Data Science
Harnessing spatio-temporal AI for coastal resilience
In today's world, where climate change is no longer a far-off concern but a present danger, coastal cities are increasingly vulnerable to storm surges.
Martial Humblot
Platform
Native support for H3 grids to reduce the computational cost of spatial queries
Incorporating the H3 grid into our spatial analysis toolkit enhances the precision and efficiency of our analyses and provides a robust framework for addressing complex geospatial challenges.
Data Science
Coastal storm surge risk analysis
Coastal storm surge risk analysis is a comprehensive framework that combines scientific, technical, and socio-economic analyses to assess and manage the risks associated with storm surges.
Data Science
Weather anomalies monitoring
Monitoring weather anomalies plays a critical role in safeguarding lives, protecting infrastructure, ensuring economic stability, and increasing the resilience of communities and ecosystems to the increasing volatility of weather patterns.
Platform
How to select the appropriate source of weather data
Although weather station data remains essential to meteorological and climate research, combining it with other data sources, such as satellite observations, Internet of Things (IoT) data, and reanalyzed data, provides a more comprehensive understanding of weather and climate phenomena.
Data Science
Improving climate resilience: the benefits of a climate risk-specific ontology
A climate-specific ontology that includes socio-economic components is not just an academic exercise. It is a practical tool that enables us to anticipate, prepare for, and respond to the challenges posed by climate change.