Abstract
Many environmental variables that are relevant to precision agriculture, such as crop and soil properties and climate, vary both in time and space. Farmers can often benefit greatly from accurate information about the status of these variables at any particular point in time and space to aid their management decisions on irrigation, fertilizer and pesticide applications, and so on. Practically, however, it is not feasible to measure a variable exhaustively in space and time. Space–time geostatistics can be useful to fill in the gaps. This chapter explains the basic elements of space–time geostatistics and uses a case study on space–time interpolation of the normalized difference vegetation index (NDVI) as an indicator of biomass in a Dutch potato field. Space–time geostatistics proves to be a useful extension to spatial geostatistics for precision agriculture, although theoretical as well as practical advances are required to mature this subject area and make it ready to be used for within-season, within-field decision making by farmers.
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Acknowledgements
We thank Mr. Claassen for use of the Lauwersmeer farm data. We thank Allard de Wit (Alterra) for his suggestion to use the double logistic function and assistance with fitting it to the NDVI data.
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Heuvelink, G.B.M., van Egmond, F.M. (2010). Space–Time Geostatistics for Precision Agriculture: A Case Study of NDVI Mapping for a Dutch Potato Field. In: Oliver, M. (eds) Geostatistical Applications for Precision Agriculture. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9133-8_5
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