Data from multiple sensors must be used together to gain a more complete understanding of land surface processes at a variety of scales. Although higher-level products derived from different sensors (e.g., vegetation cover, albedo, surface temperature) can be validated independently, the degree to which these sensors and their products can be compared to one another is vastly improved if their relative spectro-radiometric responses are known. Most often, sensors are directly calibrated to diffuse solar irradiation or vicariously to ground targets. However, space-based targets are not traceable to metrological standards, and vicarious calibrations are expensive and provide a poor sampling of a sensor's full dynamic range. Cross-calibration of two sensors can augment these methods if certain conditions can be met: (1) the spectral responses are similar, (2) the observations are reasonably concurrent (similar atmospheric & solar illumination conditions), (3) errors due to misregistrations of inhomogeneous surfaces can be minimized (including scale differences), and (4) the viewing geometry is similar (or, some reasonable knowledge of surface bi-directional reflectance distribution functions is available). This study extends on a previous study of Terra/MODIS and Landsat/ETM+ cross calibration by including the Terra/ASTER and EO-1/ALI sensors, exploring the impacts of cross-calibrating sensors when conditions described above are met to some degree but not perfectly. Measures for spectral response differences and methods for cross calibrating such sensors are provided in this study. These instruments are cross calibrated using the Railroad Valley playa in Nevada. Best fit linear coefficients (slope and offset) are provided for ALI-to-MODIS and ETM+-to-MODIS cross calibrations, and root-mean-squared errors (RMSEs) and correlation coefficients are provided to quantify the uncertainty in these relationships. Due to problems with direct calibration of ASTER data, linear fits were developed between ASTER and ETM+ to assess the impacts of spectral bandpass differences between the two systems. In theory, the linear fits and uncertainties can be used to compare radiance and reflectance products derived from each instrument.
Additional Publication Details
Cross-calibration of A.M. constellation sensors for long term monitoring of land surface processes
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications