Image de couverture de livre

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

Enregistré dans:
Publié dans:Advances in Animal Biosciences vol. 8, no. 2 (Jul 2017), p. 594-599
Auteur principal: Castrignanò, A
Autres auteurs: Quarto, R, Venezia, A, Buttafuoco, G
Publié:
Cambridge University Press
Sujets:
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
Accès en ligne:Citation/Abstract
Full Text - PDF
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
Résumé: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
Source:Health & Medical Collection