Agricultural and environmental information systems: the integrating role of area samples

This article aims to be a contribution to the improvement of agricultural and environmental off icial statistics. Methods are applied to integrate information from state agency registers regarding crop area with ground data observed in random area samples. To improve the precision of crop area estimates in small areas (municipalities), methods using ground survey and remote sensing are applied. To improve temporal resolution of crop area estimators, methods based on time series analysis are applied. Agro-meteorological models are applied to improve crop yields statistics. A method is shown whereby crop rotation models may be a useful tool to forecast changes in the dynamics of the use of natural resources (soil, water and air) by agriculture and to foresee their environmental impact. Finally, a method to update and disaggregate information from territorial censuses on land uses is applied. These methods and models are illustrated in the framework of an information system belonging to the Spanish Ministry of the Environment and Rural and Marine Affairs. The relative improvement offered by each method is assessed by evaluating the precision gain of the proposed crop area estimates versus those currently used by the aforementioned information system. Additional key words: agrometeorological models, crop rotation models, sampling in time, small area estimation, spatiotemporal econometric models, updating regional censuses and disaggregation of information.