Radiometric calibration of very large digital aerial frame mosaics

摘要

Digital aerial photography captured for ground surveys of geographic areas of the order of thousands of square kilometres may take multiple days to acquire, during which time variations in atmospheric, viewing and possibly hardware parameters may change. These changes complicate the task of radiometrically normalising the data, in the case considered here to ground reflectance, noting that normalisation has many benefits for automating procedures such as segmentation and classification. Here, we present methods for radiometric calibration of digital aerial photography, motivated by the ultimate goal of monitoring ground covers, but demonstrated here as establishing a radiometric baseline from which to monitor from. We first demonstrate application of an existing method (Collings et al., 2011, IEEE Geoscience and Remote Sensing, 49 (7), 2537-2588) on a very large data set, consisting of 30,000+ frames acquired over multiple days and record its performance. Based on those results, we introduce and test a pre-normalisation step, using Landsat Thematic Mapper (TM) imagery, and demonstrate that it produces superior results when the initial statistics are dramatically different between the frames. While such gross disparities in frame statistics can be improved with accurate meta-data and physical modelling, meta-data are often not available, particularly for historical acquisitions. The pre-normalisation step thus mimics the improvement we may expect if improved physical modelling and metadata are available. We compare our calibration procedure, including the pre-normalisation step, both qualitatively and quantitatively with calibrated data, where this step has not been performed. It is shown that this method produces visually consistent results and corrects the calibration targets to within 4.4% absolute reflectance for black-painted ground targets, 9.9% for grey-painted targets and 18.7% for white-painted targets.