2025-09-18, 09:00–09:30 (UTC), Aula Magna
This presentation showcases innovative tools—from user-friendly apps for visual interpretation and machine learning–ready data collection to in-situ observation tools embedded in the Geo-Quest app—that empower citizens to contribute meaningfully to land-use monitoring and climate action.
Global warming has already exceeded the critical 1.5°C threshold, and fossil fuel emissions continue to rise by approximately 2% annually—despite the urgent need for reductions of at least 8% per year. This presentation highlights key actions required to avert catastrophic climate change, with a particular focus on the terrestrial carbon sink and the critical roles of land use and land-use change.
However, it must be emphasized: technological innovation alone will not be enough. What is urgently needed are mindset shifts and transformative societal changes—reaching social tipping points that can drive sustained and meaningful climate action. While data improvements may have only a limited direct effect on emissions, they are essential to inform better policies, ensure transparency, and mobilize public engagement.
A deeper understanding of land-use dynamics is especially important in countries with limited capacity for regular forest inventories or land-use change monitoring. Emerging technologies—such as the new P-band radar sensors aboard Europe’s BIOMASS mission—offer promising opportunities to improve our knowledge of carbon stocks and assess the restoration potential of forests, peatlands, and other ecosystems.
Today, high-resolution maps can be generated with just a few clicks, enabled by increasingly accessible algorithms and open-source tools. Yet their full potential depends on the availability of high-quality training and validation data—an area where citizen engagement can play a key role.
Citizen participation in data collection not only improves coverage but also strengthens public awareness and accountability. This presentation showcases innovative tools—from user-friendly apps for visual interpretation and machine learning–ready data collection to in-situ observation tools embedded in the Geo-Quest app—that empower citizens to contribute meaningfully to land-use monitoring and climate action.