Referencias

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[2] CRED, “2021 Disasters in Numbers,” https://reliefweb.int/report/world/2021-disasters-numbers, Accessed: Nov. 20, 2022. [acceso: 2022-11-20].

[3] Conacyt, “Programas Nacionales Estratégicos,” [Online]. Disponible en: https://conacyt.mx/pronaces/

[4] E. Cuevas & R. Norton, “Inundaciones de 2020 en Tabasco: Aprender del pasado para preparar el futuro,” Technical Report, Centro Nacional de Prevención de Desastres, Ciudad de México, 2022.

[5] G. Konapala, S. Kumar, & A. Khalique, “Exploring Sentinel-1 and Sentinel-2 diversity for flood inundation mapping using deep learning,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 180, pp. 163–173, 2021.

[6] J. Paz, F. Jiménez, & B. Sánchez, “Urge manejo del agua en Tabasco,” Technical Report, Universidad Nacional Autónoma de México y Asociación Mexicana de Ciencias para el Desarrollo Regional A.C., Ciudad de México, 2018.

[7] L. Alzubaidi, J. Zhang, A. Humaidi, & A. Al-Dujaili, “A Review of Deep Learning: Concepts, CNN Architectures, Challenges, Applications, Future Directions,” Journal of Big Data, vol. 53, no. 8, 2021.

[8]M. Chini, R. Pelich, L. Pulvirenti, N. Pierdicca, R. Hostache & P. Matgen, “Sentinel-1 insar coherence to detect flood-water in urban areas: Houston and hurricane harvey as a test case”. Remote Sensing, Vol. 11, 2022.

[9]UN General Assembly, “Transforming our world: the 2030 Agenda for Sustainable Development”, 21 October 2015, A/RES/70/1, available at: https://www.refworld.org/docid/57b6e3e44.html [acceso 20 February 2023].
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