Methodology to filter out outliers in high spatial density data to improve maps reliability (2022)
Source: Scientia Agricola. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, AMOSTRAGEM, CANA-DE-AÇÚCAR, MAPEAMENTO DO SOLO, MILHO, SENSOR, VARIABILIDADE ESPACIAL
ABNT
MALDANER, Leonardo Felipe e MOLIN, José Paulo e SPEKKEN, Mark. Methodology to filter out outliers in high spatial density data to improve maps reliability. Scientia Agricola, v. 79, n. 1, p. 1-7, 2022Tradução . . Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162022000100102&tlng=en. Acesso em: 03 jul. 2024.APA
Maldaner, L. F., Molin, J. P., & Spekken, M. (2022). Methodology to filter out outliers in high spatial density data to improve maps reliability. Scientia Agricola, 79( 1), 1-7. doi:10.1590/1678-992x-2020-0178NLM
Maldaner LF, Molin JP, Spekken M. Methodology to filter out outliers in high spatial density data to improve maps reliability [Internet]. Scientia Agricola. 2022 ; 79( 1): 1-7.[citado 2024 jul. 03 ] Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162022000100102&tlng=enVancouver
Maldaner LF, Molin JP, Spekken M. Methodology to filter out outliers in high spatial density data to improve maps reliability [Internet]. Scientia Agricola. 2022 ; 79( 1): 1-7.[citado 2024 jul. 03 ] Available from: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162022000100102&tlng=en