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Understanding complex spatio-temporal variation

Reference	BBS/E/C/00004689
Principal Investigator / Supervisor	Professor Richard Lark
Co-Investigators / Co-Supervisors
Institution	Rothamsted Research
Department	Rothamsted Research Department
Funding type	Research
Value (£)	254,139
Status	Completed
Type	Institute Project
Start date	01/04/2005
End date	31/03/2008
Duration	36 months

Abstract

Objectives. To invent and demonstrate methods for elucidating and predicting variables whose statistics evolve in either or both time and space, and so are not suitable for geostatistical analysis. We will investigate the different ways in which agri-environmental systems depart from stationarity in time and space, and investigate the implications of this for sampling and predicting complex spatial variables. We shall develop an inferential method to compare the best wavelet basis for a data set against the expectation under stationarity and from this to identify the locations and scales of key variations in data. We shall investigate whether wavelet transforms for irregularly sampled data can be used to define non-linear transforms of a co-ordinate system under which data may be treated as stationary. We shall develop further wavelet transforms for multistate variables with a view to making wavelet transforms useful in ecology. The deliverables from this objective will comprise novel methods with implications for sampling and estimation, and insight into complex spatio-temporal variation of biological processes.

Summary

unavailable

Committee	Closed Committee - Agri-food (AF)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	X - not in an Initiative
Funding Scheme	X – not Funded via a specific Funding Scheme

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