Gong, M., Miller, C. and Scott, M. (2018) Spatio-temporal Modelling of Remote-sensing Lake Surface Water Temperature Data. In: 33rd International Workshop on Statistical Modelling (IWSM 2018), Bristol, UK, 16-20 Jul 2018, pp. 106-111.
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Publisher's URL: https://people.maths.bris.ac.uk/~sw15190/IWSM2018/IWSM33-1.pdf
Abstract
Remote-sensing technology is widely used in environmental monitoring. The coverage and resolution of satellite based data provide scientists with great opportunities to study and understand environmental change. However, the large volume and the missing observations in the remote-sensing data present challenges to statistical analysis. This paper investigates two approaches to the spatio-temporal modelling of remote-sensing lake surface water temperature data. Both methods use the state space framework, but with different parameterizations to reflect different aspects of the problem. The appropriateness of the methods for identifying spatial/temporal patterns in the data is discussed.
Item Type: | Conference Proceedings |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Scott, Professor Marian and Gong, Miss Mengyi and Miller, Professor Claire |
Authors: | Gong, M., Miller, C., and Scott, M. |
College/School: | College of Science and Engineering > School of Mathematics and Statistics |
Copyright Holders: | Copyright © 2018 The Authors |
First Published: | First published in 33rd International Workshop on Statistical Modelling (IWSM 2018): 106-111 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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