There is an ever-increasing amount of earth observation data available, largely in the form of data cubes. The relevant data formats are quite mature, data is (at least partially) freely available, various data processing libraries as well as visualization and data storage tools have been developed. Additionally, compute platforms can be used, they scale well and are becoming affordable.
Despite these relevant evolvements, non-EO experts who would greatly profit by integrating these resources into their work are still struggling to make full use of the available data as well as relevant analysis and processing tools.
Within FAIRiCUBE, we demonstrate a harmonized data space, the FAIRiCUBE Hub, where we connect all the pieces required for a data science pipeline into a user-friendly framework, where everything is FAIR (Findable, Accessible, Interoperable, Reusable) and TRUSTable (Transparency, Responsibility, User focus, Sustainability, and Technology). In this manner, we illustrate how the Green Deal Data Space (GDDS) could be formed pertaining to gridded data and the analysis thereof.
Climate change poses several challenges to cities, such as droughts, urban heat waves, changing precipitation patterns, floods and (peri-)urban biodiversity loss. Nowadays there is enough data to study these phenomena and find solutions, but it is complex to integrate and analyze due to its heterogeneity, format and quality.
As part of the FAIRiCUBE project, space4environment is combining the diverse datasets into structured data cubes and provide a comprehensive “toolkit” for their analysis.
space4environment is collaborating with the city of Luxembourg to map, analyse, and manage the spread of invasive alien plant species within Luxembourg City using municipal and environmental data.
Neophytes, also known as invasive alien plant species, are plants introduced to a region where they are not naturally found. Unlike native plants, neophytes have often been introduced intentionally or accidentally through human activity. In some cases, they adapt quickly to new environments, outcompeting native flora and disrupting local ecosystems. Their rapid spread can threaten biodiversity, alter habitats, and impact soil and water quality.
Scope of Work:
Example of environmental data used to model the occurrence probability of invasive species.
Observations of giant hogweed (Heracleum Mantegazzianum) in the city between 2011 and 2024. Besides the ecological threat, this species represents a serious health hazard for humans. The plant exudes a clear watery sap that can cause severe burning of the skin. Source: https://mdata.mnhn.lu/
At European scale, we collected and harmonised environmental variables, climate data and socioeconomic indicators into a single data cube, covering more than 600 European cities. We then carried out clustering analysis on the cube – a data-driven approach to discover patterns in data.
The clustering analysis is the starting point to identify cities with similar characteristics, assess climate change impacts across the continent and the influence of different factors on cities adaptation capacity.
The data used for the analysis can be found in the FAIRiCUBE Use Case 1 repository:
GitHub repository on the FAIRiCUBE Use Case "Urban adaptation to climate change"
