|Title||The role of positional errors while interpolating soil organic carbon contents using satellite imagery|
|Author(s)||Samsonova, V.P.; Meshalkina, J.L.; Blagoveschensky, Y.N.; Yaroslavtsev, A.M.; Stoorvogel, J.J.|
|Source||Precision Agriculture (2018). - ISSN 1385-2256 - p. 1 - 15.|
Soil Geography and Landscape
|Publication type||Refereed Article in a scientific journal|
|Keyword(s)||Digital soil mapping - Geostatistics - Positional errors - Stochastic modelling|
Increasingly, soil surveys make use of a combination of legacy data, ancillary data and new field data. While combining the different sources of information, positional errors can play a large role. For example, the spatial discrepancy between remote sensing images and field data can depend on many factors, including the positioning accuracy of ground-based observations. The accuracy of GPS receivers for the territory of Russia is approximately 3–10 m. The aim of the study was to estimate the impact of sampling positioning accuracy on the relationship between soil organic carbon content and the infrared channel of the WorldView-2 satellite image and for mapping soil organic carbon contents in an agricultural field in the territory of the Bryansk Opolje (Russia). Intensive sampling of the topsoil took place. The positional accuracy was also measured and used to perturb the locations of the samples. The data were used to study: (i) the relationships between soil organic carbon and infrared reflectance, (ii) the variation in soil organic carbon through five different interpolation techniques, and (iii) the fraction of the fields with low soil organic matter contents. The study showed that the positional inaccuracies can have an important impact. The standardized methods to estimate the positional accuracy, perturb the locations and evaluate its impact seems to be an easy way to explore the quality of data.