Too often, ground based ecosystem monitoring data is collected at extremely small spatial footprints or is limited to a few spatially non representative locations. There is a discrepancy between the desired data for management and available ecological field-based information. It seems necessary to increase the management relevance of existing and future ecological monitoring data, which too often are spatially and temporally underrepresented and suboptimal for spatial model development. The session implies the need to identify spatial indicators or surrogates for patterns and processes that are inherently difficult to assess on-ground. The session addresses the need to find spatial indicators of ecosystem processes through ground or airborne spatial data or smart analysis/statistical and modelling approaches. Management of water, soil and biodiversity is management of common goods. The associated dilemma has been described by Aristotle (“the most common is the least bestowed on”) or in “The Tragedy of the commons” (Hardin, Science 162). It is increasingly difficult for governments to define and defend policies that conserve the commons because personal benefits attract more voters than policies that value the commons. Decisions are increasingly scrutinized and need to be based on clear, logical, defendable and repeatable evidence and models. However, assessment or monitoring of ecosystem conditions and processes (i.e. biodiversity, productivity, water, carbon and nutrient fluxes) is hampered by the spatio-temporal variance in natural systems. It is extremely difficult to obtain information at the appropriate spatial and temporal extent and resolution. This session will tackle the issue of spatio-temporal information demand, where direct information may be difficult or logistically impossible to obtain at the appropriate spatial and temporal scales. This session will present review, conceptual and applied research papers with ideas and applied examples of how to find or improve the spatial information base for evidence-based decision making. The expected outcome of this session is an improvement of data collection for monitoring, optimisation of spatial location and timing (i.e. we will get a better idea when and where to sample), and an improved ability to post-process spatially and temporally underrepresented data. The session brings together spatial scientists with interest in space-time variability in ecosystems, developers of environmental sensors, and environmental managers with creative ideas to improve the spatial information base. This session will present research that ultimately improves decision outcomes through the identification of spatial indicators for ecosystem conditions and processes at management relevant spatial and temporal scales.