Lightweight Vertical Take-Off & Landing Unmanned Aerial Systems For Local-Scale Forestry and Agriculture Remote Sensing Data Collection

Abstract:

The evolution of lightweight Vertical Take-Off and Landing (VTOL) rotary Unmanned Aerial Vehicles (UAVs) and remote sensor technologies have provided researchers with the ability to integrate compact remote sensing systems with UAVs to create Unmanned Aerial Systems (UASs) capable of collecting high-resolution airborne remote sensing data. UASs offer a myriad of benefits. Some of the most notable include: (1) reduced operational cost; (2) reduced lead-time for mission planning; (3) high-resolution and high-density data collection; and (4) customization of data collection intervals to fit the needs of a specific project (i.e. acquiring data at hourly, daily, or weekly intervals). Such benefits allow researchers and natural resource managers to acquire airborne remote sensing data on local-scale phenomenon in ways that were previously cost-prohibitive. VTOL UASs also offer a stable platform capable of low speed low altitude flight over small spatial scales that do not require a dedicated runway. Such flight characteristics allow VTOL UASs to collect high-resolution data at very high densities, enabling the use of structure from motion (SFM) techniques to generate three-dimensional datasets from photographs. When combined, these characteristics make VTOL UASs ideal for collecting data over agricultural or forested research areas. The goal of this study is to provide an overview of several lightweight eight-rotor VTOL UASs designed for small-scale forest remote sensing data collection. Specific objectives include: (1) the independent integration of a lightweight multispectral camera, a lightweight scanning lidar sensor, with required components (i.e. IMU, GPS, data logger) and the UAV; (2) comparison of UAS-collected data to terrestrial lidar data and airborne multispectral and lidar data; (3) comparison of UAS SFM techniques to terrestrial lidar data; and (4) multi-temporal assessment of tree decay using terrestrial lidar and UAS SfM techniques.