Spectral Mixture Analysis for Ground-Cover Mapping Michael Schmidt and Peter Scarth Abstract Monitoring of ground-cover is an important task for land management since it has been linked to indicators of soil loss, biodiversity, and pasture pro- duction. Ground-cover is an indicator adopted by Queensland natural resource and catchment management groups. However, accurate spatial estimation of ground- cover is confounded by varying cover types, cover greenness and soil colour. This research reports on ground-cover mapping based on spectral mixture anal- ysis (SMA) of LANDSAT satellite imagery. Estimates of green and senescent vegetation and soil fractions are derived from iterative SMA. Correlations with field data are form SMA iterations are discussed with r 2 values of 0.78 and 0.69 respectively for bare ground estimates over black soils. Introduction Land- and ground-cover data of the earth surface is of strong interest for studies of terrestrial and atmospheric processes of energy fluxes and feedback mechanisms from regional to global scale (Cihlar 2000). Ground cover data is a key source of information for various scientific questions and natural resource management (Jensen 1996). Major drivers for ground cover are understood to be climate and land management (Scarth et al. 2006); sustainable land management is a priority for the State of Queensland. Approximately 65% of Queensland is covered by state rural leasehold land (more than 40 million hectares). The Queensland government has ini- tiated a review process for renewal of leases which require estimates of bare-ground for the assessment of the land condition (Karfs et al. 2007). Scarth et al. (2006) used Landsat data Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) over Queensland with a regression based approach to estimate bare ground as a state-wide product using 450 field estimates as train- ing data. The product is the best available data source for ground-cover, but has M. Schmidt (B ) Department of Natural Resources and Water, Indooroopilly, QLD 4068, Australia e-mail: michael.schmidt@nrw.qld.gov.au 349 S. Jones, K. Reinke (eds.), Innovations in Remote Sensing and Photogrammetry, Lecture Notes in Geoinformation and Cartography, DOI 10.1007/978-3-540-93962-7_27, C  Springer-Verlag Berlin Heidelberg 2009