Drone-Based Monitoring of Biodiversity Responses to Targeted Forest Restoration in Tropical Habitat Mosaics

Abstract

The research will determine the efficacy of drone-based surveillance in determining biodiversity
responses to forest restoration in tropical habitat mosaics. The study contrasts the level of species
richness, abundance, and vegetation health (NDVI) in restored and non-restored regions in two years.
In the main, the findings include that: the species richness grew by 30% in Year 1, and 44% in Year
2, in the restored areas; but it rose by 5-7% in non-restored areas. The biodiversity index of Shannon
Wiener of restored areas has increased 34%, from 2.3 to 3.1, but in non-restored regions, the
improvement was only 12%. Drones were found to have a 95% species detection rate, and they
significantly improve biodiversity observation in large and remote areas of restoration. The research
also brought out the fact that the restored areas had significant vegetation health improvement in terms
of their NDVI, which rose to 0.80 in Year 2 after restoration, as compared to the smaller rise in non
restored areas (from 0.45 to 0.55). These results emphasize the usefulness of drones in scalable, cost
effective biodiversity monitoring in conservation and restoration efforts. According to the research,
drone technology will be able to take accurate and repeatable data to measure the success of the
restoration and alter the adaptive management strategies. The next step in the field should be
enhancing the accuracy of drone sensors, control of the distance of flight, and machine-learning
species detection. Also, a combination of drone data, satellite imagery, and ground-based surveys can
provide a more comprehensive view of biodiversity processes.