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Spatiotemporal interpolation for environmental modelling


Susanto, F and de Souza Jr, P and He, J, Spatiotemporal interpolation for environmental modelling, Sensors, 16, (8) Article 1245. ISSN 1424-8220 (2016) [Refereed Article]


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Copyright 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (

DOI: doi:10.3390/s16081245


A variation of the reduction-based approach to spatiotemporal interpolation (STI), in which time is treated independently from the spatial dimensions, is proposed in this paper. We reviewed and compared three widely-used spatial interpolation techniques: ordinary kriging, inverse distance weighting and the triangular irregular network. We also proposed a new distribution-based distance weighting (DDW) spatial interpolation method. In this study, we utilised one year of Tasmania's South Esk Hydrology model developed by CSIRO. Root mean squared error statistical methods were performed for performance evaluations. Our results show that the proposed reduction approach is superior to the extension approach to STI. However, the proposed DDW provides little benefit compared to the conventional inverse distance weighting (IDW) method. We suggest that the improved IDW technique, with the reduction approach used for the temporal dimension, is the optimal combination for large-scale spatiotemporal interpolation within environmental modelling applications.

Item Details

Item Type:Refereed Article
Keywords:distribution-based distance weighting, inverse distance weighting; ordinary kriging, spatiotemporal interpolation, triangular irregular network
Research Division:Environmental Sciences
Research Group:Pollution and contamination
Research Field:Pollution and contamination not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:de Souza Jr, P (Professor Paulo de Souza Junior)
ID Code:117733
Year Published:2016
Web of Science® Times Cited:20
Deposited By:Information and Communication Technology
Deposited On:2017-06-27
Last Modified:2017-10-17
Downloads:110 View Download Statistics

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