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Machine Learning Methods for Characterising and Tracking Spatiotemporal Drought events Case Study: Central America Dry Corridor

Drought is a natural, erratic phenomenon that has a widespread and significant impact on socioeconomic and environmental development. The early monitoring and evaluation of drought through forecasting models would allow the articulation of early control and mitigation strategies, thus achievin...

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Bibliographic Details
Institution:Escuela Colombiana de Ingeniería
Main Authors: Sánchez Hernández, Karel Aldrin, Santos Granados, Germán, Corzo Perez, Gerald A., Van Andel, Schalk, Muñoz Arriola, Francisco
Format: Trabajo de grado - Maestría
Language:English
Published: Maestría en Ingeniería Civil 2021
Subjects:
Aprendizaje automático - Previsión de sequías - Centroamérica
Medio ambiente - Previsión de sequías - Centroamérica
Agricultura - Aspectos ambientales - Protección del medio ambiente- Centroamérica
Aprendizaje automático - Previsión de sequías- Centroamérica
Medio ambiente
Machine Learning - Drought Forecasting - Central America
Environment
Online Access:https://repositorio.escuelaing.edu.co/handle/001/1588
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