Comparison Between Vegetation Index Obtained by Active and Passive Proximal Sensors

Authors

  • Victor Hugo Rohden Prudente
  • Erivelto Mercante
  • Jerry Adriani Johann
  • Carlos Henrique Wachholz de Souza
  • Lucas Volochen Oldoni
  • Luiz Almeida
  • Willyan Ronaldo Becker
  • Bruno Bonemberger da Silva

DOI:

https://doi.org/10.5296/jas.v9i2.18462

Abstract

Proximal sensors have been used to characterize the crop biophysical properties by reflectance values and/or using Vegetation Indices (IV). Our goal with this work is to compare NDVI (Normalized Difference Vegetation Index) spectra-temporal profiles obtained by active (GreenSeeker 505 Handheld) and passive (FieldSpec4 model Standard-Res) proximal sensors to monitor soybeans and beans. It was monitored agricultural fields with soybeans Nidera 5909RG variety and beans Imperador variety, located in the municipality of Cascavel, Parana state, Brazil. The proximal sensors were used to monitor the crop's conditions on different Days After Sowing (DAS). NDVI from FieldSpec4 (NDVI FS) showed a higher correlation with GreenSeeker NDVI (NDVI GS) in the wavelengths of 649 nm and 771 nm for soybeans (rs = 0.9105) and 646 nm and 792 nm for beans (rs = 0.9382). The inter-calibration of NDVI GS values in function of NDVI FS, considering the entire phenological cycle, resulted in RMSE = 0.0520 and dr = 0.8630 for soybeans and RMSE = 0.0636 and dr = 0.8890 for beans. NDVI values showed saturation during the major vegetative development of the crops, interfering in the inter-calibration process. In general, the NDVI GS and NDVI FS were similar in terms of their spectral-temporal pattern. According to our results, the active sensor could be used to crop monitoring, resulting in a lower cost and less climatic interference.

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Published

2021-04-27

How to Cite

Prudente, V. H. R., Mercante, E., Johann, J. A., Souza, C. H. W. de, Oldoni, L. V., Almeida, L., … Silva, B. B. da. (2021). Comparison Between Vegetation Index Obtained by Active and Passive Proximal Sensors. Journal of Agricultural Studies, 9(2), 391–405. https://doi.org/10.5296/jas.v9i2.18462

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