Operational continental-scale land cover mapping of Australia using the Open Data Cube

C. J. Owers, R. M. Lucas, D. Clewley, B. Tissott, S. M. T. Chua, G. Hunt, N. Mueller, C. Planque, S. M. Punalekar, P. Bunting, P. Tan, Graciela Metternicht

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

To comprehensively support national and international initiatives for sustainable development, land cover products need to be reliably and routinely generated within operational frameworks. Coupled with consistent semantics and taxonomies, ensuring confidence in mapping land cover for multiple time periods, facilitates informed decision-making at scales appropriate to multiple policy domains. The United Nations Food and Agriculture Organisation (FAO) Land Cover Classification System (LCCS) provides a taxonomy that comparable at different scales, level of detail and geographic location. The Open Data Cube (ODC) initiative offers a framework for operational continental-scale land cover mapping using analysis-ready Earth Observation data. This study utilised the FAO LCCS framework and the Landsat sensor data through Digital Earth Australia (DEA; Australia's ODC instance) to generate consistent and continent-wide land cover mapping (DEA Land Cover) of the Australian continent. DEA Land Cover provides annual maps from 1988 to 2020 at 25 m resolution. Output maps were validated with ∼12,000 independent validation points, giving an overall map accuracy of 80%. DEA Land Cover provides Australia with a nationally consistent picture of land cover, with an open-source software package using readily available global coverage data and demonstrates a pathway of adoption for national implementations across the world.
Original languageEnglish
Pages (from-to)1715-1737
Number of pages23
JournalInternational Journal of Digital Earth
Volume15
Issue number1
DOIs
Publication statusPublished - 2022

Open Access - Access Right Statement

© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/),which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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