2010
DOI: 10.1590/s0006-87052010000500018
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Mapping of soil micronutrients in an european atlantic agricultural landscape using ordinary kriging and indicator approach

Abstract: Nutrient maps based on intensive soil sampling are useful to develop site-specific management practices. Geostatistical methods have been widely used to determine the spatial correlation and the range of spatial dependence at different sampling scales. If spatial dependence is detected, the modelled semivariograms can then be used to map the interested variable by kriging, an interpolation method that produces unbiased estimates with minimal estimation variance. The objectives of this paper were to examine and… Show more

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Cited by 16 publications
(8 citation statements)
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References 22 publications
(12 reference statements)
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“…Akbas et al (2009) analyzed spatial structure of available micronutrients and mapped the spatial pattern using geostatistical methods in a 45-ha alluvial field in Turkey. Dafonte et al (2010) mapped the spatial distribution of soil micronutrients using ordinary kriging and indicator kriging in a 30-ha agricultural area in Galicia, Spain. Fortunately, with the implementation of a series of nationwide soil surveys in China (e.g., Second National Soil Survey Project, National Soil Testing and Fertilizer Recommendation Project), it is able to obtain the data of available microelements at large scales.…”
Section: Introductionmentioning
confidence: 99%
“…Akbas et al (2009) analyzed spatial structure of available micronutrients and mapped the spatial pattern using geostatistical methods in a 45-ha alluvial field in Turkey. Dafonte et al (2010) mapped the spatial distribution of soil micronutrients using ordinary kriging and indicator kriging in a 30-ha agricultural area in Galicia, Spain. Fortunately, with the implementation of a series of nationwide soil surveys in China (e.g., Second National Soil Survey Project, National Soil Testing and Fertilizer Recommendation Project), it is able to obtain the data of available microelements at large scales.…”
Section: Introductionmentioning
confidence: 99%
“…With the existence of spatial dependence, values of the studied property can be estimated for the nonsampled locations, through the kriging method (CASTRIGNANO et al, 2002;DAFONTE et al, 2010). This method uses an unbiased linear interpolation estimator with a minimum variance which guarantees the best data estimate.…”
Section: Introductionmentioning
confidence: 99%
“…Modelling errors due to researcher subjectivity can be reduced by using fitting tests such as those based on SSR (sum of square error) (Pang et al, 2009;Parfitt et al, 2009;Dafonte et al, 2010;Lu et al, 2012), R 2 (Gallardo and Paramá, 2007;Shi et al, 2008;Pang et al, 2009;Parfitt et al, 2009;Dafonte et al, 2010;Guedes Filho et al, 2010;Montanari et al, 2012), cross-validation (Parfitt et al, 2009;Guedes Filho et al, 2010;Hani and Pazira, 2011;Lu et al, 2012) and external validation (Ferreyra et al, 2002), which assess the whole modelling process and spatial estimates. Cross-validation results are expressed using indices such as RMSE (Hani and Pazira, 2011;Teixeira et al, 2012).…”
Section: Resultsmentioning
confidence: 99%