The effect of the plot shape, number of subplots and their spatial arrangement on the sample variance for spatially explicit point populations is analysed for a simple intensity estimator. We derive the sample variance and covariance for sampling designs involving more than one subplot. Some numerical approximations are also presented. If a clustered point pattern has to be sampled, the best strategy to reduce the sample variance is to consider as many rectangular subplots as possible, for a prescribed total sample area, distributed over a grid. In contrast, if a regular point pattern is to be sampled, then a single circular subplot should be considered. If we assume that the point configuration is Poisson, then we can consider any subplot shape and spatial distribution ensuring no overlapping between the subplots. A case study in forestry is considered to assess the validity of our results.