# Capability Analysis of Earth Observation Data for Integrated Emergency Management
## 5 Discussion on Recommendations for Utilising Satellite Data for Integrated Emergency Management  
While the literature consists of various works applying satellite imagery to assess land cover changes, urban development and environmental impacts, this study aims to explore the use of satellite imagery to consider the dynamic nature of risks identified by regional stakeholders. Although current satellite data were not found capable of independently supporting integrated emergency management in any of the three regional case studies, the scoping study identified that combining satellite imagery with additional geospatial datasets can help stakeholders, including LRFs, and manage and analyse the impact of different risks. The strength of this study lies in its effort to explore several different avenues of data collection and analysis, although not all case studies yielded equal results. Despite the short-term duration of the scoping study, this research strengthened collaborations across multiple agencies and, through a series of workshops, helped build and disseminate knowledge in the North East England region. The following discussion suggests a list of recommendations for future research and innovation in using satellite data to support the IEMF. * Implement change detection analysis for emergency incidents:  
We suggest implementing change detection functionality for all three case studies. Using such an approach, we can measure the change in snow build-up on critical infrastructure to respond to snow incidents. Determining the methodological accuracy for the fire case study proved difficult due to unavailable ground-truth data from real response sites and confidentiality issues around sites that have been, or are currently, under criminal investigation. We recommend fine-tuning the approach to estimate the magnitude of the height change (in addition to the direction of change). Magnitudes would allow for the automatic ranking of suspected sites, which is particularly important for response to fire incidents because the legal restrictions imposed by exceeded permits increase the fire risk. In future work to respond to power outages, change detection can assist in monitoring flooding events, the growth of vegetation near power lines, and the loss of electricity pylons. Risk-prone or affected sites can be highlighted by comparing time series and overlaying a change polygon onto the electricity network. * Integrate social data for enhanced risk analysis:  
The snow and power outage case studies would benefit from other social vulnerability factors, such as data on \"distance to nearest supermarket\". Due to its higher temporal and spatial resolution of precise power outages and vulnerability data, we suggest acquiring data from the Smart Energy Research Lab (SERL) to analyse the causes of power outages in the future. The fire case study suggests integrating the proximity to the nearest fire station and the incident site as further data layers. In accordance with [PERSON] et al. (2018), who utilised ERA5 data as input to the Global Flood Awareness System (GloFAS) for flood forecasting and early warning, ERA5 can aid stakeholders in incident management and provide important variables for vulnerability assessment. As extreme weather adversely affects disaster response times, we suggest integrating road network data to better understand traffic conditions and improve emergency response. * Conduct vulnerability analysis:  
The three case studies illuminated how different response types require more nuanced data to complement current satellite imagery analysis. Health and well-being data can help assess a community's sensitivity to the hazard and capacity to adapt to it ([PERSON] and [PERSON], 2018).