Abstract: The iron tailing samples of different particle sizes, from different dry and wet conditions and different mining areas in Hebei Province were selected for high−spectral measurement in the study. The high−spectral features of iron tailings from different conditions were compared. Then the effective window of high−spectral recognition of iron tailings was determined by fitting analysis. The results show that: firstly, as for the iron tailing samples of different sizes from different mining areas, no significant spectral value difference is found within the range of 500—600 nm; while significant reflectance value difference within the range of 500—600 nm is observed concerning iron tailing samples from different dry and wet conditions; secondly, if the iron tailings are divided into dry and wet types and analyzed accordingly, the spectral range of 500—600 nm is proved to be an area where the spectral characteristics of iron tailings are only slightly affected by factors such as particle sizes, humidity and deposit types, which is a primary recognition window, suitable for multispectral remote sensing information extraction of iron tailings. After the comparative tests of discriminating rule information extraction through multi-spectral remote sensing imagery in the DT-tailings and DT−tailings−B2, the resulting extraction accuracy by DT−tailings−B2 rule is found to have increased in wet tailings, dry tailings, and ores from open pit mines and mountains; the extraction accuracy increases by 5.00%, 22.04%, 4.49% and 19.59% respectively. The results verify the validity of high−multispectral remote sensing information extraction from iron tailings.