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...

Full description

Saved in:

Bibliographic Details
Published in:	Geomatics, natural hazards and risk Vol. 13; no. 1; pp. 2737 - 2776
Main Authors:	Hanadé Houmma, Ismaguil, El Mansouri, Loubna, Gadal, Sébastien, Garba, Maman, Hadria, Rachid
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 31.12.2022 Taylor & Francis Ltd Taylor & Francis Group
Subjects:	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 Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!