An automatic method for subpixel registration of KMSS-M imagery based on coarse-resolution actualized reference

Abstract

The paper describes a method for automatic subpixel-accurate geographic referencing of imagery acquired by KMSS-M with 60 m spatial resolution, based on leveraging a coarse, reconstructed, cloud-free and daily updated MODIS surface reflectance reference image. The method is based on maximizing Pearson's correlation value when determining an optimal local displacement of the distorted image fragment by comparing with the reference image. To assess the effectiveness of the method when used over continental-scale and heterogeneous areas, three experiments were carried out providing quantitative estimates of imagery registration errors: an experiment with model datasets, an experiment to estimate the absolute registration error of MODIS reference imagery, and an experiment to estimate the registration error of geocorrected KMSS-M data. Experimental evaluation of the method based on model datasets of decameter-resolution Sentinel-2 (MSI) imagery demonstrated its robustness when used over a variety of environmental conditions over a one year-long observation period. The average georeferencing error of MODIS coarse-resolution reference was shown to be less than 20 meters in Red and Near-infrared bands. Corrected KMSS-M imagery evaluation over the Russian Grain Belt within 2020 has shown, on average, the subpixel referencing accuracy both in Red and Near-infrared bands, while the average absolute georeferencing error of the original uncorrected KMSS-M imagery was shown to be about 3 kilometers. Subpixel registration accuracy of KMSS-M imagery, corrected with MODIS-based coarse-resolution reference, opens new prospects for using multi-temporal analysis of this multispectral surface reflectance data in a variety of scientific and practical applications associated with vegetation cover satellite monitoring. The technological flexibility of the method ensures its applicability to data from other satellite systems for Earth optical remote sensing.

Accuracy Assessment of Atmospheric Correction of KMSS-2 Meteor-M #2.2 Data over Northern Eurasia

“…The resultant mean absolute error of geolocation for all qualified nodes processed over the Russian grain belt does not exceed 40 meters for KMSS imagery acquired during the season of 2020, as was shown earlier [33] using Sentinel-2 (MSI) imagery as a reference. It was also shown that geolocation misalignments between source KMSS and reference Sentinel-2 imagery are not uncommon to exceed 3000 meters.…”

“…It was also indicated that LOWESS-reconstructed MODIS reference imagery features higher geolocation accuracy than the original MOD09 datasets. Namely, using Sentinel-2 (MSI) imagery of decameter resolution as a reference, it was shown that the average geolocation error of LOWESS-reconstructed MODIS was below 20 m [33], making these MODIS images suitable for sub-pixel KMSS imagery georeferencing.…”

“…A detailed description of components of KMSS data processing workflow was given in several studies [6,8,31,33]. In this section, we focus on key elements of the workflow and their performance.…”