Remote sensing (e.g. photogrammetry, Landsat and Lidar) is increasingly providing a fertile source of site and landscape information for establishing baselines and monitoring. As well as information on vegetation structural attributes, remote sensing can provide information on functional attributes such as fire footprints. Ecosystem models combined with remotely-derived attributes can be used to create datasets from a combination of ground-based calibration sites and attributes, such as species composition and CGP 13501 data. Observations by ‘citizen scientists’ have many advantages as a result of their often sustained nature, close proximity to and familiarity with a subject area. Their contribution may be limited, however, as depending on their experience, interest and training, electron acceptor may be able to identify some things extremely reliably, but may not be able to conduct complex observations and measurements. The researcher or analyst must assess the value of all sources and determine the reliability and hence value each. Multi-Criteria Analysis (MCA) provides a useful tool to incorporate a wide range of information to compile, sequence and analyse of relationships between land use and its effects on the environment (Janssen, 2001 and Lesslie et al., 2008).