Understanding of soil organic carbon content（SOC）based on remote sensing(RS)and geographic information system(GIS)techniques becomes the development trend of current discipline.In this research，remotely sensed spectral data from Landsat 8 OLI，soil organic carbon content（121 samples from 0~20 cm soil layer）and the related ground parameters in the West River Valley were integrated to construct models for spatial prediction in the area.Space inversion was employed to check the model reliability.Results indicated that evaluation of SOC content was achieved by the constructed models using remote sensing data（P=0.000)，implying that it was potentially reliable to predict SOC content.When the related ground parameters of soil parent material，landforms and agricultural land use were considered，respectively，the R2 values of prediction models were significantly improved（P=0.000).Concretely，the R2 was increased from 0.385 to 0.579，indicating the involvement of ground parameters was beneficial to prediction accuracy.In contrast to the determined content，optimal interpolation model better reflected the basic pattern of regional distribution for SOC content.However，the accuracy of spatial inversion should be improved in some special areas.