Assessment of Adjacency Correction over Inland Waters Using Sentinel-2 MSI Images

Satellite remote sensing data have been used for water quality mapping, but accurate water reflectance retrieval is dependent on multiple procedures, such as atmospheric and adjacency corrections. For the latter, physical-based methods are used to minimize the adjacency effects caused by neighboring land targets close to water pixels, and implementation requires atmospheric and environmental parameters, such as aerosol optical depth and horizontal range (i.e., distance in meters) of the adjacency effect (H-Adj). Generally, the H-Adj is empirically defined by users and can lead to substantial errors in water reflectance when incorrectly used. In this research, a physical-based approach with three empirical methods to determine the H-Adj (fixed, SIMilarity Environment Correction-SIMEC, and Adaptative Window by Proportion-AWP-Inland Water) were used to correct and characterize the adjacency effects in Sentinel-2 images over Brazilian inland waters. An interactive inversion method of the deep blue waveband estimated the aerosol loading for the atmospheric correction procedure. The results of atmospheric and adjacency corrections were validated against in-situ reflectance data. The inverted aerosol loading achieved a good agreement with in-situ measurements, especially at visible wavelengths (Mean Absolute Percentage Error-MAPE for eutrophic (similar to 56%), bright (similar to 80%), and dark (similar to 288%) waters). The adjacency correction performance was near similar between the SIMEC and AWP-Inland Water methods in eutrophic and bright waters (MAPE difference < 3%). However, only the AWP-Inland Water method provided a smaller error (MAPE similar to 53%) for dark waters compared to the fixed (similar to 108%) and SIMEC (similar to 289%) methods, which shows how critical HAdj parametrization is for low water reflectance values. Simulations of different atmospheric and adjacency effects were performed, and they highlighted the importance of adjacency correction under aerosol loading higher 0.1, which is a typical aerosol loading in a dry climate season, and over extremely dark, low-reflectance waters. This paper contributes to further understanding adjacency effects in medium spatial resolution imagery of inland waters using a physical-based approach including the uncertainties in H-Adj determination.

Automated summary

This research used a physical-based approach with three empirical methods to correct and characterize the adjacency effects in Sentinel-2 images over Brazilian inland waters. The importance of determining the H-Adj parameter for low water reflectance values was highlighted, and the importance of adjacency correction under high aerosol loading and extremely dark, low-reflectance waters was emphasized.