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SRS-GDA: A spatial random sampling toolbox for grid-based hydro-climatic data analysis in environmental change studies

HAN WANG, Yunqing Xuan Orcid Logo

Environmental Modelling & Software, Volume: 124, Start page: 104598

Swansea University Authors: HAN WANG, Yunqing Xuan Orcid Logo

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Abstract

We present in this paper the development of a new, open-source MATLAB toolbox SRS-GDA that aims to provide random spatial sampling of grid-based hydro-climatic datasets for environmental change studies. This toolbox addresses the needs of quantifying how hydro-climatic responses, which are often dri...

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Published in: Environmental Modelling & Software
ISSN: 1364-8152 1873-6726
Published: Elsevier BV 2020
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URI: https://cronfa.swan.ac.uk/Record/cronfa52972
Abstract: We present in this paper the development of a new, open-source MATLAB toolbox SRS-GDA that aims to provide random spatial sampling of grid-based hydro-climatic datasets for environmental change studies. This toolbox addresses the needs of quantifying how hydro-climatic responses, which are often driven by grid-based forcing datasets such as climate model projections, vary with location and scale. The toolbox can be used to carry out random spatial sampling of grid-based quantities with various constraints: shape, size, location, dominant orientation and resolution. A case study of a large dataset, the GEAR rainfall dataset is supplied to demonstrate the typical uses case of this toolbox. The provision of the toolbox for downloading together with the sample data is also presented.
Keywords: Spatial random sampling, Grid-based data analysis, Environment change, MATLAB toolbox, Open source software
College: Faculty of Science and Engineering
Funders: The authors would like to thank the Centre of Hydrology and Ecology (CEH), UK for providing the GEAR dataset to test the toolbox. The co-author Han Wang's PhD study is jointly sponsored by the two scholarships offered by the Chinese Scholarship Council (CSC), China and the College of Engineering, Swansea University, UK, which are both gratefully acknowledged. This study is supported by the UK-China Urban Flooding Programme Grant (REF: UUFRIP\10021) from the Royal Academy of Engineering, United Kingdom.
Start Page: 104598