Together with our partners, students from diverse Arizona middle and high schools engage in STEM (Science, Technology, Engineering and Mathematics) focused activities to address real-world environmental challenges within their communities. This work meaningfully incorporates the use of technologically advanced systems such as Unmanned Aircraft Systems (UAS), or drones, and Geographic Information Systems (GIS).
The goal of Green Drone is to strengthen and catalyze development of a broader “pipeline” of students interested in STEM by using cutting edge technology to address real-world environmental challenges within their communities. We hope to encourage persistence in staying on the STEM-focused pathway by exposing students to advanced systems such as drones and GIS. Management of our public lands and natural resources will soon fall into the hands of today’s youth. This program helps to equip these future leaders with the tools and resources needed to successfully protect and conserve our natural ecosystems.
National Forest Foundation, The Boeing Company, APS Foundation, Maytag Foundation, Arconic Foundation, Society for Science, Niagara Cares, Northern Arizona University, Tonto National Forest, Arizona State University, Arizona Geographic Information Council, Esri, Audubon Arizona, Arizona Department of Forestry and Fire Management, Scottsdale Community College, and many more.
Green Drone offers both middle and high school programs which allow students to explore topics of conservation, natural resource management, and GIS and UAS technologies. Students learn how these technologies are used in projects to collect and analyze data, perform resource monitoring, and improve project management. With this knowledge and access to online GIS technology and resources, students can engage in scientific exploration using new tools to improve the quality of their research and analysis.
Green Drone also supports efforts to achieve an accurate model of vegetation classification on the Lower Salt River Restoration Project site. This process of machine learning utilizes structural and spectral data in a series of algorithms to identify unique characteristics pertaining to individual plant species. This training model can then be used to map vegetation populations across the site. We are excited to share that work completed in the first year of Green Drone was highlighted in the scientific journal Drones, serving as a significant contribution to the world of vegetation mapping using drone technology.