Agri-environmental trade-offs are issues critical for policy makers charged with managing both food supply and the sustainable use of the land. Reliable data are crucial for developing effective policies and for evaluating their impact. However, often the reliability of agricultural and agro-environmental statistics is low.
Due to the technological development, in the last decades, different kinds of geospatial data have become easily accessible at decreasing prices and have started to be an important support to statistics production process.
In this paper, we focus on methodological issues related to the use of geospatial information for sampling frame construction, sample design, stratification, ground data collection and estimation of agricultural and agri-environmental parameters. Particular attention is devoted to the impact of spatial resolution of data, change of support aggregation and disaggregation of spatial data, when remote sensing data, Global Positioning Systems and Geographic Information Systems (GIS) are used for producing agricultural and agro-environmental statistics.