# Comparison of Land Cover Categorical Data Stored in OSM and Authoritative Topographic Data
## 6 Conclusions  
It was assumed that the selection of a set of geospatial data for a specific application (fit-for-purpose data) could be completed on the basis of the local or regional CCI. Geospatial datasets are assessed by clustering hexagonal grid cells based on ordered CCI similarity. Like any data classification, it is an exploratory procedure because it leads to an understanding of objects and processes. The research is theoretical and methodological in nature, but the close connection to a specific problem situation also gives it a cognitive aspect. Assuming that the study area consists of several spatially disconnected areas (e.g., counties, cities), the regional CCI makes it possible to assess the suitability of the sets according to a common scale based on the standard deviation. However, the results of the regional assessment outperform the local classification, giving better results, i.e., a higher level of data compliance. The overestimation of regional compliance ranges from 9 to 20% of the county's area, with an average of 3% reduction in the area over which the two datasets (BDOT10k and OSM) have comparable information scope. Areas of medium and large incompatibility are reduced by an average of 2.4%. Sensitivity analysis shows that neither the size of the region nor the spatial location of the counties had a significant impact on the values of the regional CCI. The CCI values in all analyzed districts revealed clustering. A greatest variation between BDOT10k and OSM data was observed in areas with a high degree of urbanization (e.g., Piaseczno city, Otwock city) and near the course of major transportation routes. The analyses carried out did not prove statistically significant correlations between the CCI coefficients and the land cover elements studied (buildings, roads, rivers, railways, forests and water bodies). OSM is a valuable source of up-to-date geographic data in emergency mapping, with capacities including, but not limited to, identifying infrastructure at risk of destruction, collapsed buildings, fires and accessibility, which can be important inputs for the orientation of rescuers on the ground. The use of these data in areas with varying degrees of completeness and timeliness of the other official spatial data is of particular importance. Nevertheless, the volunteer type of data may raise issues about quality. The analysis performed of the compliance of the OSM dataset in comparison with official data allows the selection of a set with appropriate characteristics suitable for the intended purpose. Conducting and comparing several counties using a common analytical framework allows for synthesizing how complete the analyzed geodatasets are, and identifying potential commonalities and differences across places. The method proposed in this paper has several limitations. Among them are TOPSIS constrains, such as the way that variables are weighted, correlations between variables, and the possibility of an alternative that is close to the ideal point and the nadir point simultaneously. An additional limitation is the CCI designation that is based solely on criteria (variable) such as differences in the area and length of the geographic feature analyzed in the OSM and BDOT10k datasets. In future work, our research will primarily address at least some of the limitations mentioned above. Thus, we will use a different WLC approach to assess the correspondence between OSM and authoritative topographic data. The [PERSON]'s information capacity method, a the method of optimal predictor selection, is considered for the selection of explanatory variables to be used in a model to evaluate geodatasets. Another research question to deliberate regards the impact of the scope and methods of weighting variables. **Author Contributions:** Conceptualization S.B. and E.B. ; methodology S.B. and K.P. ; formal analysis S.B. ; investigation S.B. ; resources S.B. ; data curation S.B. ; writing--original draft preparation S.B. ; writing--review and editing S.B., E.B. and K.P. ; visualization S.B.