Spatial and temporal evolution of olive cultivation due to pest attack, using remote sensing and satellite image processing

Authors

  • Edwin Martin Pino Vargas Universidad Nacional Jorge Basadre Grohmann
  • Germán Huayna H2O-UNJBG, Grupo de Investigación del Agua, Universidad Nacional Jorge Basadre Grohmann, Tacna 23000.

DOI:

https://doi.org/10.17268/sci.agropecu.2022.013

Keywords:

Olive plague, temporal evolution, remote sensing, spectral signatures, The Yarada, Atacama Desert

Abstract

Climate change, as well as the appearance of pests and diseases, are affecting olive plantations (Olea europaea L.) and the production of olives in the world, therefore, there is an urgent need for tools to help us identify the spatial and temporal evolution of the olive groves, regarding the attack of pests, in this case, the Orthezia olivicola and the olive borer Phloeotribus scarabaeoides. In this work, we use information from freely available satellite images that allowed us to carry out spatial and temporal analysis and the combination of vegetation indices. For the studied area, according to the values of the NDVI (Normalized Difference Vegetation Index), it was identified that the surface of diseased plants ranges from 42% to 68%, moderately healthy plants from 2% to 18%, and the state of the plantation considered as very healthy plants with a tendency to zero, which means that practically 100% of the olive trees are affected by some level. The temporal variation of the NDVI, DVI, SAVI, GNDVI, EVI2, and MSAVI indices, allowed us to establish the states of affectation as mild, moderate pest attack, the severity of the pest attack added to the water deficit, and very strong pest attack and state of permanent wilting.

Author Biography

Edwin Martin Pino Vargas, Universidad Nacional Jorge Basadre Grohmann

Director Unidad de Investigación Facultad de Ingeniería Civil, Arquitectura y Geotecnia

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Published

2022-06-06

How to Cite

Pino Vargas, E. M., & Huayna, G. . (2022). Spatial and temporal evolution of olive cultivation due to pest attack, using remote sensing and satellite image processing. Scientia Agropecuaria, 13(2), 149-157. https://doi.org/10.17268/sci.agropecu.2022.013

Issue

Section

Original Articles