Comparative validation of recent 10 m-resolution global land cover maps

Xu, P., Tsendbazar, N.-E., Herold, M., de Bruin, S., Koopmans, M., Birch, T., Carter, S., Fritz, S. ORCID: https://orcid.org/0000-0003-0420-8549, Lesiv, M. ORCID: https://orcid.org/0000-0001-9846-3342, Mazur, E., Pickens, A., Potapov, P., Stolle, F., Tyukavina, A., Van De Kerchove, R., & Zanaga, D. (2024). Comparative validation of recent 10 m-resolution global land cover maps. Remote Sensing of Environment 311 e114316. 10.1016/j.rse.2024.114316.

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Abstract

Accurate and high-resolution land cover (LC) information is vital for addressing contemporary environmental challenges. With the advancement of satellite data acquisition, cloud-based processing, and deep learning technology, high-resolution Global Land Cover (GLC) map production has become increasingly feasible. With a growing number of available GLC maps, a comprehensive evaluation and comparison is necessary to assess their accuracy and suitability for diverse uses. This particularly applies to maps lacking statistically robust accuracy assessment or sufficient reported detail on the validation procedures. This study conducts a comparative independent validation of recent 10 m GLC maps, namely ESRI Land Use/Land Cover (LULC), ESA WorldCover, and Google and World Resources Institute (WRI)’s Dynamic World, examining their spatial detail representation and thematic accuracy at global, continental, and national (for 47 larger countries) levels. Since high-resolution map validation is impacted by reference data uncertainty owing to geolocation and labelling errors, five validation approaches dealing with reference data uncertainty were evaluated. Of the considered approaches, validation using the sample label supplemented by majority label within the neighborhood is found to produce more reasonable accuracy estimates compared to the overly optimistic approach of using any label within the neighborhood and the overly pessimistic approach of direct comparison between the map and reference labels. Overall global accuracies of the maps range between 73.4% ± 0.7% (95% confidence interval) to 83.8% ± 0.4% with WorldCover having the highest accuracy followed by Dynamic World and ESRI LULC. The quality of the maps varies across different LC classes, continents, and countries. The maps' spatial detail representation was assessed at various homogeneity levels within a 3 × 3 kernel. Although considered as high-resolution maps, this study reveals that ESRI LULC and Dynamic World have less spatial detail than WorldCover. All maps have lower accuracies in heterogenous landscapes and in some countries such as Mozambique, Tanzania, Nigeria, and Spain. To select the most suitable product, users should consider both the map's accuracy over the area of interest and the spatial detail appropriate for their application. For future high-resolution GLC mapping, producers are encouraged to adopt standardized LC class definitions to ensure comparability across maps. Additionally, the spatial detail and accuracy of GLC maps in heterogeneous landscapes and over some countries are the key features that should be improved in future versions of the maps. Independent validation efforts at regional and national levels, as well as for LC changes, should be strengthened to enhance the utility of GLC maps at these scales and for long-term monitoring.

Item Type:	Article
Uncontrolled Keywords:	Global land cover; 10 m-resolution; Independent validation; Reference data uncertainty; Spatial detail
Research Programs:	Advancing Systems Analysis (ASA) Advancing Systems Analysis (ASA) > Novel Data Ecosystems for Sustainability (NODES) Strategic Initiatives (SI)
Depositing User:	Michaela Rossini
Date Deposited:	23 Jul 2024 13:32
Last Modified:	23 Jul 2024 13:32
URI:	https://pure.iiasa.ac.at/19901

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