# Earth Observation and Biodiversity Big Data for Forest Habitat Types Classification and Mapping
## 5 Conclusions  
Data-driven decisions are increasingly emerging as a turning point for policy makers. Sound scientific evidence and the availability of reliable and replicable data are key elements supporting informed decisions. In accordance with the renewed European Union ambition settled in the European Green Deal and in the targets of the 2030 Biodiversity Strategy, to protect nature as a whole, and strictly protect forests, the procedure presented here can contribute to detect forest types and changes over time and space, thus enhancing their conservation and restoration. The combination of EO data, observing and measuring ecosystem processes, big data analytics, making use of advanced computational analytic techniques. like RF machine learning algorithm, allowed for demonstrating the applicability of up-to-date technologies for habitats classification. To this end, an operational example of how EO processing chains can support forest habitats assessment and monitoring is attempted in this paper. Several studies on habitat mapping by remote sensing products at the regional or sub-regional scale are available, but this is a first attempt to map EUNIS forest habitat-types in Italy at the national scale with the integration of nationwide biodiversity databases. The approach presented here will allow an information technology procedure to be sped up with annual or seasonal updating, depending on the extension of the study area and the monitoring objectives. The obtained procedures could be applied on several environmental data in order to cyclically and promptly repeat spatial analysis to detect changes in space and time in support of ecosystem conservation issues, especially to evaluate the impact of illegal actions (e.g., forest harvesting) or natural hazards (e.g., destructive storms or other natural disasters) on habitat distribution. conceptualization and interpreted the results; [PERSON] and [PERSON] have written the manuscript with the assistance of [PERSON] and [PERSON]; [PERSON] significantly contributed to the manuscript draft review; [PERSON] managed the data collection from European Vegetation Archive; [PERSON] supervised the project and acquired the research funds; [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] written--review and edited the final text. All authors have read and agreed to the published version of the manuscript. This manuscript is not funded by a specific project grant. Not applicable. The authors want to acknowledge the Italian Institute for Environmental Protection and Research (ISPRA) that under the research agreement with the Italian Space Agency (ASI) \"Habitat Mapping project\" helped in achieving the goals of this study. The authors are also grateful to the useful and constructive comments and the support by ISPRA and academic colleagues: [PERSON], [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON]. Moreover, we would acknowledge the independent researchers on the development of free and open-source software for supporting the sharing of knowledge. The authors declare no conflict of interest.