A spatiotemporal regression-kriging model for space-time interpolation: a case study of chlorophyll-a prediction in the coastal areas of Zhejiang, China

Zhenhong Du, Sensen Wu, Mei Po Kwan, Chuanrong Zhang, Feng Zhang, Renyi Liu

Research output: Contribution to journalArticlepeer-review

Abstract

Spatiotemporal kriging (STK) is recognized as a fundamental space-time prediction method in geo-statistics. Spatiotemporal regression kriging (STRK), which combines space-time regression with STK of the regression residuals, is widely used in various fields, due to its ability to take into account both the external covariate information and spatiotemporal autocorrelation in the sample data. To handle the spatiotemporal non-stationary relationship in the trend component of STRK, this paper extends conventional STRK to incorporate it with an improved geographically and temporally weighted regression (I-GTWR) model. A new geo-statistical model, named geographically and temporally weighted regression spatiotemporal kriging (GTWR-STK), is proposed based on the decomposition of deterministic trend and stochastic residual components. To assess the efficacy of our method, a case study of chlorophyll-a (Chl-a) prediction in the coastal areas of Zhejiang, China, for the years 2002 to 2015 was carried out. The results show that the presented method generated reliable results that outperform the GTWR, geographically and temporally weighted regression kriging (GTWR-K) and spatiotemporal ordinary kriging (STOK) models. In addition, employing the optimal spatiotemporal distance obtained by I-GTWR calibration to fit the spatiotemporal variograms of residual mapping is confirmed to be feasible, and it considerably simplifies the residual estimation of STK interpolation.

Original languageEnglish (US)
Pages (from-to)1927-1947
Number of pages21
JournalInternational Journal of Geographical Information Science
Volume32
Issue number10
DOIs
StatePublished - Oct 3 2018

Keywords

  • GTWR-STK
  • Zhejiang coastal areas
  • spatiotemporal autocorrelation
  • spatiotemporal kriging
  • spatiotemporal non-stationarity

ASJC Scopus subject areas

  • Information Systems
  • Geography, Planning and Development
  • Library and Information Sciences

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