When establishing environmental monitoring programmes, it crucial to make reliable cost estimates, especially where a field survey is involved. This paper presents a methodology for creating a spatial measure of a field survey effort (SE). A set of relevant variables affecting a SE (e.g. areas with rough terrain, or distant from the main road network) was classified using fuzzy sets and then combined to produce spatially explicit effort indicators, which were integrated to a single measure using an analytic hierarchy process (AHP). To evaluate this approach and identify the limits for its application, three spatially nested case studies were used to test the spatial expression of SE and the scalable capacity of the method itself. The presented methodology could cope with variations in the scale and data resolution, retrieving a coherent estimate of SE across the different case studies. The presented methodology is therefore useful for (i) testing the network designs for sampling bias related to SE, (ii) comparing alternative sampling designs, (iii) assessing the sampling costs and (iv) supporting the human and logistical resource management.