Increasing the detail of European land use/cover data by combining heterogeneous data sets

Abstract

Data on land use and land cover (LULC) are a vital input for policy-relevant research, such as modelling of the human population, socioeconomic activities, transportation, environment, and their interactions. In Europe, CORINE Land Cover has been the only data set covering the entire continent consistently, but with rather limited spatial detail. Other data sets have provided much better detail, but either have covered only a fraction of Europe (e.g. Urban Atlas) or have been thematically restricted (e.g. Copernicus High Resolution Layers). In this study, we processed and combined diverse LULC data to create a harmonised, ready-to-use map covering 41 countries. By doing so, we increased the spatial detail (from 25 to one hectare) and the thematic detail (by seven additional LULC classes) compared to the CORINE Land Cover. Importantly, we decomposed the class 'Industrial and commercial units' into 'Production facilities', 'Commercial/service facilities' and 'Public facilities' using machine learning to exploit a large database of points of interest. The overall accuracy of this thematic breakdown was 74%, despite the confusion between the production and commercial land uses, often attributable to noisy training data or mixed land uses. Lessons learnt from this exercise are discussed, and further research direction is proposed.

Direct flood risk assessment of the European road network: an object-based approach

“…Alfieri et al, 2018;125 Lugeri et al, 2010;Serinaldi and Kilsby, 2017). These, however, overlook most of the road network (Rosina et al, 2018), see Fig. S2.…”

“…Meneses et al, 2019). The LUISA land cover map is a spatial and thematic refinement of CORINE-2012 using various additional data sources, such as rasterized object datasets (Rosina et al, 2018). As a result, many motorways that were absent in 130 https://doi.org/10.5194/nhess-2020-104 Preprint.…”

“…This peculiarity was manually removed in the model implementation of LUISA (Table S2), such as in the recent PESETA-IV study (Dottori et al, 2020). 290 Another difference between CORINE and LUISA is the strong increase in damage to 'Road and rail networks and associated land', from 15 to 144 million €/y respectively, resulting from integrating the motorway network into the LUISA land cover grid (Rosina et al, 2018).…”

“…CC BY 4.0 License. are very narrow line elements and have not been explicitly integrated in the LUISA grid (Rosina et al, 2018), their contribution to the LUISA damage is negligible. Therefore, we assume that LUISA class 'Road and rail networks and associated land' corresponds to the motorway network and that the other LUISA land use classes correspond to the underlying road network.…”

Multi-Source Geo-Information Fusion in Transition: A Summer 2019 Snapshot

“…We can also notice low or very low change in some countries (Austria, UK, and Greece). We can suspect that the "compatibility of information between all member states" may still be improved: research in data fusion is still in progress [12], especially following the decision to add new High Resolution Layers (HRL) as a complement to the CORINE Land Cover product [13].…”