Comparison of Crop Trait Retrieval Strategies Using UAV-Based VNIR Hyperspectral Imaging.

ABSTRACT: Hyperspectral cameras onboard unmanned aerial vehicles (UAVs) have recently emerged for monitoring crop traits at the sub-field scale. Different physical, statistical, and hybrid methods for crop trait retrieval have been developed. However, spectra collected from UAVs can be confounded by various issues, including illumination variation throughout the crop growing season, the effect of which on the retrieval performance is not well understood at present. In this study, four retrieval methods are compared, in terms of retrieving the leaf area index (LAI), fractional vegetation cover (fCover), and canopy chlorophyll content (CCC) of potato plants over an agricultural field for six dates during the growing season. We analyzed: (1) The standard look-up table method (LUTstd), (2) an improved (

SUBMITTER: Abdelbaki A 

PROVIDER: S-EPMC7613394 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature