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.
| Original language | English |
|---|---|
| Title of host publication | Geostatistical Applications for Precision Agriculture |
| Editors | M.A. Oliver |
| Place of Publication | London |
| Publisher | Springer |
| Pages | 117-137 |
| ISBN (Print) | 9789048191321 |
| DOIs | |
| Publication status | Published - 2010 |
