Land cover–wetness combination maps

What the data product is This data product is the end product of a workflow of decision rules to inform a classification problem for the combined land cover and wetness of peatlands and mineral wetlands across ten European catchment areas. It used high-resolution land cover data products in combination with the water table depth model developed in this project. The 10 m raster products from ESA WorldCover (2021), the Copernicus Land Service Monitoring Programme CLCplus Backbone (2023) and Google Dynamic World (GDW; March-September modal composite, 2023) were selected, and their land cover classes harmonised as follows: each source contributes a per-pixel score to each harmonised class – GDW and ESA weighted by per-class accuracy derived from their respective confusion matrices, and CLCplus weighted by its per-pixel confidence value so that lower-confidence CLC assignments contributed less to the final decision. The class with the highest combined score was assigned as the output land cover. Pixels where no class achieved a positive score were assigned as no data. For the Scottish catchments, where the balancing contributions of the CLCPlus Backbone data set were not available for download, we replaced the CLCPlus data with the UKCEH Land Cover Map product, combining it with GDW and ESA in the same manner. This decision tree resulted in a single output land cover class per 10 m pixel. In cases where no agreement could be found, an “uncertain” class assignment was used. This was combined with wetness levels based on reducing the complexity of the data product in https://zenodo.org/records/16753826. We used a functional classification of “wet” = mean annual predicted water level between 0 and -0.2 metres; for “shallow drained” we used thresholds of -0.2 to -0.5 metres; and for “deep-drained” areas we used -0.5 or deeper, to allow for the uncertainties of ~20 cm in the water table predictions. Each single land cover class from the decision rule set was therefore subdivided into three wetness classes. A lookup table (lookup_combo.csv) is provided to decode the combined class values in each output raster. What it is useful for At present, the condition or land cover of wetland and peatland areas, as defined by the European Wetland Map across several European catchment areas, can only be defined by either global land cover data products, which tend to have a very limited number of assigned classes; CORINE, which has limited temporal steps; or higher resolution national data that do not use cross-compatible classification systems. This data product formed a first attempt at producing a harmonisation across European wetland and peatland condition classification and will be used for a scientific publication that compares the utility of the underlying parent products. As such, this is a purely academic exercise with limited immediate use cases. Other uses in derived products should take note of the caveats. Important caveats and use notes Although we tested whether the predicted classes matched available ground observations from the EVA database and our own compilation for Wet Horizons, Deliverable D1.4, this was more of a proof of principle, as there was insufficient data available from the same time period as the Earth Observation data. In addition, only a very low number of the available vegetation community observations fell within some of the predicted decision-rule combination categories. In addition, the modelling effort produced some incongruent output classes, such as 'water (deep drained)', meaning that the land cover product combination suggested water as the most likely land cover, but the water table depth model suggested a mean annual water table depth below 0.5 metres. We therefore suggest caution in further use as the model output is likely to be of only moderate predictive quality. Contacts for further queries or feedback on this product For further information or feedback, please contact the author team, either directly or via [e-mail].