Evaluation of Spatial Variability and Mapping of Soil Properties in Precision Agriculture

摘要

It is important to understand the spatial variability of soil properties and to choose an optimal interpolation technique for mapping soil properties in precision agriculture. The objectives of this paper were: a) to evaluate spatial variability of soil properties within a field using geostatistical analysis, b) to compare the interpolation methods for mapping soil properties. This research was conducted in a wheat field of the trail farm in Shunyi county, Beijing. With an AgGPS 132, seventy-two soil samples were obtained within 40m regular intervals of a grid. The soil properties tested were N, P, and K. The results suggested that the spatial variability of P were more obvious than N and K, the random sampling error of N was bigger than P and K, and the range of K was larger than N and P. The techniques of Kriging and Inverse Distance Weighting (IDW) can significantly improve estimation precision compared with Spline technique. Comparison of Kriging and IDW estimations revealed that Kriging performed better than IDW. Furthermore, Kriging is the best with spherical or exponential model, and IDW is the best with the exponent values of 2.