Characterizing the relative calibration of Landsat-7 (ETM+) visible bands with Terra (MODIS) over clear waters: The implications for monitoring water resources

Abstract

Since its launch, the Enhanced Thematic Mapper plus (ETM+) onboard Landsat-7 has been continuously monitored via different calibration techniques to ensure it maintains the science requirements for demanding application areas. The majority of its applications, including agriculture and forestry, require a robust calibration for medium to high reflective targets. However, when imaging water resources, then the question becomes whether the calibration coefficients are valid for the dark end of the sensor's responsivity curve. Motivated by the Landsat Data Continuity Mission (LDCM) and its potential for providing long-term, robust water studies, in this effort, the calibration status of ETM+ visible bands are examined using a cross-calibration technique. The well-calibrated Terra-MODIS scenes (collection 5) of the past decade over relatively optically stable waters were chosen to evaluate ETM+ stability. The cross-comparison showed that the calibration instability of ETM+ reflective bands lie well within its radiometric uncertainty. The slight calibration differences were found to be less than 1.6%, 0.93%, and 3.2% for the blue, green and the red bands obtained for the period when the MODIS had been radiometrically stable. The NIR band of ETM+, however, exhibits, on average, 4.8% higher signals than those of MODIS. The error budget analysis for the calibration differences showed that 1.2%, 1.6%, 3.5%, and 6.5% errors are associated with the Visible-Near-Infrared (VNIR) bands, respectively. Using the results from the calibration study combined with simulations, it was demonstrated that ETM+ underestimates the retrieved diffuse surface reflectance (Rd) in the blue and the green bands as much as 12.2% and 4.4%, respectively, while the red band is overestimated 37%, on average, when studying slightly/moderately turbid. The uncertainties in the retrieval of Rd were applied in a water constituent retrieval framework where a physics-based model was utilized to obtain concentrations of chlorophyll-a (CHL) and total suspended solids (TSS) from a Landsat-7 dataset in slightly/moderately turbid waters. It was found that the calibration-induced errors in the retrieval of Rd yield, on average, 20% error in retrieval of these components. The results indicate that although ETM+ is well calibrated, its calibration status should be quantified rigorously for water studies when physics-based methods are employed for the removal of atmospheric effects. The over-water characterization of Landsat satellites will become more crucial when the LDCM becomes operational due to its increased capabilities for water resource studies.