Understanding and managing soil spatial variation for optimal crop production

Oliver M.A., . (2007) Understanding and managing soil spatial variation for optimal crop production. [Proceedings Paper]

Properties of the soil vary at many different scales of spatial variation in the landscape and even within a single field. Traditionally in agriculture it is the variation in the soil between fields that is managed but the level of resolution that the farmer is interested in now for site-specific or precision farming is that within fields. To describe the variation of soil and other properties within fields accurately depends upon having reliable information. The latter usually comes from sampling becausewe cannot examine every possible location. The spatial variation within fields comprises a very local component of less then a few metres and one or more longer scale components of tens or hundreds of metres. We can eliminate the former to ensure that the sample represents the surrounding area by taking a bulked sample. To resolve the longer scale component of variation a suitable sampling intensity must be chosen that relates to this spatial scale. Geostatistics provides tools that can describe the spatial variation of properties where sampling is adequate in terms of both sample size and intensity. The variogram the central tool of geostatistics describe the correlation structure and it can also be used for estimation by kriging. Once the variogram is know it can be used with the kriging equations to datermine an optimal sampling scheme for kriging. A geostatistical approach for precision agriculture is illustrated with a case study of a field in southern England. Soil properties and yield were estimated using the variogram and the data. The data were sub-sampled to illustrate the effects on he estimates of both reducing the number of sampling points and increasing the sampling interval. Finally an optimal sampling interval for the field studied was determined using geostatistics.

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Abstract

Properties of the soil vary at many different scales of spatial variation in the landscape and even within a single field. Traditionally in agriculture it is the variation in the soil between fields that is managed but the level of resolution that the farmer is interested in now for site-specific or precision farming is that within fields. To describe the variation of soil and other properties within fields accurately depends upon having reliable information. The latter usually comes from sampling becausewe cannot examine every possible location. The spatial variation within fields comprises a very local component of less then a few metres and one or more longer scale components of tens or hundreds of metres. We can eliminate the former to ensure that the sample represents the surrounding area by taking a bulked sample. To resolve the longer scale component of variation a suitable sampling intensity must be chosen that relates to this spatial scale. Geostatistics provides tools that can describe the spatial variation of properties where sampling is adequate in terms of both sample size and intensity. The variogram the central tool of geostatistics describe the correlation structure and it can also be used for estimation by kriging. Once the variogram is know it can be used with the kriging equations to datermine an optimal sampling scheme for kriging. A geostatistical approach for precision agriculture is illustrated with a case study of a field in southern England. Soil properties and yield were estimated using the variogram and the data. The data were sub-sampled to illustrate the effects on he estimates of both reducing the number of sampling points and increasing the sampling interval. Finally an optimal sampling interval for the field studied was determined using geostatistics.

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Item Type:	Proceedings Paper
Additional Information:	Available at Perpustakaan Sultan Abdul Samad Universiti Putra Malaysia 43400 UPM Serdang Selangor Malaysia. mal S590.2 S683 2007 Call Number
AGROVOC Term:	SOIL BIOLOGY
AGROVOC Term:	CROPS
AGROVOC Term:	STATISTICAL METHODS
AGROVOC Term:	SOIL MANAGEMENT
AGROVOC Term:	ENGLAND
Geographical Term:	MALAYSIA
Depositing User:	Ms. Suzila Mohamad Kasim
Last Modified:	24 Apr 2025 05:13
URI:	http://webagris.upm.edu.my/id/eprint/10855

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