# The Impact of Spatial Resolutions on Nature-Based Solution Suitability Mapping for Europe
## 5 Discussion  
In this study, we tested the impact of different spatial resolutions on the output of the suitability mapping to support our decision of a suitable input LULC layer for the suitability mapping of the NBS Toolkit.  
Overall, the results showed a great sensitivity when comparing the suitability maps of different resolution LULC input layers. This was indicated by the different analyses. Firstly, the cell statistics showed that the suitability mapping outputs of coarser resolution layers were more coherent with another than with the fine resolution layer. Secondly, a high sensitivity was detected through the patch statistics in the total size of suggested areas, the number of patches, the degree of fragmentation, and in the coherence analysis of all layers. Thirdly, the qualitative accuracy and appropriateness validation results suggest that the OSM fine resolution layer was more accurate and appropriate than the coarsest layer, especially close to low-density urban areas or houses. This finding aligns with the outcomes of [PERSON] et al. [19], stating that fine resolution layers are recommended to be used for urban analysis. However, in this study, rural areas were the focus and, therefore, the fine resolution layer showed only minor advantages compared to the coarser layers, based on the satellite imagery validation. In more homogenous land covers and uses (e.g., agricultural land), the coherence between all layers was greatest; thus, for these areas, the usage of coarser resolution layers can be sufficient, considering higher computational processing time of fine resolution layers, but also increasing complexity due to working with different data types (e.g., raster and vector). Lastly, the computation showed that there are no major differences in processing time within the study area, but it can be assumed that for computation at the European scale, a difference will become obvious [15].  
It can be concluded that the findings confirm the hypothesis that the resolution of LULC input datasets for suitability mapping needs to be determined in alignment with the aimed landscape type (urban or rural), as coarser resolution layers with, e.g., 100 m resolutions may not be accurate enough for highly heterogenous urban landscapes. Furthermore, which Nature-Based Solution the suitability mapping is focusing on needs to be considered. In this study, a large-scale NBS was selected, but for small-scale NBS, such as ponds and basins, finer resolution layers can be more appropriate. Hence, for decision-making on input layer's spatial resolution for suitable mapping, the desired goal (NBS scale and landscape) needs to be taken into account. This conclusion reflects findings in other studies [18,19].  
Even though the suitability of data for an intended purpose may not always be defined based on statistical measures [50], we used the results of this study to support our decision-making on the most suitable input layer for the computation of suitability maps for Europe. Based on the results, we utilise the LUISA layer for assessing the suitability of riparian forest buffers across Europe. However, for small-scale Nature-Based Solutions, or for solutions to be implemented in (semi-)urban areas, the toolkit will be using the OSM fine resolution layer.  
Finally, it can be recapped that the suitability mapping at the European scale functions as a pre-assessment and, therefore, inaccuracy in mapping may be caused by the coarseness of the input datasets. As we have seen, even the fine resolution layer indicated inaccuracies which could not be prevented. Hence, we argue that a local and context-specific assessment (including, i.e., social, economic, and political criteria) is necessary for in-depth validation and for final decision-making to avoid implications for the environment, society, and overall flood risk [3,51,52,53].