Addressing the escalating levels of methane in the Earth's atmosphere is among the most urgent issues humanity faces. Methane ranks as one of the most potent greenhouse gases (GHGs), trapping over 25 times more heat than carbon dioxide over a 100-year period; thus, significantly reducing methane emissions will make a substantial impact in the fight against climate change.

One of the most impactful methods for mitigating methane emissions involves the prompt detection and repair of methane leaks. Achieving effective and efficient leak detection requires a geospatial sensor web approach. This approach entails combining the multi-scale and multi-modal methane observations from disparate sensing systems into a unified system of systems.

In this presentation, I will begin by introducing the concept of the geospatial sensor web, focusing on the role of Artificial Intelligence (AI) and the Internet of Things (IoT). Subsequently, I will argue that the geospatial sensor web stands as the most effective solution for curtailing methane emissions. I will also showcase a live demonstration of such a sensor web deployed in the field reducing methane emissions. To conclude, I will share my view regarding the challenges and opportunities that the geospatial sensor web is poised to encounter in the next five to ten years.