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@PHDTHESIS{Chakhvashvili:1047698,
      author       = {Chakhvashvili, Erekle and Rascher, Uwe},
      title        = {{R}emote sensing of crop parameters using {UAV}-based
                      multispectral imaging and radiative transfer models},
      school       = {University of Bonn},
      type         = {Dissertation},
      publisher    = {Universitäts- und Landesbibliothek Bonn},
      reportid     = {FZJ-2025-04464},
      pages        = {160},
      year         = {2025},
      note         = {Dissertation, University of Bonn, 2025},
      abstract     = {In the face of climate change and a growing global
                      population, it's important to increase the output of
                      agricultural systems and improve crop resilience to
                      challenging environmental conditions. Achieving these
                      objectives requires monitoring crop health in the field, as
                      well as breeding more resilient crop varieties. However,
                      these tasks are labor-intensive and not economically
                      sustainable. Remote sensing tools, such as uncrewed aerial
                      vehicles (UAVs), have demonstrated their potential to
                      successfully measure crop parameters while minimizing the
                      need for human and financial resources. The mapping of crop
                      parameters has been widely studied in both the satellite and
                      UAV research communities. The UAV community typically uses
                      data-driven and parametric models to predict crop
                      parameters, while satellites rely on physical models called
                      radiative transfer models (RTMs) to retrieve these
                      variables. However a key drawback of using satellites is
                      their low spatial and temporal resolution for applications
                      in precision agriculture. This thesis explores the use of
                      radiative transfer model PROSAIL to retrieve crop variables
                      with UAVs and multispectral imaging. First, we examine the
                      reflectance calibration workflows of the optical sensor,
                      vital for time-series image analysis. We propose a
                      multi-panel approach for calibrating reflectance of a
                      multispectral sensor, which our analysis shown to perform
                      better than the one-point calibration. Next we address the
                      challenges of retrieving structural and biochemical
                      variables in complex and homogeneous crop canopies. Our
                      findings confirm that the higher spatial resolution provided
                      by UAVs doesn't disrupt the fundamental assumptions of the
                      PROSAIL, which was originally developed for simpler
                      canopies. Finally, we investigate the sensor synergies for
                      crop stress detection. In one study we explore the synergy
                      between terrestrial laser scanner, multispectral imaging,
                      and RTMs to track drought-induced leaf movement in soybean.
                      We show that it's possible to track leaf orientation using
                      just multispectral cameras. Another study discusses the
                      challenges associated with using multiple sensors together
                      to detect crop stress.},
      keywords     = {UAV (Other) / remote sensing (Other) / RTMs (Other) / crop
                      (Other) / ddc:630 (Other)},
      cin          = {IBG-2},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {2171 - Biological and environmental resources for
                      sustainable use (POF4-217) / DFG project G:(GEPRIS)390732324
                      - EXC 2070: PhenoRob - Robotik und Phänotypisierung für
                      Nachhaltige Nutzpflanzenproduktion (390732324)},
      pid          = {G:(DE-HGF)POF4-2171 / G:(GEPRIS)390732324},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.48565/BONNDOC-646},
      url          = {https://juser.fz-juelich.de/record/1047698},
}