Influence of geostatistical rigor on the quality of maps used in precision agriculture

• Grant number: 18/25473-2
• Support Opportunities: Scholarships in Brazil - Master
• Start date: May 01, 2019
• End date: February 29, 2020
• Field of knowledge: Agronomical Sciences - Agricultural Engineering - Agricultural Machinery and Implements
• Principal Investigator: Lucas Rios do Amaral
• Grantee: Agda Loureiro Gonçalves Oliveira
• Host Institution: Faculdade de Engenharia Agrícola (FEAGRI). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 17/50205-9 - Monitoring integrated crop-livestock systems through remote sensing and precision agriculture for more sustainable production - towards low carbon agriculture, AP.TEM

Abstract

Maps used by precision agriculture to prescribe local application are based on sample grid and interpolation. Interpolation by kriging presents some difficulties related to its usage since it's a complex method and considers several parameters for calculation (i.e. anisotropy, trend, nugget effect, partial sill, range) and when they are not used it causes loss of quality in the analyses, reducing reliability of maps created by this method. Accordingly, this study aims to evaluate if a rigor in geostatistical modelling leads to expressive gain of quality of the maps used by precision agriculture. To test this, it will be studied the gain on predictive quality by treating anisotropy and tendency found in data, considering two sample grids (1 sample/ ha and 1 sample/4ha), besides of calculating semivariogram by method of moments and method of restricted maximum likelihood. These parameters will be tested in a simulated virtual field produced by a process of Gaussian Unconditional Simulation calculated by gstat package on software R. In addition, the parameters will be also tested in two experimental fields that present conditions of trend and anisotropy. The results obtained by the analyses will be evaluated through comparison of predicted values by interpolation and observed values obtained in the fields, in addition will be carry out a sensibility analyses and error propagation to identify the impact of each parameter on the estimation error's obtained by interpolation of maps using geostatistics. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

PUSCH, MAIARA; OLIVEIRA, AGDA L. G.; FONTENELLI, V, JULYANE; DO AMARAL, LUCAS R.. OIL PROPERTIES MAPPING USING PROXIMAL AND REMOTE SENSING AS COVARIAT. Engenharia Agrícola, v. 41, n. 6, p. 634-642, NOV-DEC 2021. (18/25473-2)

MAIARA PUSCH; AGDA L. G. OLIVEIRA; JULYANE V. FONTENELLI; LUCAS R. DO AMARAL. SOIL PROPERTIES MAPPING USING PROXIMAL AND REMOTE SENSING AS COVARIATE. Engenharia Agrícola, v. 41, n. 6, p. 634-642, 2021-12-17. (18/25473-2)

OLIVEIRA, AGDA L. G.; LIMA, JOAQUIM P.; BRASCO, THIAGO L.; AMARAL, LUCAS R.. The importance of modeling the effects of trend and anisotropy on soil fertility maps. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 196, p. 11-pg., 2022-03-30. (18/25473-2)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

OLIVEIRA, Agda Loureiro Gonçalves. Influence of geostatistical rigor on the quality of maps used in precision agriculture. 2020. Master's Dissertation - Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Agrícola Campinas, SP.