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Photointerpretation of Satellite Images in Arable Crops

Photointerpretation of Satellite Images in Arable Cropsvon Nelson Mario Victoria Bariani Sie sparen 15% des UVP sparen 15%
Über Photointerpretation of Satellite Images in Arable Crops

Remote sensing (RS) of agricultural production has a high potential to contribute to the management of irrigated rice crops. To analyse this hypothesis, six commercial fields in the western border of Rio Grande do Sul with the IRGA 424RI cultivar were monitored in the field during the 2016/17 harvest, recording the characteristics of the area, management procedures and the main stages of rice development throughout the cycle. The available images from the OLI sensor of the Landsat 8 satellite with less atmospheric interference between September 2016 and April 2017 were processed to obtain the vegetation index (NDVI) of the crops and colour compositions. The NDVI images were photointerpreted (30 m resolution) with the aid of the panchromatic band (15 m resolution) when necessary. Photointerpretation of the images throughout the cycle made it possible to infer the main characteristics of the area, the plots used in production, the uniformity of the crop, the irrigation channels, the progress of sowing and harvesting. It is concluded that RS can contribute to the management of irrigated rice crops, providing information that can be clearly associated with the truth in the field.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9786206491507
  • Einband:
  • Taschenbuch
  • Seitenzahl:
  • 52
  • Veröffentlicht:
  • 26. September 2023
  • Abmessungen:
  • 150x4x220 mm.
  • Gewicht:
  • 96 g.
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Beschreibung von Photointerpretation of Satellite Images in Arable Crops

Remote sensing (RS) of agricultural production has a high potential to contribute to the management of irrigated rice crops. To analyse this hypothesis, six commercial fields in the western border of Rio Grande do Sul with the IRGA 424RI cultivar were monitored in the field during the 2016/17 harvest, recording the characteristics of the area, management procedures and the main stages of rice development throughout the cycle. The available images from the OLI sensor of the Landsat 8 satellite with less atmospheric interference between September 2016 and April 2017 were processed to obtain the vegetation index (NDVI) of the crops and colour compositions. The NDVI images were photointerpreted (30 m resolution) with the aid of the panchromatic band (15 m resolution) when necessary. Photointerpretation of the images throughout the cycle made it possible to infer the main characteristics of the area, the plots used in production, the uniformity of the crop, the irrigation channels, the progress of sowing and harvesting. It is concluded that RS can contribute to the management of irrigated rice crops, providing information that can be clearly associated with the truth in the field.

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