David Will Presents: Drones & Remote Sensing on Kaho’olawe

Conservationists use drones for remote sensing in support of restoration of Kaho’olawe Island, Hawai’i.

An international conference focused on the impacts and management of invasive alien species on islands is taking place at University of Dundee, Scotland July 10-14. We’re sharing research that will be presented by experts in the field. For more information visit the conference website

Remote sensing data can help restoration specialists optimize invasive species removal operations. This study examines how high resolution data captured by drones can support restoration planning on Kaho’olawe Island, Hawaii. Kaho’olawe presents a special conservation challenge in that it is littered with unexploded ordnance.


This case study uses traditional remote sensing techniques to select three representative study areas that have limited unexploded ordnance concern. The workflows for collecting, processing, and analyzing the data can enable managers to determine if integrating Small Unmanned Aircraft Systems into invasive species removal programs is a cost-effective and efficient way to improve project success.


David Will working with a drone on Kaho’olawe Island, Hawaii. Credit: Island Conservation

Featured Photo: Kaho’olawe Island,Hawaii. Credit: Andrew Wright/Island Conservation

About David Will

David received a BS in bioinformatics from the University of California, Santa Cruz. During his tenure, David worked with the Site Stewardship Program, as part of the Chancellors Undergraduate Internship Program, to restore and maintain the campus’s numerous sensitive natural areas. Over the course of the internship he developed an internal wiki to store mitigation documents, survey data, and maps relevant to campus restoration efforts. David has a strong background in computer science and a keen interest in using computer applications and GIS as a tool to aid conservation and restoration efforts. He is currently developing a database and integrated data-collection system for monitoring, analyzing, and displaying field data.

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