Impact of Improved Calibration of a NEO HySpex VNIR-1600 Sensor on Remote Sensing of Water Depth

This paper investigates at the example of bathymetry how much an application can profit from comprehensive characterizations required for an improved calibration of data from a state-of-the-art commercial hyperspectral sensor. A NEO HySpex VNIR-1600 sensor is used for this paper, and the improvements are based on measurements of sensor properties not covered by the manufacturer, in particular, detector nonlinearity and stray light. This additional knowledge about the instrument is used to implement corrections for nonlinearity, stray light, spectral smile distortion and nonuniform spectral bandwidth and to base the radiometric calibration on a SI-traceable radiance standard. Bathymetry is retrieved from a data take from the lake Starnberg using WASI-2D. The results using the original and improved calibration procedures are compared with ground reference data, with an emphasis on the effect of stray-light correction. For our instrument, stray-light biases the detector response from 416-500 nm up to 8% and from 700-760 nm up to 5%. Stray-light-induced errors affect bathymetry mainly in water deeper than Secchi depth, whereas in shallower water, the dominant error source is the calibration accuracy of the light source used for radiometric calibration. Stray-light correction reduced the systematic error of water depth by 19% from Secchi depth to three times Secchi depth, whereas the relative standard deviation remained stable at 5%.

[1]  Peter Gege,et al.  A case study at starnberger see for hyperspectral bathymetry mapping using inverse modeling , 2014, 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

[2]  S. Nevas,et al.  Validation of short-pulse-laser-based measurement setup for absolute spectral irradiance responsivity calibration. , 2014, Applied Optics.

[3]  Peter Gege,et al.  DLR's New Traceable Radiance Standard “RASTA” , 2012 .

[4]  Shunlin Liang,et al.  Earth system science related imaging spectroscopy — an assessment , 2009 .

[5]  Peter Gege,et al.  Calibration facility for airborne imaging spectrometers , 2005 .

[6]  Andreas Baumgartner,et al.  Independent Laboratory Characterization of NEO HySpex Imaging Spectrometers VNIR-1600 and SWIR-320m-e , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[7]  C. Mobley,et al.  Hyperspectral remote sensing for shallow waters. I. A semianalytical model. , 1998, Applied optics.

[8]  Peter Gege,et al.  Characterisation methods for the hyperspectral sensor HySpex at DLR's calibration home base , 2012, Remote Sensing.

[9]  Juan M. Fontenla,et al.  High‐resolution solar spectral irradiance from extreme ultraviolet to far infrared , 2011 .

[10]  Andreas Albert,et al.  Inversion Technique for Optical Remote Sensing in Shallow Water , 2005 .

[11]  K. Stamnes,et al.  Comparison of numerical models for computing underwater light fields. , 1993, Applied optics.

[12]  Wojciech M. Klonowski,et al.  Intercomparison of shallow water bathymetry, hydro‐optics, and benthos mapping techniques in Australian and Caribbean coastal environments , 2011 .

[13]  Z. Ahmad,et al.  Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space. , 2000, Applied optics.

[14]  Jens Nieke,et al.  Calibration facility for airborne imaging spectrometers , 2005, SPIE Remote Sensing.

[15]  D. Clark,et al.  Stray light correction algorithm for multichannel hyperspectral spectrographs. , 2012, Applied optics.

[16]  R. Richter,et al.  Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction , 2002 .

[17]  C. Mobley,et al.  An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters. , 2003, Optics express.

[18]  Andreas Baumgartner Characterization of integrating sphere homogeneity with an uncalibrated imaging spectrometer , 2013, 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

[19]  Daniel Schlaepfer,et al.  PARGE: parametric geocoding based on GCP-calibrated auxiliary data , 1998, Optics & Photonics.

[20]  P Mouroulis,et al.  Design of pushbroom imaging spectrometers for optimum recovery of spectroscopic and spatial information. , 2000, Applied optics.

[21]  Andreas Müller,et al.  Ortho Image Production within an Automatic Processing Chain for hyperspectral Airborne Scanner ARES , 2005 .

[22]  J. Hollandta,et al.  Providing radiometric traceability for the calibration home base of DLR by PTB , 2013 .

[23]  Dariusz Stramski,et al.  Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe , 2003 .

[24]  A. Sperling,et al.  Colorimetry of LEDs with array spectroradiometers , 2009 .

[25]  Claude Flener,et al.  Estimating deep water radiance in shallow water: adapting optical bathymetry modelling to shallow river environments , 2013 .

[26]  Monica Pepe,et al.  BOMBER: A tool for estimating water quality and bottom properties from remote sensing images , 2012, Comput. Geosci..

[27]  Peter Gege,et al.  WASI-2D: A software tool for regionally optimized analysis of imaging spectrometer data from deep and shallow waters , 2014, Comput. Geosci..