This work describes the first in-flight absolute calibration of the "Sistema Satelital par la Observacion de la Tierra" (SSOT or Fasat-C). It was performed on January 29th 2013 at Antumapu site located in the southern area of Santiago, Chile. A description of the procedure is presented which includes both ground measurement and atmospheric characterization. The Chilean satellite for Earth observation carries on board a "New AstroSat Optical Modular Instrument" (NAOMI) high-resolution pushbroom imager which provides a 1.45 m ground sampling distance in the panchromatic (0.455-0.744 um) channel and a 5.8 m ground sampling distance for the green (0.455-0.52 p.m), blue (0.528-0.588 um), red (0.625-0.695 um) and near-infrared (0.758-0.881 urn) channels from a 620 km orbit. Radiometric calibration was carried out in order to estimate the land leaving radiance and bidirectional reflectance at the top of the atmosphere. To correct the reflectance data for atmospheric effects, the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) code was used. Aerosol Optical Depth (AOD), water vapor and ozone content were obtained from MOD04, MODO5 and MODO7 products respectively, which are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. Statistical results such as BIAS, SIGMA and RMSE were calculated for the comparison between surface reflectance values and in situ measurements. Results show that the overall accuracy of the atmospherically corrected surface reflectance calculated from FasatC imagery can be estimated to around +/- 5%, with a R-2 coefficient of 0.939 between atmospherically corrected reflectance values and in situ measurements. The atmospheric correction applied in this work by combining MODIS data and the 6S radiative transfer code could be used for further calibration of the Fasat-C images, although in situ atmospheric irradiance measurements are necessary to estimate reliable values of surface reflectance. Future validation tasks have been considered for further applications to natural resources management and surface land cover classification. (C) 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.