Analysis of Turbid Water Quality Using Airborne Spectrometer Data with a Numerical Weather Prediction Model-aided Atmospheric Correction

Photogrammetric Engineering and Remote Sensing (Impact Factor: 1.61). 03/2008; 74(3):363–374. DOI: 10.14358/PERS.74.3.363


The effects of an atmospheric correction method for water quality estimation have been studied and validated for Airborne Imaging Spectrometer for Applications (AISA) data. This novel approach uses atmospheric input parameters from a numerical weather prediction model: HIRLAM (High
Resolution Limited Area Model). The atmospheric correction method developed by de Haan and Kokke (1996) corrects the spectrometer data according to the coefficients calculated using Moderate Resolution Transmittance Code (MODTRAN) radiative transfer code simulations. The airborne campaigns
were carried out at lake and coastal Case 2 type water areas between 1996 and 1998. The water quality interpretation was made using the MERIS satellite instrument wavelengths. The correction improved most of the water quality (turbidity, total suspended solids, and Secchi disk depth) estimates
when data from several flight campaigns were used jointly. The atmospheric correction reduced the standard deviation of the measurements conducted on different days. The highest improvement was obtained in the estimation of turbidity.

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