Asset Details

  • Description:
  • Performances of regression models used to estimate maize variables applied to the calibration and validations data sets
  • License:
  • Rights Managed
  • Rights Holder:
  • Springer Nature
  • License Rights Holder:
  • © Springer Science+Business Media, LLC, part of Springer Nature 2018
  • Asset Type:
  • Image
  • Asset Subtype:
  • Table
  • Image Orientation:
  • Portrait
  • Image Dimensions:
  • 1032 x 2520
  • Image File Size:
  • 717 KB
  • Creator:
  • Martina Corti, Daniele Cavalli, Giovanni Cabassi, Antonio Vigoni, Luigi Degano, Pietro Marino Gallina
  • Credit:
  • Corti, M., Cavalli, D., Cabassi, G., Vigoni, A., Degano, L., & Marino Gallina, P. (2018). Application of a low-cost camera on a UAV to estimate maize nitrogen-related variables. Precision Agriculture, 20(4), 675-696. https://doi.org/10.1007/s11119-018-9609-y.
  • Collection:
  • Keywords:
  • CIR camera, UAV, Colorgrams, Vegetation indices, Maize
  • Restrictions:
  • Property Release:
  • No
  • Model Release:
  • No
  • Purchasable:
  • Yes
  • Sensitive Materials:
  • No
  • Article Authors:
  • Martina Corti, Daniele Cavalli, Giovanni Cabassi, Antonio Vigoni, Luigi Degano, Pietro Marino Gallina
  • Article Copyright Year:
  • 2018
  • Publication Volume:
  • 20
  • Publication Issue:
  • 4
  • Publication Date:
  • 09/14/2018
  • DOI:
  • https://doi.org/10.1007/s11119-018-9609-y

Click on image to enlarge

Would you like to download this asset? Tell us more and we can generate a quote, license and downloadable file.

Add to Cart