Iron is an essential element for almost all living species. Previous studies demonstrated that both the growth rate and concentration of chlorophyll a in cultures of cyanobacteria were limited by insufficient Fe concentrations. The cyanobacteria biological soil crust in desert where most rain falls seasons are dominated by filamentous species are
well adapted for primary colonization of arid environments due to their extraordinary ability to survive desiccation and extreme temperature, high pH and salinity. Satellite imageries are widely used to map geological and environmental features at different scales. To date, little research has been done to spectrally examine biological soil crusts or map them using remote sensing. Recent researches demonstrated that ASTER visible- near infrared scanner systems can be used successfully to map iron ores and cyanobacteria soil crust. In this study Mathematical Evaluation Method (MEM) performed on ASTER imagery data, firstly. This research demonstrates cyanobacteria growth –iron contamination relationships by remote sensing techniques at the Chadormalu desert, Yazd Province, Iran. In other words, this study illustrates directional relationship of spatial distribution between cyanobacteria soil crust and major iron ores contamination at this mining area, probably related to cyanobacteria physiology. The MEM method, despite being approximate is suitable in detecting iron contamination in inaccessible remote areas on earth or may be useful in astrobiological studies, especially, in Mars biological explorations.