In recent years, satellite data has become an essential tool in biodiversity conservation. Remote sensing technology allows researchers to monitor ecosystem services from above, providing high-resolution images that offer a clear picture of changing landscapes.
This technology is particularly important for monitoring remote or inaccessible regions, where traditional field surveys might be too costly and time-consuming.
Satellite imagery can capture a wide range of environmental data, including land cover, vegetation types, water bodies and human activities.
By analysing these datasets, researchers can detect changes and threats to wildlife habitats, such as deforestation, urbanisation, glacier melting, and climate change.
This helps conservationists monitor habitat loss in real-time and make informed decisions to help preserve endangered species.
One of the most valuable uses of satellite data in conservation is its role in habitat suitability modeling. These models predict the ideal habitat for species to thrive and identify unsuitable areas, considering factors like bio-climatic data, topographical data, land use/land cover data and human activity.
When combined with sophisticated algorithms, satellite data allows scientists to refine these models, leading to more accurate predictions.
This is especially important in the context of climate change, which is causing rapid shifts in habitats. Satellite data helps identify areas where species might need to migrate to find new habitats or where conservation efforts should focus on restoring degraded habitats.
Elusive species like the snow leopard inhabits high altitudes (3,000–7,500 metres) and extreme climates. Studying their habitat is challenging.
Machine learning models, integrated with satellite and other variables (climatic, topographical, and human activity data), play a pivotal role in understanding and conserving these species.
One of the primary advantages of satellite data is its ability to monitor habitats and species movement in real-time. Unlike traditional methods, which may take weeks or months to gather and analyse data, satellite imagery provides up-to-date information almost instantly.
This real-time capability allows conservationists to respond to environmental threats as they occur. For example, when wildfires ravage forests or illegal logging threatens protected areas, satellite imagery can provide immediate insights into the extent of the damage. This rapid response is crucial for species that are already at risk and ecosystems that need urgent protection.
In 2019, satellite data played a crucial role in assessing the damage caused by wildfires in the Amazon. The imagery provided essential information on the extent of the fires, helping conservationists understand the impact on biodiversity and habitat suitability, and guiding recovery efforts.
Another notable example is scientists from the University of Bath have used high-resolution satellite data from WorldView-3 and WorldView-4, combined with AI algorithms, to track African elephants through forests and grasslands. The AI systems demonstrated the ability to detect animals with the same accuracy as human observers, offering a valuable tool for monitoring wildlife without disturbing their natural habitats.
While satellite data holds immense promise, challenges remain. High-resolution imagery can be expensive, limiting access for smaller conservation organisations and NGOs.
However, as technology advances and open-source platforms provide more data, accessibility is improving. Additionally, analysing satellite data requires specialised knowledge and software, which may restrict its use in some regions.
To address this, collaborations and capacity-building initiatives are helping local conservationists learn to effectively use satellite data.
Looking forward, integrating satellite data with emerging technologies like artificial intelligence (AI) and machine learning will significantly enhance conservation efforts.
AI can process vast amounts of satellite data to identify patterns and predict changes in habitat suitability more accurately, enabling conservationists to make proactive decisions and respond to threats before they escalate.
Views expressed are author's own and do not necessarily reflect those of Down To Earth