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Artificial intelligence and machine learning model for spatial and temporal prediction of drought events in the department of Magdalena, Colombia ; Modelo de inteligencia artificial y aprendizaje automático para la predicción espacial y temporal de eventos de sequía en el departamento del Magdalena, Colombia

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اقرأ أكثر حفظ في قائمتي
  • معلومة اضافية
    • بيانات النشر:
      Corporación Universidad de la Costa
      Colombia
    • الموضوع:
      2022
    • Collection:
      REDICUC - Repositorio Universidad de La Costa
    • الموضوع:
      Colombia; Magdalena
    • نبذة مختصرة :
      Introduction— Drought is one of the most critical hydrometeorological phenomenon in terms of its impacts on society. Although Colombia is a tropical country, there are areas of the territory which have periods of drought, and this causes significant economic damage. Objective— Due to recent advances in terms of the spatial and temporal resolutions of remote sensing, and artificial intelligence techniques, it is possible to develop automatic learning models supported by historical information. Methodology— In this study, a Random Forest (RF) and Bagged Decision Tree Classifier (DTC) model was built to perform spatial and temporal drought prediction in the department of Magdalena using the following features: Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), precipitation, Normalized Difference Water Index (NDWI), Normalized Multiband Drought Index (NMDI), evapotranspiration (ET), surface soil moisture (SSM), subsurface soil moisture (SUSM), Multivariate ENSO Index (MEI), Southern Oscillation Index (SOI), and Oceanic Niño Index (ONI). Results— For labelling, which allows one to train and evaluate the model, the Standardized Precipitation Index (SPI) was used to identify drought events. Conclusions— The implementation of the developed model can allow governmental entities to take actions to mitigate impacts generated by recurring droughts in their territories. ; Introducción— La sequía es uno de los fenómenos hidrometeorológicos más críticos por sus impactos en la sociedad. A pesar de que Colombia es un país tropical, existen zonas del territorio que presentan periodos de sequía, lo que ocasiona importantes perjuicios económicos. Objetivo— Debido a los recientes avances en cuanto a las resoluciones espaciales y temporales de la teledetección, y a las técnicas de inteligencia artificial, es posible desarrollar modelos de aprendizaje automático apoyados en información histórica. Metodología— En este estudio se construyó un modelo clasificador de Bosque Aleatorio (RF) y Árbol de Decisión ...
    • File Description:
      17 páginas; application/pdf
    • ISSN:
      0122-6517
      2382-4700
    • Relation:
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Aristizábal, “Artificial Intelligence and Machine Learning Model for Spatial and Temporal Prediction of Drought Events in the Department of Magdalena, Colombia”, INGECUC, vol. 18, no. 2, pp. 249–265. DOI: http://doi.org/10.17981/ingecuc.18.2.2022.20; https://hdl.handle.net/11323/10017; Corporación Universidad de la Costa; REDICUC - Repositorio CUC; https://repositorio.cuc.edu.co/
    • الرقم المعرف:
      10.17981/ingecuc.18.2.2022.20
    • Rights:
      Derechos de autor 2022 INGE CUC ; Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) ; https://creativecommons.org/licenses/by-nc-nd/4.0/ ; info:eu-repo/semantics/openAccess ; http://purl.org/coar/access_right/c_abf2
    • الرقم المعرف:
      edsbas.230AB16A