With global temperature on the rise and drastic climate changes the frequency and intensity of heat waves are also increasing .
In 2022 Europe alone had 61500 deaths due to heat waves. In particular elderly (>65), children & people with chronic diseases are at greater risk. If this group of people live in a town or village far from health care infrastructure they face a multiplied risk during heat waves. A study has shown that the death rate due to heat waves has increased by 18% for vulnerable people living in rural areas.
Mitigation and adaptation strategies must be implemented to protect at-risk populations against heat waves. Our strategy to protect this population against heat waves is:
Identify which areas and populations are at greater risk using data from Sentinel 3
Build warning systems targeting the identified areas and populations. Warning systems can be implemented in several forms we target the following:
App showing live heat wave risk index
SMS subscription to at-risk population
Live roadsigns at roads entering the local towns and villages that provide real-time warnings for heat waves
Provide this insight to government and local authorities so they best can plan where they should locate first aid responders, shelters, and new health infrastructure
The goal is to provide better protection and warning systems to at-risk populations against heat waves. The key stakeholders are local authorities, municipalities, and the government. The insight we provide into where the at-risk population is located is valuable information for authorities implementing disaster plans such as Rijkinstituut voor Volksgezondheid en Milieu (RIVM) (National Institute for Public Health and Environment) in the Netherlands. The specific authority depends on country to country.
EU Space Technologies
We name a map that will identify at-risk population as the Heat Stress Vulnerability Map. Different layers of data are used to create the Heat Stress Vulnerability Map and thus pinpoint the areas and at-risk populations.
The Heat Stress Vulnerability map combines two key information: the accessibility of healthcare infrastructure together with the risk index of intense temperatures.
The Sea-Land-Surface-Temperature-Radiometer (SLSTR) instrument on board Sentinel 3 will be used to perform LST measurement. By combining Sentinel 3 data together with Landsat 8 data we can increase the resolution of land surface temperature (LST) estimate  . With historical data we can identify the areas that are more affected by the heat waves. In the future we also aim to identify the risk areas of heat islands within cities with higher resolution satellite data.
The accessibility of healthcare infrastructure can be computed from the hospital location data released European Union data together with the route map information Following the steps of  and .
Space for International Development & Humanitarian Aid
In the context of the Hackathon, we tackle challenge #1 where we are focusing on the lack of infrastructure for remote areas during heat waves. We do site planning and selection for where to:
Implement warning systems
Locate first responders and aid shelters for disaster mitigation
Build new health care infrastructure (e.g. hospital) to reach the at-risk population
We are a team of 7:
Charles Govillot: CEO and project owner
Kevin De Sousa: Earth Observation Expert
Nelly Paradel: Satellite data processing expert
Linda Hermann: Background in mathematics and machine learning. Will be working on algorithms to develop the Heat Stress Vulnerability Map and satellite data processing
Yefri Gonzalez: Full stack developer. Responsible for developing app that will be used as warning system and do satellite data processing
Chrisy Raharison: Business and Innovation: Responsible business development.
Anas Alam: Engineer: Doing Integration between development and busines
 Climate Change Indicators: Heat Waves, United States Environmental Protection Agency (EPA), July 2022
 Ballester, J., Quijal-Zamorano, M., Méndez Turrubiates, R.F. et al. Heat-related mortality in Europe during the summer of 2022. Nat Med 29, 1857–1866 (2023). https://doi.org/10.1038/s41591-023-02419-z
 Graczyk, D.; Pińskwar, I.; Choryński, A. Heat-Related Mortality in Two Regions of Poland: Focus on Urban and Rural Areas during the Most Severe and Long-Lasting Heatwaves. Atmosphere 2022, 13, 390. https://doi.org/10.3390/atmos13030390
 Weiss, D. J., Nelson, A., Gibson, H. S., Temperley, W., Peedell, S., Lieber, A., Gething, P. W. (2018). A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature, 553(7688), 333-336,336A-336J. doi:https://doi.org/10.1038/nature25181
 Nelson, A., Weiss, D.J., van Etten, J. et al. A suite of global accessibility indicators. Sci Data 6, 266 (2019). https://doi.org/10.1038/s41597-019-0265-5
 Onačillová, Katarína, Michal Gallay, Daniel Paluba, Anna Péliová, Ondrej Tokarčík, and Daniela Laubertová. 2022. "Combining Landsat 8 and Sentinel-2 Data in Google Earth Engine to Derive Higher Resolution Land Surface Temperature Maps in Urban Environment" Remote Sensing 14, no. 16: 4076. https://doi.org/10.3390/rs14164076
 Zhao-Liang Li, Bo-Hui Tang, Hua Wu, Huazhong Ren, Guangjian Yan, Zhengming Wan, Isabel F. Trigo, José A. Sobrino, Satellite-derived land surface temperature: Current status and perspectives, Remote Sensing of Environment, Volume 131, 2013, Pages 14-37, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2012.12.008.