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@INPROCEEDINGS{Dogar:1037663,
      author       = {Dogar, Sardar Salar Saeed and Brogi, Cosimo and Donat,
                      Marco and Vereecken, Harry and Huisman, Johan Alexander},
      title        = {{E}valuating the impact of integrating {EMI} and remote
                      sensing data in the delineation of management zones in a
                      heterogeneous agricultural field},
      reportid     = {FZJ-2025-00828},
      year         = {2024},
      abstract     = {Accurate and reliable characterization of intra-field
                      heterogeneity in soil properties, and water content is
                      crucial in precision agriculture, as these factors
                      significantly impact crop performance and yield.
                      Non-invasive hydro-geophysical methods, such as
                      electromagnetic induction (EMI), can be employed to
                      delineate intra-field agricultural management zones, which
                      represent areas with homogeneous field characteristics that
                      have a similar influence on crops. Integrating additional
                      data sources, such as remote sensing imagery and yield maps,
                      has the potential to enhance the quality of these management
                      zones. However, extracting both above-ground and subsurface
                      information from multiple datasets for large agricultural
                      fields presents challenges in data harmonization and
                      analysis. Furthermore, the selection of optimal dataset
                      combinations and the impact of different data products on
                      management zone delineation have not been fully explored. In
                      this study, we present an approach to delineate intra-field
                      management zones using two key indicators: EMI measurements
                      conducted with a CMD Mini-Explorer and a CMD Mini-Explorer
                      Special-Edition (featuring 3 and 6 coil separations,
                      respectively), and the Normalized Difference Vegetation
                      Index (NDVI) derived from PlanetScope satellite imagery. To
                      assess the contribution of each indicator, three scenarios
                      were used for zone delineation: (1) using EMI measurements
                      alone, (2) using NDVI alone, and (3) using a combination of
                      both. The resulting management zones were then evaluated by
                      analyzing differences in multi-year crop yield and soil
                      information using statistical methods. The results revealed
                      that NDVI alone provided strong insights into field
                      characteristics and could serve as a valuable alternative to
                      traditional yield maps, particularly for capturing
                      above-ground variability. However, the integration of NDVI
                      with EMI data was most beneficial, capturing a more
                      comprehensive view of both above and subsurface spatial
                      variability. Overall, the findings demonstrate the
                      advantages of integrating proximal and remote sensing data
                      and suggest a high potential for differential crop
                      fertilization and targeted soil management in the study
                      area.},
      month         = {Nov},
      date          = {2024-11-05},
      organization  = {Tereno Workshop 2024, Leipzig
                       (Germany), 5 Nov 2024 - 7 Nov 2024},
      subtyp        = {After Call},
      cin          = {IBG-3},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {2173 - Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217) / DFG project G:(GEPRIS)390732324 - EXC 2070:
                      PhenoRob - Robotik und Phänotypisierung für Nachhaltige
                      Nutzpflanzenproduktion (390732324)},
      pid          = {G:(DE-HGF)POF4-2173 / G:(GEPRIS)390732324},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/1037663},
}