£66.74

CRC Press Spatio-temporal characterisation of drought: data analytics, modelling, tracking, impact and prediction (IHE Delft PhD Thesis Series)

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£68.99 £52.50 £56.10 £59.70 £63.29 £66.89 £70.49 09 June 2024 13 November 2024 20 April 2025 24 September 2025 01 March 2026

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Description

Studies of drought have increased in light of new data availability and advances in spatio-temporal analysis. However, the following gaps still need to be filled: 1) methods to characterise drought that explicitly consider its spatio-temporal features, such as spatial extent (area) and pathway; 2) methods to monitor and predict drought that include the above-mentioned characteristics and 3) approaches for visualising and analysing drought characteristics to facilitate interpretation of its variation. This research aims to explore, analyse and propose improvements to the spatio-temporal characterisation of drought. Outcomes provide new perspectives towards better prediction. The following objectives were proposed. 1) Improve the methodology for characterising drought based on the phenomenon’s spatial features. 2) Develop a visual approach to analysing drought variations. 3) Develop a methodology for spatial drought tracking. 4) Explore machine learning (ML) techniques to predict crop-yield responses to drought. The four objectives were addressed and results are presented. Finally, a scope was formulated for integrating ML and the spatio-temporal analysis of drought. Proposed scope opens a new area of potential for drought prediction (i.e. predicting spatial drought tracks and areas). It is expected that the drought tracking and prediction method will help populations cope with drought and its severe impacts.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
11 February 2022
Listed Since
19 October 2021

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