Modelling agricultural drought: a review of latest advances in big data technologies

This article reviews the main recent applications of multi-sensor remote sensing and Artificial Intelligence techniques in multivariate modelling of agricultural drought. The study focused mainly on three fundamental aspects, namely descriptive modelling, predictive modelling, and spatial modelling...

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Veröffentlicht in:	Geomatics, natural hazards and risk Jg. 13; H. 1; S. 2737 - 2776
Hauptverfasser:	Hanadé Houmma, Ismaguil, El Mansouri, Loubna, Gadal, Sébastien, Garba, Maman, Hadria, Rachid
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Abingdon Taylor & Francis 31.12.2022 Taylor & Francis Ltd Taylor & Francis Group
Schlagworte:	Agricultural drought agricultural drought indices Algorithms Artificial intelligence Big Data Comparative analysis Comparative studies Computer Science Criteria Drought drought frequency Environment and Society Environmental Sciences Geography Humanities and Social Sciences Image Processing Learning algorithms Machine learning Methods and statistics Modeling and Simulation Modelling Multi-sensor modelling Multivariate analysis multivariate drought modelling Prediction models Remote sensing Remote sensors Vulnerability Drought frequency Artificial intelligence AI Machine learning Indices Big data Multivariate drought modelling Agricultural drought Multi-sensors modelling
ISSN:	1947-5705, 1947-5713
Online-Zugang:	Volltext
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