ABSTRACT
Unmanned aerial vehicles (UAVs) are capable of acquiring remote sensing imagery quickly, repeatedly, and at high spatial resolution, with greater advantages over traditional satellite- or airplane-based platforms. This chapter will introduce UAV-based remote sensing, followed by a research project investigating grassland vegetation properties using UAV-acquired imagery. In this project, a modified digital camera (with near-infrared, green, and blue bands) was mounted on an octocopter to investigate biophysical and biochemical properties [e.g., leaf area index (LAI), chlorophyll content] of a tall grassland in Southern Ontario, Canada. Field surveys were conducted simultaneously with UAV flights to measure ground data. UAV-acquired images were processed using procedures including image quality evaluation, mosaicking, orthorectification, geometric correction, and radiometric correction. Field-measured reflectance of study sites was used in the radiometric correction. The calibrated imagery was then applied to estimate canopy LAI and chlorophyll content using vegetation indices. Results show that canopy LAI and chlorophyll content can be retrieved from UAV-acquired imagery using spectral indices (with R 2 around 0.75). Topographical conditions and soil moisture highly influenced the spatial variations of these grassland properties. Challenges of UAV applications and suggestions for future work will be discussed at the end of this chapter.
