In the context of spatial statistics, the classical variogram estimator proposed by Matheron is not robust against outliers in the data, nor is Cressie and Hawkins' estimator. Therefore, we suggest the use of a variogram estimator based on a highly robust estimator of scale. The robustness properties of these three estimators are analysed and compared. Several simulations are carried out from a spherical underlying variogram, with various amounts of outliers in the data. Results show that the highly robust variogram estimator improves the estimation significantly