Use of remote sensing images through a multispectral sensor to evaluate the variability of phosphorus and potassium in the sugarcane crop

Author(s)

Almir Salvador Neto

• Document type: Doctoral Thesis
• Press: Jaboticabal. 2022-11-03.
• Institution: Universidade Estadual Paulista (Unesp). Faculdade de Ciências Agrárias e Veterinárias. Jaboticabal
• Defense date: 2022-07-04
• Advisor: José Eduardo Corá

Abstract

The objective of the research project was to use remote sensing images through a multispectral sensor to evaluate the spatial and temporal variability of sugarcane productivity, define management zones and evaluate the variability of phosphorus and potassium in soil and tissues. vegetable. To achieve the proposal, a commercial area of sugarcane was monitored over two harvests 2018/2019 and 2019/2020 with the use of a multispectral sensor embedded in a drone, in order to validate the vegetation indices for the evaluation of the spatial and temporal variability of the sugarcane crop, identification of management zones and the variability of phosphorus and potassium. The vegetation indices GRVI, NDVI, NDRE, GNDVI, SAVI and RVI made it possible, through the reflectances, to evaluate the spatial and temporal variability of the productivity of the sugarcane crop, to identify the management zones, and finally to identify the variability of the nutrients phosphorus and potassium. The RVI vegetation index was the most accurate in combination with the productivity map to define management zones, followed by NDVI, NDRE, GNDVI, SAVI and GRVI. In addition, they made it possible to identify soil fertility in the respective management zones, the extraction and export of P and K, the textural classes, and finally concluded that the vegetation indices are precise tools both for the delimitation of management zones and for proper management of fertilizers. (AU)

• FAPESP's process: 20/04486-9 - Use of remote sensing and technologies for mapping sugarcane productivity for efficiency in the use of potassium and phosphorus
• Grantee: Almir Salvador Neto
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)