Topography-adjusted Monte Carlo simulation of the adjacency effect in remote sensing of coastal and inland waters. (July 2023)

• Record Type: Journal Article
• Authors: Wu, Yulun; Knudby, Anders; Lapen, David
• Is Part Of: Journal of quantitative spectroscopy & radiative transfer. Volume 303(2023)
• Publication Date: 2023-07
• Subjects: Radiative transfer -- Aquatic remote sensing -- Adjacency effect -- Atmospheric correction -- Coastal waters -- Inland waters; Spectrum analysis -- Periodicals; Radiation -- Periodicals; Analyse spectrale -- Périodiques; Rayonnement -- Périodiques; Radiation; Spectrum analysis; Periodicals; 543.0858
• DOI: 10.1016/j.jqsrt.2023.108589
• Languages: English
• ISSNs: 0022-4073

Abstract

Highlights: We present a Monte Carlo radiative transfer code for coastal aquatic applications. It supports arbitrary land surfaces, allowing modeling of the adjacency effect. It imports atmospheric settings from 6S, allowing transition of RT from 1D to 3D. In a case study, 83.7% of NIR reflectance of lakes is explained by adjacency. The code allows further development of atmospheric correction for coastal aquatic RS. Abstract: We present a Monte Carlo radiative transfer (RT) code that simulates the top-of-atmosphere (TOA) reflectance of waterbodies considering the adjacency effect. The code is the first open-source tool that supports modeling of the adjacency effect with arbitrary topography. It uses the same atmospheric and aerosol settings as 6S, along with user-input surface reflective properties and topography, allowing users to transition from 1D to 3D RT modeling and characterize the adjacency effect in their study areas. The calculation of radiometric quantities was validated against libRadtran, showing a maximum difference lower than 0.6% in extreme optical settings. Examples of the use of the code are presented in three case studies where modeled and measured radiative properties align with each other. One case study shows that 83.7% of the variance in the near-infrared TOA reflectance of 47 lakes in Minnesota was explained by the adjacency effect, emphasizing the significance of the adjacency effect to atmospheric correction algorithms that use near-infrared bands to retrieve aerosol and glint information. Another case study supports the finding of strong wavelength dependence of the effective sea-surface reflectance in above-water measurements of remote sensing reflectance. The code will support physics-based methods that remove the adjacency effect in atmospheric correction processes, and it has the potential to improve satellite-based monitoring of coastal and inland waterbodies.