Landscape-based surrogate measures are commonly used to measure plant diversity, however, the difference between predicted diversity and field measures raises doubts about their effectiveness. A review of the literature was performed to address this (115 studies first evaluations, 61 second evaluations) to establish the types of surrogates used, their usefulness and factors affecting their prediction power. Three types of indicators were detected: landscape metrics, indicators based on the variability of spectral data and geomorphometric indices. The most effective indicators were slope, altitude, elevation, percentage of land cover (PLAND) and edge density (ED), as well as diverse distance metrics. Spectral data, shape index (SHAPE), patch area (PA) and the Shannon diversity index (SHDI) were less useful. Four possible explanatory variables for the effectiveness of surrogates were identified: landscape type analysed, species (taxa) examined, habitat quality and scale of research