How have RPAS helped monitor forests and what can we apply in forest restoration monitoring?

We are currently experiencing an unprecedented moment in forest restoration, where monitoring activities in recovery areas play a vital role in problem identification and method adaptation. However, it is crucial to shift away from expensive traditional methodologies and develop technologies that enable large-scale monitoring using more accessible and cost-effective tools. In an effort to provide an evidence-based perspective, we conducted a systematic review of how remotely piloted aircraft systems equipped with various sensors have been employed for forest monitoring. We consulted three databases and included 53 articles in our review. The results revealed a trend toward research in tropical ecosystems, with forest structure being the most frequently assessed attribute, and canopy height being the most widely measured structural indicator. Red-green-blue sensors were commonly used, both individually and in combination with others, and there was a noticeable shift toward the use of light detection and ranging. Data validation primarily relied on forest inventory methods, often involving comparisons of outputs from different sensors and the use of artificial intelligence algorithms. Despite the wide range of studies utilizing sensor-equipped drones to analyze forest attributes, there is a notable scarcity of research specifically addressing the application of these technologies in forest restoration monitoring. Filling this research gap is essential, as employing techniques that enable large-scale monitoring, such as aerial photogrammetry and remote sensing, aligns with current trends and contributes to global commitments to environmental restoration and conservation.

Automated summary

The development of technologies that enable large-scale monitoring in forest restoration is crucial. This study conducted a systematic review of how sensor-equipped drones have been used for forest monitoring, revealing a focus on tropical ecosystems and specific attributes such as forest structure and canopy height. However, there is a lack of research specifically addressing the application of these technologies in forest restoration monitoring.