Adjustment of Sentinel-3 Spectral Bands With Sentinel-2 to Enhance the Quality of Spatio-Temporally Fused Images

Abstract

Spatiotemporal fusion (STF) methods are a 1 paramount solution for generating high spatial and temporal 2 time series, overcoming the limitations of spatial and temporal 3 resolution of satellite data. STF methods typically rely on band-4 by-band fusion, assuming spectral similarities. However, selecting 5 the optimal band for fusion becomes challenging when multiple 6 narrow bands overlap with the target band, often leading to the 7 use of only one single band. Furthermore, sensor specifications 8 and observation configurations can further compound this chal-9 lenge, reducing spectral and spatial information. 10 We introduce a new preprocessing step that maximizes the 11 use of spectral information from narrow bands. It minimizes 12 radiometric differences caused by sensor variations in the STF 13 process by considering the spectral response function (SRF). 14 Our method generates adjusted bands that closely match the 15 target band's spectral characteristics, leveraging all available 16 spectral information. We evaluated this strategy at two study 17 sites employing Sentinel 2 and Sentinel 3 data by comparing 18 fused images from adjusted bands and the original bands using 19 three popular STF methods. 20 The results obtained showed that the images fused with the 21 adjusted bands were closer to the target images and achieved 22 better performance, improving the fusion quality compared to 23 the original bands (SAM by 37% and RMSE by 30%). The 24 preprocessing step offers a feasible approach to generate spectral 25 bands that would be captured by the sensors if they had the 26 same spectral characteristics. Importantly, this preprocessing 27 technique is applicable to any STF method. 28 Index Terms-Spatiotemporal data fusion, Sentinel-2, Sentinel-29 3 OLCI, Spectral Response Function, Bands overlapping, Band 30 adjustment 31 I. INTRODUCTION 32 A S sensor technologies have advanced, there has been 33 a noticeable improvement in the spatial, spectral, and 34 temporal resolutions of images captured by optical remote 35 sensing sensors used for land cover studies. However, technical 36 limitations create a fundamental trade-off among these reso-37 lutions [1]. For instance, the MultiSpectral Instrument (MSI) 38 on board Sentinel-2 (S2) provides images with high spatial 39 resolutions (10 m, 20 m, and 60 m) and a frequency of re-40 visiting of 5 days. On the other hand, the optical instruments 41