Principles and methods of scaling geospatial Earth science data

Yong Ge*, Yan Jin, A. Stein, Yuehong Chen, Jianghao Wang, Jinfeng Wang, Qiuming Cheng, Hexiang Bai, Mengxiao Liu, Peter M. Atkinson

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

31 Citations (Scopus)


The properties of geographical phenomena vary with changes in the scale of measurement. The information observed at one scale often cannot be directly used as information at another scale. Scaling addresses these changes in properties in relation to the scale of measurement, and plays an important role in Earth sciences by providing information at the scale of interest, which may be required for a range of applications, and may be useful for inferring geographical patterns and processes. This paper presents a review of geospatial scaling methods for Earth science data. Based on spatial properties, we propose a methodological framework for scaling addressing upscaling, downscaling and side-scaling. This framework combines scale-independent and scale-dependent properties of geographical variables. It allows treatment of the varying spatial heterogeneity of geographical phenomena, combines spatial autocorrelation and heterogeneity, addresses scale-independent and scale-dependent factors, explores changes in information, incorporates geospatial Earth surface processes and uncertainties, and identifies the optimal scale(s) of models. This study shows that the classification of scaling methods according to various heterogeneities has great potential utility as an underpinning conceptual basis for advances in many Earth science research domains.
Original languageEnglish
Article number102897
Pages (from-to)1-17
Number of pages17
JournalEarth-science reviews
Publication statusPublished - 1 Oct 2019




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