Sunglint correction in airborne hyperspectral images over inland waters

This study assessed sunglint effects in airborne high spatial and high spectral resolution images acquired by the SpecTIR sensor under different view-illumination geometries over the Brazilian Ibitinga reservoir (Case II waters). These effects were corrected using the Goodman et al. (2008) and the Kutser et al. (2009) methods, and a variant that used the continuum removal technique to calculate the oxygen absorption band depth. The performance of each method to removing sunglint effects was evaluated by a quantitative analysis of pre- and post-sunglint correction reflectance values (residual reflectance images). Furthermore, the analysis was supported by inspection of the reflectance differences along transects placed over homogeneous masses of waters or over specific portions of the scenes affected and non-affected by sunglint. Results showed that the algorithm of Goodman et al. (2008) produced better results than the other two methods, as it approached to zero the amplitude of the reflectance values between homogenous water masses free and contaminated by sunglint. The Kutser et al. (2009) method had also good performance, except for the most contaminated sunglint portions of the scenes. When the continuum removal technique was incorporated to the Kutser et al. (2009) method, results varied with the scene and were more sensitive to atmospheric correction artifacts and instrumental signal-to-noise ratio.

[1]  A. Gitelson,et al.  Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data. , 2012, Water research.

[2]  Anatoly A. Gitelson,et al.  Remote estimation of chl-a concentration in turbid productive waters — Return to a simple two-band NIR-red model? , 2011 .

[3]  M. Bauer,et al.  Airborne hyperspectral remote sensing to assess spatial distribution of water quality characteristics in large rivers: the Mississippi River and its tributaries in Minnesota. , 2013 .

[4]  R. Clark,et al.  Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications , 1984 .

[5]  Chad I. Miller Evaluation of Sun Glint Correction Algorithms for High-Spatial Resolution Hyperspectral Imagery , 2012 .

[6]  John M. Melack,et al.  Remote sensing of aquatic vegetation: theory and applications , 2008, Environmental monitoring and assessment.

[7]  J. Mustard,et al.  A semianalytical approach to the calibration of AVIRIS data to reflectance over water application in a temperate estuary , 2001 .

[8]  Serge Andréfouët,et al.  Sea surface correction of high spatial resolution Ikonos images to improve bottom mapping in near-shore environments , 2003, IEEE Trans. Geosci. Remote. Sens..

[9]  James J. Szykman,et al.  Trophic status, ecological condition, and cyanobacteria risk of New England lakes and ponds based on aircraft remote sensing , 2012 .

[10]  Tiit Kutser,et al.  Monitoring cyanobacterial blooms by satellite remote sensing , 2006 .

[11]  Jaan Praks,et al.  A sun glint correction method for hyperspectral imagery containing areas with non-negligible water leaving NIR signal , 2009 .

[12]  John D. Hedley,et al.  Technical note: Simple and robust removal of sun glint for mapping shallow‐water benthos , 2005 .

[13]  Vittorio E. Brando,et al.  Imaging Spectrometry of Water , 2002 .

[14]  Samantha J. Lavender,et al.  Sun Glint Correction of High and Low Spatial Resolution Images of Aquatic Scenes: a Review of Methods for Visible and Near-Infrared Wavelengths , 2009, Remote. Sens..

[15]  S. Ustin,et al.  Influence of atmospheric and sea-surface corrections on retrieval of bottom depth and reflectance using a semi-analytical model: a case study in Kaneohe Bay, Hawaii. , 2008, Applied optics.

[16]  Thomas Heege,et al.  Hyperspectral seafloor mapping and direct bathymetry calculation using HyMap data from the Ningaloo reef and Rottnest Island areas in Western Australia , 2007 .

[17]  Gail P. Anderson,et al.  Analysis of Hyperion data with the FLAASH atmospheric correction algorithm , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[18]  J. Barrett,et al.  The optical properties of water droplets in the infrared , 1985 .

[19]  L. Prieur,et al.  Analysis of variations in ocean color1 , 1977 .

[20]  T. Kutser,et al.  Removing glint effects from field radiometry data measured in optically complex coastal and inland waters , 2013 .

[21]  Fred J. Tanis,et al.  Multispectral bathymetry using a simple physically based algorithm , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[22]  K. Voss,et al.  Bidirectional reflectance function for oceanic waters with varying chlorophyll concentrations: Measurements versus predictions , 2005 .

[23]  Sampsa Koponen,et al.  Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data , 2002 .

[24]  M. Schaepman,et al.  Review of constituent retrieval in optically deep and complex waters from satellite imagery , 2012 .