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: 1.8). 01/2008; 74:363–374.

ABSTRACT 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.