Lobelia is a Spanish SME specialized in Earth observation, physical climate risk assessment, computational intelligence and in the development of analytical visualization software.
Lobelia offers international experience in the generation of observational datasets of geophysical characteristics. Based on its exclusive and validated data of hydrological resources, air, soil, oceans, Earth’s vegetation and climate, Lobelia creates software and provide advance analytics to facilitate the decision-making processes of its clients and to develop effective solutions for a decarbonized and resilient society.
Lobelia is part of the Coalition for Resilient Investment in Infrastructure (CCRI), led by the British Government and the World Economic Forum, as a provider of climate data.
What do you offer?
- High resolution historical data, monitoring services and projections of essential climate variables and of computed variables from satellite-based observations, both locally and on large scale;
- Physical climate risk assessments (drought, forest fires, floods, sea level rise, coastal erosion, etc.) at infrastructure (highways, airports, railways, energy services, etc.) and supply chain level. Analysis and projections are based on the integration of existing and computed datasets, with global and local climate models through state-of-the-art Artificial Intelligence;
- Tailored Interactive visualization tools, aiming at facilitating data access, analysis and decision-making processes, through “serverless” features that enable seamless exploration of cloud-based data with rich and efficient interfaces.
What are you looking for?
Lobelia is looking for international and local clients, agents, existing service suppliers and key institutions that aim at integrating physical climate risk into their decision-making and investment processes.
Lobelia aims at creating dialogue with local entities to develop customized solutions based on local needs and priorities, and to engage with local experts for the development of strategic partnerships and for the integration of physical observations into existing models and services, offering accurate and locally-adapted scientifically validated solutions and datasets.
