Correction of Adjacency Effects on Nearshore Lake Remote Sensing Reflectance Considering Multifactor and Morphological Influences on the Water-Land Interface

Accurate retrieval of water quality parameters in nearshore lake environments using medium- and high-resolution remote sensing imagery is often constrained by substantial radiative interference from high-reflectance terrestrial features at the water–land boundary. To investigate the mechanisms underlying this adjacency effect, this study employed an inverse Monte Carlo (MC) radiative transfer model to quantitatively simulate the adjacency radiance under the combined influence of atmospheric conditions, observation geometry, and surface properties. Key contributing factors were identified through sensitivity analysis. In addition, a lake morphology index was introduced to characterize the spatial superposition effect of radiative diffusion caused by shoreline structure. Consistent with previous studies, the simulations confirmed the dominant contribution of terrestrial radiance to adjacency effects in nearshore waters and further quantified how this effect varies with environmental factors and lake morphological features. The intensity and spatial pattern of adjacency radiance are jointly influenced by multiple environmental factors and lake morphological features. Based on these findings, a parameterized adjacency effect correction model was developed by coupling multi-factor influences with morphological constraints, enabling effective correction of nearshore remote sensing reflectance. Validation using representative lakes demonstrated that the model significantly reduces retrieval errors in nearshore reflectance and decreases the computational cost of pixel-level MC simulation by approximately 90%. The proposed method is well-suited for correcting adjacency effects in medium- and high-resolution imagery of lakes with complex shorelines, providing high-quality remote sensing reflectance for the accurate inversion of nearshore water quality parameters.