A geostatistical approach for modelling and combining spatial data with different support

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Detalles Bibliográficos
Publicado en:	Advances in Animal Biosciences vol. 8, no. 2 (Jul 2017), p. 594-599
Autor principal:	Castrignanò, A
Otros Autores:	Quarto, R, Venezia, A, Buttafuoco, G
Publicado:	Cambridge University Press
Materias:	Italy Environmental Software Geophysics Data analysis Geostatistics Diamonds Methods Datasets Mining Spatial data Studies Sensors Mathematical analysis Alluvial deposits Rivers Electrical resistivity Computer vision Vertical orientation Remote sensing Pixels Metallurgy Agronomy Mathematical models Information processing Geographic information systems Soil conductivity Statistics Matrices (mathematics) Functions (mathematics) Agricultural management Temporal distribution Skin Statistical analysis Water content Data processing Computer programs Applied statistics Documentation Methodology Alluvial plains Probability theory Remote sensors Mines Electrical conductivity Soils Tomatoes
Acceso en línea:	Citation/Abstract Full Text - PDF
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Descripción
Resumen:	The paper proposes a geostatistical framework to solve the issues of heterogeneous support for spatial estimation. Apparent soil electrical conductivity (ECa) was measured in a field cropped with San Marzano tomato using a multiple frequency electromagnetic profiler with 6 operating frequencies. Mixed support kriging was used to estimate ECa taking into account the change of support. The method includes punctual kriging with the error being the dispersion variance associated with each frequency. The individual ECa maps were weighted by the dispersion variance to obtain a map which was used for field partition in management zones.
ISSN:	2040-4700 2040-4719
DOI:	10.1017/S2040470017000048
Fuente:	Health & Medical Collection