Sectioning remote imagery for characterization of Avena sterilis infestations. Part A: Weed abundance

Sectioning remote imagery for characterization of Avena sterilis infestations. Part A: Weed... Software was developed to spatially assess key crop characteristics from remotely sensed imagery. Sectioning and Assessment of Remote Images (SARI®), written in IDL® works as an add-on to ENVI®, has been developed to implement precision agriculture strategies. SARI® splits field plot images into grids of rectangular “micro-images” or “micro-plots”. The micro-plot length and width were defined as multiples of the image spatial resolution. SARI® calculates different indicators for each micro-plot, including the integrated pixel digital values. Studies on weed patches were done with SARI® using ground-truth data and remote images of two wheat plots infested with Avena sterilis at LaFloridaII and Navajas (Southern Spain). Patches of A. sterilis represented 47.5 and 19.2% of the field areas at the two locations, respectively; the infested areas were a combination of a few large and several small patches. At LaFloridaII, 2.1% of all patches were >500 m2 and 55.0% of all patches were smaller than 10 m2. Based on ground-truth weed abundance data, SARI® output includes geo-referenced and visual herbicide prescription maps, which could be used with variable-rate application equipment. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Sectioning remote imagery for characterization of Avena sterilis infestations. Part A: Weed abundance

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Publisher
Springer Journals
Copyright
Copyright © 2011 by Springer Science+Business Media, LLC
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-011-9249-y
Publisher site
See Article on Publisher Site

Abstract

Software was developed to spatially assess key crop characteristics from remotely sensed imagery. Sectioning and Assessment of Remote Images (SARI®), written in IDL® works as an add-on to ENVI®, has been developed to implement precision agriculture strategies. SARI® splits field plot images into grids of rectangular “micro-images” or “micro-plots”. The micro-plot length and width were defined as multiples of the image spatial resolution. SARI® calculates different indicators for each micro-plot, including the integrated pixel digital values. Studies on weed patches were done with SARI® using ground-truth data and remote images of two wheat plots infested with Avena sterilis at LaFloridaII and Navajas (Southern Spain). Patches of A. sterilis represented 47.5 and 19.2% of the field areas at the two locations, respectively; the infested areas were a combination of a few large and several small patches. At LaFloridaII, 2.1% of all patches were >500 m2 and 55.0% of all patches were smaller than 10 m2. Based on ground-truth weed abundance data, SARI® output includes geo-referenced and visual herbicide prescription maps, which could be used with variable-rate application equipment.

Journal

Precision AgricultureSpringer Journals

Published: Nov 6, 2011

References

  • Spatial stability of Avena sterilis ssp. ludoviciana populations under annual applications of low rates of imazamethabenz
    Barroso, J; Fernández-Quintanilla, C; Ruiz, D; Hernáiz, P; Rew, LJ
  • Comparison of sampling methodologies for site-specific management of Avena sterilis
    Barroso, J; Ruiz, D; Fernández-Quintanilla, C; Leguizamón, ES; Hernaiz, P; Ribeiro, A; Díaz, B; Maxwell, BD; Rew, LJ
  • Detecting weed-free and weed-infested areas of a soybean field using near-infrared spectral data
    Chang, J; Clay, SA; Clay, DE; Kevin, D
  • A decision algorithm for patch spraying
    Christensen, S; Heisel, T; Walter, AM; Graglia, E

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