You can only manage what you can measure. 68% of the environmental indicators in the Sustainable Development Goals framework lack sufficient data for monitoring global progress. Geospatial data can help address this major shortfall. It can become a key tool in helping to measure how the environment is changing and to monitor the effectiveness of intervention strategies.
Satellite earth observation data has long been an important source of information for measuring and monitoring how the environment is changing. However, producing geospatial information for large areas from earth observation data is time-consuming and costly. Integration of machine learning is growing, and artificial intelligence is more responsive: earth observation data is now easier and quicker to use, helping governments monitor climate change more effectively.
Case study: Developing a geographic information system for United Arab Emirates
The Environment Agency, Abu Dhabi, is a government agency committed to protecting and enhancing the environment as well as maintaining and promoting the biodiversity of the desert and marine ecosystem. OS worked with Environment Agency, Abu Dhabi, to develop a geographic information system roadmap which provides a detailed structured plan to help capture, maintain and analyse environmental information to support their 2030 vision.
OS and Deimos Space UK worked with the Mohammed Bin Rashid Space Centre in Dubai to automate the production of geospatial information from satellite earth observation data using machine learning algorithms, making earth observation data more accessible and usable, saving time and costs. This state-of-the-art machine to machine model combines earth observation data and artificial intelligence to monitor and track the growth and health of important vegetation such as mangroves and palm trees.
What's the future for monitoring vegetation health?
Geospatial data aligned with New Space datasets will be used to measure the effectiveness of interventions put in place to mitigate the effects of climate change.
Accessing earth observation data is key to this widespread use; automating geospatial information attribution and creation using machine learning and artificial intelligence (AI) will make these new measuring data services more far more accessible. Geospatial information can then inform development of mitigation strategies and eventually support the prediction of change in health to ensure the desirable outcome is reached.
Talk to us about your sustainability goals
We can help any nation or organisation use geospatial data and know-how to put in place innovative sustainability solutions so that we can all see a better place.