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Books > Earth & environment > Earth sciences > The hydrosphere
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Spatio-temporal characterisation of drought: data analytics, modelling, tracking, impact and prediction (Paperback)
Loot Price: R2,295
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Spatio-temporal characterisation of drought: data analytics, modelling, tracking, impact and prediction (Paperback)
Series: IHE Delft PhD Thesis Series
Expected to ship within 12 - 19 working days
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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.
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