vol. 15 Núm. 88 (2026)
Artículos

Emparejamiento espectral no lineal para la detección de asbesto en imágenes hiperespectrales urbanas mediante alineamiento temporal dinámico

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  • Gabriel Elías Chanchí-Golondrino,
  • Manuel Alejandro Ospina Alarcón,
  • Manuel Saba
Gabriel Elías Chanchí-Golondrino
Universidad de Cartagena, Cartagena de Indias, Colombia.
Biografía del autor/a

PhD, Facultad de Ingeniería de la Universidad de Cartagena, Cartagena de Indias, Colombia.

Manuel Alejandro Ospina Alarcón
Universidad de Cartagena, Cartagena de Indias, Colombia.
Biografía del autor/a

PhD, Facultad de Ingeniería de la Universidad de Cartagena, Cartagena de Indias, Colombia.

Manuel Saba
Universidad de Cartagena, Cartagena de Indias, Colombia.
Biografía del autor/a

PhD, Facultad de Ingeniería de la Universidad de Cartagena, Cartagena de Indias, Colombia.

DOI: https://doi.org/10.34069/AI/2026.88.02.2

Publicado 2026-10-10

Palabras clave

  • Alineamiento temporal dinámico,
  • asbesto,
  • correlación,
  • imágenes hiperespectrales,
  • sensado remoto.

Cómo citar

Chanchí-Golondrino, G. E., Ospina Alarcón, M. A., & Saba, M. (2026). Emparejamiento espectral no lineal para la detección de asbesto en imágenes hiperespectrales urbanas mediante alineamiento temporal dinámico. Amazonia Investiga, 15(88), 29–43. https://doi.org/10.34069/AI/2026.88.02.2

Derechos de autor 2026 Gabriel Elías Chanchí-Golondrino, Manuel Alejandro Ospina Alarcón, Manuel Saba

Creative Commons License

Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.

Resumen

El sensado remoto hiperespectral ha ganado relevancia en biomedicina, agricultura y monitoreo ambiental, donde las firmas espectrales permiten detectar materiales mediante métodos computacionales. Este artículo presenta la implementación y evaluación del método de alineamiento temporal dinámico (DTW) para la detección de asbesto en imágenes hiperespectrales, comparándolo con la técnica de correlación ampliamente utilizada. La investigación sigue la metodología CRISP-DM, adaptada en cuatro fases: entendimiento del negocio, preparación de datos, modelado y evaluación, y despliegue. Los resultados muestran que el método DTW es efectivo para la detección de asbesto en imágenes hiperespectrales, aunque es menos sensible y eficiente computacionalmente que el método de correlación. El estudio sugiere que el método DTW es adecuado para identificar materiales con variaciones espectrales no lineales y puede aplicarse para detectar otros materiales además del asbesto. Dada la relevancia de la detección de asbesto para la salud pública, este método puede contribuir a una identificación más precisa de cubiertas de asbesto-cemento en zonas urbanas. El uso de bibliotecas de código abierto como Spectral, NumPy, SciPy y FastDTW para la implementación destaca la accesibilidad de este enfoque para aplicaciones académicas e industriales. Este trabajo pretende servir de referencia para futuras investigaciones sobre la detección de materiales utilizando DTW en imágenes hiperespectrales.

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