## 5 Conclusions  
We have drawn the following main conclusions from this research:  
* Satellite spatial resolution is decisive in terms of assessing biodiversity and habitats. VHR data (at approximately 1-4 m) offers great potential for habitat suitability and connectivity assessment for the five wildlife species in this research and, most likely, for many more. * Automated habitat suitability assessment using VHR imagery is feasible and provides valuable, ecologically meaningful information
* The expert insights of ecologists on the species-habitat relationships examined here provide key underpinning knowledge to enable use to be made of the potential of VHR satellite data for habitat assessment. * VHR data and imagery offer great potential for use in habitat management at the scale of individual properties (farms, etc.) and at a whole-landscape scale. It provides an effective source of information of value for land management and environmental decision making and as potential evidence for the MRV relevant to ELM and similar policies. **Supplementary Materials:** The following are available online at [[https://www.mdpi.com/article/10.3390/su13169105/s1](https://www.mdpi.com/article/10.3390/su13169105/s1)]([https://www.mdpi.com/article/10.3390/su13169105/s1](https://www.mdpi.com/article/10.3390/su13169105/s1)), Table S1. UK CEH Land Cover 2019 classes description; Table S2. Habitat requirements of 5 studied species; Table S3. Species habitat requirement and opportunities to create/improve/extend suitable habitat for selected species; Table S4. Workflow of modelling the habitat suitability and connectivity; Table S5. Habitat assessment approach and contribution of VHR satellite imagery; and Figure S1. Examples of VHR satellite data. **Author Contributions:** Conceptualization, A.A., R.J.M., S.M. and J.L. ; methodology, A.A., R.J.M., S.M. and J.L. ; software, A.A.; validation, A.A., R.J.M., S.M. and J.L. ; formal analysis, A.A., investigation, A.A.; resources, A.A., S.M. and R.J.M. ; data curation, A.A.; writing--original draft preparation, A.A.; writing--review and editing, A.A., S.M., R.J.M. and J.L., visualization, A.A.; supervision, S.M., R.J.M. and J.L., project administration, R.J.M. ; funding acquisition, S.M., R.J.M. and J.L. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was part-funded by Natural Environment Research Council (NERC) SCENARIO Doctoral Training Partnership, Grant/Award NE/L002566/1, CASE award partner the National Physical Laboratory (NPL) and by UKRI/Research England SPF funding via the University of Surrey. The APC was funded by the University of Surrey. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** Some dataset presented in this study are openly available in [90; 91; 92; 93]. Restrictions apply to the availability of the UK CEH LCM2019 and Crops2019 products. Data were obtained from Digimap Edina, available from the [[https://digimap.edina.ac.uk/](https://digimap.edina.ac.uk/)]([https://digimap.edina.ac.uk/](https://digimap.edina.ac.uk/)) with the permission of University of Surrey. **Acknowledgments:** This research was supported by the SCENARIO Doctoral Training Partnership of the UK Natural Environment Research Council (NERC) with PhD funding for the first author. We thank the National Physical Laboratory (NPL) for co-funding as the CASE award partner and, in particular, for co-supervision by [PERSON] of NPL for AA's PhD research. We also would like to thank University of Surrey SPF UKRI/Research England support for AA for her secondent _\"Earth Observation for Advanced Monitoring, Reporting and Verification for Environmental Land Management (ELM) policy in the Surrey Hills Ara of Outstanding Natural Beauty (SH-AONB)\"_ to conduct this research with the SH-AONB Defra Test and Trial.