As the climate crisis demands a strong and immediate reaction, satellite imagery holds many keys to measuring, adapting, and transforming our environment and practices. Ever-growing geospatial data sources are part of the answer, but equally essential is accelerating the development of services relying on Earth Observation. This resource has only begun to reveal its potential for impact, thanks to a novel asset: artificial intelligence (AI), which combines analytical power with processing velocity.
Time is of the essence. Not a day goes by without a fresh warning, yet another projection confirming the impending disaster. The general disruption has even started migrating from the fields of statistics and modeling to the real world. As glaciers dwindle and wetlands dry out, or extreme heat episodes, droughts, and floods wreak havoc across the planet at a disquieting pace.
Satellite images are precious material to measure, predict and adapt to these phenomena. Thanks to constant improvement in AI techniques applied to geospatial imagery, the availability of the data it contains, is significantly accelerated.
The applications are many: vegetation and biodiversity health assessment, urban heat island identification, methane emissions measurement, or ocean watch, to name a few that help public and private organizations implement mitigation and compensation strategies.
But AI-driven satellite imagery processing is about more than just supporting resilience plans. As geopolitical roadblocks continue to hinder the adoption of systemic measures meant to tackle the climate and environmental crisis, automated Earth data collection and analysis provide a formidable resource to achieve tangible progress.
Supporting the transformation of supply chains is but one of these applications. At the same time, objective, continuous, and scalable data delivered by geospatial AI is an invaluable asset to inform sustainable forest management or agro-ecological transition initiatives.
For the farming industry, remote sensing and deep learning are major assets for widespread transformation by providing objective assessments. Not only does satellite data help directly monitor the implementation of more sustainable practices such as soil cover, crop rotation diversification.
Geospatial AI also brings out indirect indicators, validated by research and ground observations, on crucial aspects such as carbon storage, water retention, or organic soil fertility.
This is just one example of the almost inexhaustible potential of satellite imagery, thanks to the AI-led boost in strategic data extraction and near real-time mobilization. Putting such a rich and precious resource at the service of citizens has been a landmark decision by the European Commission, through the launch of the Copernicus program, in partnership with the European Space Agency.
For several years now, Europeans have been able to rely on freely available satellite images to monitor the environment. With their high revisit frequency, Sentinel missions provide an invaluable wealth of information on Earth’s transformations.
These space data are used by the various Copernicus services. Nevertheless, the significant value is also derived from them in other spheres: institutional, academic, and economic – all of them are also teaming up as part of the International Space Climate Observatory initiatives.
Thanks to this new information, once reliable, objective, dynamic, and immediately available, public research and businesses can respond to the environmental challenges met by territories and production systems more rapidly and efficiently every day.
In the field of climate, now the challenge is for these innovative players to scale up the impact of spatial data. There are several paths to explore to achieve this:
- Making satellite imagery and data easily understandable and usable by non-experts in a spatialized or analytical manner
- Shifting from one-shot analysis to continuous information streams
- Adjusting the extraction of spatial data to any scale of the territorial grid
- Putting the reservoir of information from the Copernicus program at the service of global issues through world-scale products based on proven models used on the European territory is more robust than global models.
But beyond the mobilization of data, the challenge is also to develop services that rely on this new information and to industrialize its use for all benefits. It is the ambition of the European Union’s space program to contribute to the development of these “downstream” applications.
This is also the objective of the French government, which, after initial support through the France Relance plan with the help of the National Center for Space Studies (CNES), aims to “develop and promote economic models based on data or space services downstream in the value chain” as part of its major France 2030 investment plan.
These supporting actions are essential to ensuring the European development of players already engaged in such global-scale, continuous data production from satellite imagery. Many innovative companies can rapidly develop use cases that revolutionize the monitoring of natural, agricultural, and urban areas.
These new space specialists are destined to become essential links in the chain of economic transformation by tapping into Earth observation for the benefit of all: public authorities, but also, and above all, businesses, whose production models will have to significantly reshape to meet the challenges of today and the decades to come.
Disclaimer: Views Expressed are Author's Own. Geospatial World May or May Not Endorse it
