Laura Vedovato introduces readers to a range of remote sensing tools, explaining how they can be applied to topical forests to monitor the effectiveness of restoration efforts. Read more in the original Review article.
Introduction
In recent years, global commitments to forest restoration, like the UN Decade on Restoration and the Global Biodiversity Framework, have highlighted the need for scalable, effective ways to track progress. Yet, monitoring tropical forest restoration is a significant challenge. Tropical forests are complex and dynamic systems, requiring tools that go beyond traditional field surveys to monitor restoration at scale. Remote sensing technologies offer a promising solution, providing a cost-effective way to monitor these ecosystems over time and across vast areas.
Why remote sensing?
Field surveys, while essential, are often limited to small, accessible sites and require significant resources. Remote sensing technology allows us to overcome these limitations, capturing continuous and large-scale data on forest attributes like canopy cover, biodiversity, and biomass. This data is crucial for understanding how well restoration projects are progressing and which practices yield the best results.
Different tools, different insights
Remote sensing tools come in various forms, each offering unique benefits, some of them:
- High-resolution RGB images: These images, often captured from drones, allow for detailed, high-resolution views of the forest canopy. This can be especially useful in smaller, fragmented restoration sites or for tracking individual tree growth. RGB images enable detailed canopy mapping, structural assessments, and even tree species identification when combined with advanced algorithms.
- Satellite images: Multispectral and hyperspectral images from satellites, such as those provided by Landsat, can track forest cover changes, detect deforestation, and even estimate vegetation health through indices like NDVI (Normalized Difference Vegetation Index).
- Lidar and radar: These active sensors can penetrate forest canopies to reveal structural information such as tree height and density, allowing us to estimate biomass and observe structural diversity in forest recovery.
Applying remote sensing to restoration
Restoration projects vary widely in their approaches, from natural regeneration to tree planting. Remote sensing can capture the unique structural patterns these methods produce. For instance, canopy height and gaps in the forest can provide clues about biodiversity and successional stages. Using remote sensing, managers can monitor the effects of restoration choices over time and make adjustments as needed.
Challenges and future directions
Remote sensing, while powerful, has its limitations. High-resolution data can be costly and may require specialized expertise to analyse. Yet, new developments in cloud computing and artificial intelligence are making these tools more accessible. These tools allow practitioners to analyse large datasets without needing a supercomputer. Moving forward, partnerships between research centers and private companies can help expand access to these technologies and improve models that estimate carbon storage, biodiversity, and other ecosystem services.
The way forward
As we advance our use of remote sensing for forest restoration, one priority is creating shared databases and open-source tools. These resources can help standardize monitoring across regions and make it easier for practitioners worldwide to track restoration progress. Ultimately, remote sensing offers an efficient, data-driven approach to understanding and supporting tropical forest recovery. This technology not only enhances our ability to meet restoration goals but also promotes sustainable forest management for generations to come.
Read the full article ‘Remote sensing approaches to monitor tropical forest restoration: Current methods and future possibilities’ in Journal of Applied Ecology.
