Investigating the Potential of a Newly Developed UAV-Mounted VNIR/SWIR Imaging System for Monitoring Crop Traits—A Case Study for Winter Wheat

Autor: Alexander Jenal, Hubert Hüging, Hella Ellen Ahrends, Andreas Bolten, Jens Bongartz, Georg Bareth
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Remote Sensing, Vol 13, Iss 9, p 1697 (2021)
Druh dokumentu: article
ISSN: 13091697
2072-4292
DOI: 10.3390/rs13091697
Popis: UAV-based multispectral multi-camera systems are widely used in scientific research for non-destructive crop traits estimation to optimize agricultural management decisions. These systems typically provide data from the visible and near-infrared (VNIR) domain. However, several key absorption features related to biomass and nitrogen (N) are located in the short-wave infrared (SWIR) domain. Therefore, this study investigates a novel multi-camera system prototype that addresses this spectral gap with a sensitivity from 600 to 1700 nm by implementing dedicated bandpass filter combinations to derive application-specific vegetation indices (VIs). In this study, two VIs, GnyLi and NRI, were applied using data obtained on a single observation date at a winter wheat field experiment located in Germany. Ground truth data were destructively sampled for the entire growing season. Likewise, crop heights were derived from UAV-based RGB image data using an improved approach developed within this study. Based on these variables, regression models were derived to estimate fresh and dry biomass, crop moisture, N concentration, and N uptake. The relationships between the NIR/SWIR-based VIs and the estimated crop traits were successfully evaluated (R2: 0.57 to 0.66). Both VIs were further validated against the sampled ground truth data (R2: 0.75 to 0.84). These results indicate the imaging system’s potential for monitoring crop traits in agricultural applications, but further multitemporal validations are needed.
Databáze: Directory of Open Access Journals
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