Natural resources management is increasingly recognizing the complexity of interactions between socio-cultural, economic and biophysical aspects of the environment. Human actions at many different scales fundamentally control the fate of our environment. The 'Tragedy of the commons' had already been understood by the ancient Greeks and the situation has not changed. In order to obtain optimal future outcomes, we need to assess the effect of our management actions and control these accordingly. Our natural resources (water, soil, vegetation, biodiversity) are becoming increasingly precious as demand increases. Careful and informed management is required at all oranisational levels but is there an appropriate data basis for the decision making process?

In an ideal world, decisions should be based on evidence, or in other words on solid and objective data. But the reality is often different. Frequently, information is either detailed and accurate but not widely applicable, or widely applicable, but not accurate enough to give confidence in its use. In this presentation I will argue, that we need to carefully compromise accuracy for spatial representativeness. I will also argue that data, which that has been collected at inappropriate spatial or temporal scales will reduce decision outcomes even if the data is precise and accurate and I will give examples how spatial models and remote sensing can improve the usefulness of limited field data in NRM decision making.