We could soon be able to track changes in Australia s forests in near‑real time—using satellites

Billy Odell Tucker-Robinson Founder & Host — Banking With Billy Network • Intelligence Network • Data Science • AI Research • World News
Published: 2026-09-17T14:06:23.503Z • Permanent link

Satellite technology has long been a game-changer in the realm of environmental monitoring, and now it's poised to revolutionize the way we track changes in Australia's forests. Researchers at the Commonwealth Scientific and Industrial Research Organisation (CSIRO), in collaboration with the University of New South Wales (UNSW), have been working on a project that could potentially provide near-real-time monitoring of forest health. The project, which involves the use of satellite data and artificial intelligence, aims to detect early signs of forest degradation, such as deforestation and land clearing, allowing for swift action to be taken to mitigate the damage.

Led by Dr. Amanda Lohmann, a renowned expert in remote sensing and Earth observation, the team has been utilizing a combination of satellite data from the European Space Agency's (ESA) Copernicus program and machine learning algorithms to identify patterns in forest health. The data is then compared to historical records and ground-truth observations to validate the findings. According to Lohmann, the project has shown promising results, with the ability to detect changes in forest cover and biomass with unprecedented accuracy. "We're talking about a level of detail that's not possible with traditional methods," she explained. "This technology has the potential to be a game-changer for forest management and conservation efforts.

The project has also caught the attention of the Australian government, with the Department of the Environment and Energy (DEE) expressing interest in leveraging the technology to inform policy decisions. "We're excited about the potential of this technology to support our efforts to protect and conserve Australia's unique and fragile ecosystems," said a spokesperson for the DEE. The project is expected to be rolled out nationally, with the potential to be replicated in other countries. The implications of this technology are far-reaching, with the potential to revolutionize the way we monitor and manage our planet's natural resources.

The impact of this technology on the forestry industry is likely to be significant. Companies such as Greenpeace and the World Wildlife Fund (WWF) have long been vocal about the need for more effective monitoring and enforcement of forest protection laws. With the ability to track changes in forest health in real-time, these organizations will be able to identify areas of high conservation value and mobilize support for targeted conservation efforts. "This technology has the potential to be a powerful tool in the fight against deforestation and forest degradation," said a spokesperson for Greenpeace. The project also has implications for the timber industry, which has faced criticism in recent years for its role in driving deforestation.

The research community is also expected to be significantly impacted by this technology. Scientists at institutions such as the University of Melbourne and the Australian National University (ANU) have been working on similar projects, and the integration of satellite data and machine learning algorithms is likely to revolutionize the field of remote sensing. "This technology has the potential to be a major breakthrough in our ability to monitor and understand the health of our planet's ecosystems," said Dr. Kate Williams, a leading expert in remote sensing at the University of Melbourne.

The development of this technology is part of a larger trend towards increased use of satellite data in environmental monitoring. In recent years, there has been a significant increase in the availability of satellite data, driven in part by the growing demand for remote sensing capabilities in a range of industries. The ESA's Copernicus program, for example, provides access to a vast array of satellite data, including images of the Earth's surface, atmospheric conditions, and ocean currents. This data is used by a range of organizations, from governments and NGOs to private companies and research institutions. The integration of machine learning algorithms and artificial intelligence is likely to further accelerate this trend, enabling the detection of complex patterns and relationships that were previously impossible to identify.