On remote Pacific islands and outer atolls, agroforestry (i.e., the cultivation and conservation of trees for agriculture) provides food security and income to local communities. Growing instability from climate change and invasive species like the coconut rhinoceros beetle threaten these resources. Actively managing and sustaining agroforestry resources requires detailed and up-to-date knowledge of forest inventories and conditions.
Project researchers will build capacity for conducting detailed agroforestry assessment and monitoring in Pacific Island nations, by using imagery collected from small unmanned aerial systems (sUAS or “drones”) and custom computer algorithms to automatically detect and monitor the health of coconut trees and other species of importance. This will allow project partners to quickly assess and manage important agroforestry groves, increasing food security and resilience. The main goals of the project are to (1) increase stakeholder capacity in the Pacific Islands for performing agroforestry inventory and monitoring, (2) further develop artificial intelligence detection algorithms for species of interest and health concerns in the Pacific Island, and (3) examine the utility of using satellite imagery for automated species detection and health monitoring.
The results from this work can be used by smallholder coconut farmers and processors and local and national government agencies to better manage agroforestry resources for coconut, pandanus, and other species of interest across the Pacific Island region. Early detection of invasive species, aging trees, and other stressors for agroforestry production will directly improve local community health and economic well-being.
