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Media type:
Text;
Doctoral Thesis;
Electronic Thesis;
E-Book
Title:
A UAV-BASED VNIR/SWIR MULTISPECTRAL MULTI-CAMERA SYSTEM FOR MONITORING VEGETATION - Development, Application and Evaluation on Agricultural Systems
Contributor:
Jenal, Alexander Gerhard Josef
[Author]
Published:
Cologne University: KUPS, 2022
Language:
German;
English
Origination:
Footnote:
Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
Description:
A growing world population with limited or even declining resources and intensifying climate change are putting increasing pressure on global food production and, in particular, on the agricultural sector. Driven by technological innovations, precision agriculture, and smart farming are upcoming management strategies essential for counteracting these negative impacts. Both trends aim to use site-specific management practices to selectively account for multifaceted plant variability within croplands to maximize yields with minimal inputs, which should also lead to more sustainable agricultural management practices. However, since one cannot manage what one cannot measure, timely information on current in-field conditions is of the utmost importance for effectively implementing these agronomic management strategies. In this regard, optical remote sensing systems based on unmanned aerial vehicles (UAVs) can significantly contribute to airborne spectral vegetation analysis of small and medium-sized agricultural areas, both in research and in agricultural applications. Specifically, multispectral multi-camera systems are often used to acquire spectral image data sets for deriving established vegetation indices (VIs), which are then used as the basis for non-destructive estimation of specific crop traits to support—for example, site-specific crop management decisions in precision agriculture. These imaging systems can be effortlessly integrated into various UAV systems, and the spectral image data obtained has a high spatial resolution. Furthermore, these acquired data sets can be processed in photogrammetric workflows to derive spectral orthomosaics and 3D structural information. However, these commercial or experimental systems consist exclusively of multiple silicon-based image sensors. Moreover, they are in most cases self-contained and not adaptable to different applications, thus limiting their spectral resolution to a small number of primarily broad spectral bands in the visible (VIS) and near-infrared (NIR) ...