This thesis considers various aspects of the use of ground-based methods and remote sensing of Biological Soil Crusts (BSC). They are mostly distributed in winter rainfall dominated areas such as those at Middleback Field Centre (MFC) in South Australia. They can be used potentially as an indicator of rangeland condition by estimating grazing pressure (trampling). Two BSC based indicators for rangeland condition assessment are species composition and cover. While there is strong agreement that BSC composition is a good indicator, there is less agreement that BSC cover alone is a good indicator. Although BSC have been included in previous remotely-sensed studies, their spectral characteristics, and hence their contributions to remotely-sensed spectral signatures, are not well known. Data collection methods were refined for suitable method selection, stratification and site characterization, and morphological/ functional group classification. Cover data of BSC were collected using a 100 m line-intercept method on the stratified land units and statistical analyses were based on the cover variance analyses. Spectra of BSC groups were collected and characterized for different remote sensing indices. Five grazing gradient models based on collected spectra were developed for the evaluation of BSC effect on remotely-sensed data. Both existing and newly developed remote sensing indices were examined for BSC detection. Sampling for cover of BSC in the field showed that there is indeed a detectable change with distance from water, suggesting that BSC cover can be used as an indicator of rangeland condition, provided that appropriate stratification of the study sites is carried out prior to sampling, and spectral differences in morphological and functional groups are taken into account. Spectral analysis of BSC components showed that different classes of organisms in the crusts have different spectral characteristics, and in particular, that the (commonly-used) perpendicular vegetation index (PD54) is not suitable for detecting BSC. On the other hand, ground-level spectral modelling showed that the Normalized Difference Vegetation Index (NDVI) and Soil Stability Index (SSI) did show a distinguishable contribution from BSC. A procedure for detecting cover of BSC was developed for image taken during the period after an effective rain, in contrast to the normal practice of selecting images of dry surfaces for interpretation. The most suitable intervals appears to be 2-4 days after rain in late autumn, winter and early spring. Of the existing indices, the SSI is the best for estimating cover of BSC from Landsat images. However, eight new indices, specifically designed for detection of BSC were developed during the cource of this work. The best results were obtained for indices using using the middle-infrared bands. These results are promising for application to rangeland monitoring and suggest that BSC cover is an important indicator of rangeland condition if appropriate stratification, classification and data-collection methods are used. The effects of BSC cover on a remotely-sensed method are considerable, and thus they can not be neglected during image interpretation. There are different phenological patterns for BSC, annual and perennial elements, thus there is the possibility for the selection of imagery based on each phenological stage to detect these elements. Application of certain indices such as the PD54 may create mis-estimation of land covers. Although some of the existing and newly developed indices had significant results for BSC cover estimation, there is a requirement for a standalone remotely-sensed method to conclude the best index.