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UAV sensing in support of vegetation management: Lessons learned from California

Authors: Maggi Kelly*, University of California, Sean Hogan, University of California Division of Agriculture and Natural Resources, Andy Lyons, University of California Division of Agriculture and Natural Resources
Topics: Remote Sensing, Geographic Information Science and Systems
Keywords: UAVs, drones, remote sensing, vegetation, management
Session Type: Paper
Presentation File: No File Uploaded

There is a long legacy of the use of remote sensing in general (and Landsat imagery in particular) by scientists, land managers, governmental agencies, and nongovernmental organizations to map vegetation characteristics for land management and fire applications. However, several characteristics of Unmanned Aerial Vehicles (UAVs): pilot control and on-demand flights, fine spatial resolution, multiple alternative sensor (RGB, multispec, thermal and LiDAR) payloads, and ability to directly sample mean that UAVs will play an increasing role vegetation monitoring and management, particularly on small properties. Individual cases are needed to develop standard automated workflows to help natural resource and agricultural managers better incorporate large volumes of high resolution UAV imagery into vegetation management operations. This talk will present several UAV case studies that focus on small properties across a range of California vegetation types in both natural and agricultural settings. Case studies include post-fire monitoring with RGB and multispectral camera imagery, individual tree segmentation for orchard management using multispectral and lidar data; vegetation moisture stress monitoring with red edge camera imagery; and the benefits of repeated measurements through an agricultural growing season. The talk will highlight some of the technical limitations to UAVs (battery life, flight time, regulation, metadata standards) that can prohibit more widespread UAV use and sharing of collected data.

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