EGU21-9521
https://doi.org/10.5194/egusphere-egu21-9521
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Estimation of water stress in olive orchards through remote sensing data analysis

Luz Karime Atencia1,2,3, María Gómez del Campo1,3, Gema Camacho1,3, Antonio Hueso1,3, and Ana M. Tarquis1,3
Luz Karime Atencia et al.
  • 1CEIGRAM, Universidad Politécnica de Madrid, Spain
  • 2Unmanned Technical Works (UTW), Leganés, Madrid, Spain
  • 3ETSIAAB, Universidad Politécnica de Madrid, Madrid, Spain

Olive is the main fruit tree in Spain representing 50% of the fruit trees surface, around 2,751,255 ha. Due to its adaptation to arid conditions and the scarcity of water, regulated deficit irrigation (RDI) strategy is normally applied in traditional olive orchards and recently to high density orchards. The application of RDI is one of the most important technique used in the olive hedgerow orchard. An investigation of the detection of water stress in nonhomogeneous olive tree canopies such as orchards using remote sensing imagery is presented.

In 2018 and 2019 seasons, data on stem water potential were collected to characterize tree water state in a hedgerow olive orchard cv. Arbequina located in Chozas de Canales (Toledo). Close to the measurement’s dates, remote sensing images with spectral and thermal sensors were acquired. Several vegetation indexes (VI) using both or one type of sensors were estimated from the areas selected that correspond to the olive crown avoiding the canopy shadows.

Nonparametric statistical tests between the VIs and the stem water potential were carried out to reveal the most significant correlation. The results will be discussing in the context of robustness and sensitivity between both data sets at different phenological olive state.

ACKNOWLODGEMENTS

Financial support provided by the Spanish Research Agency co-financed with European Union FEDER funds (AEI/FEDER, UE, AGL2016-77282-C3-2R project) and Comunidad de Madrid through calls for grants for the completion of Industrial Doctorates, is greatly appreciated.

How to cite: Atencia, L. K., Gómez del Campo, M., Camacho, G., Hueso, A., and Tarquis, A. M.: Estimation of water stress in olive orchards through remote sensing data analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9521, https://doi.org/10.5194/egusphere-egu21-9521, 2021.

Displays

Display file