Peter Gege

Inversion of irradiance and remote sensing reflectance in shallow water between 400 and 800 nm for calculations of water and bottom properties

What we believe to be a new inversion procedure for multi- and hyperspectral data in shallow water, represented by the subsurface irradiance and remote sensing reflectance spectra, was developed based on analytical equations by using the method of nonlinear curve fitting. The iteration starts using an automatic determination of the initial values of the fit parameters: concentration of phytoplankton and suspended matter, absorption of gelbstoff, bottom depth, and the fractions of up to six bottom types. Initial values of the bottom depth and suspended matter concentration are estimated analytically. Phytoplankton concentration and gelbstoff absorption are initially calculated by the method of nested intervals. A sensitivity analysis was made to estimate the accuracy of the entire inversion procedure including model error, error propagation, and influence of instrument characteristics such as noise, and radiometric and spectral resolution. The entire inversion technique is included in a public-domain software (WASI) to provide a fast and user-friendly tool of forward and inverse modeling.

The water color simulator WASI: an integrating software tool for analysis and simulation of optical in situ spectra

A WINDOWS-based program was developed for modeling and analyzing optical in situ measurements in aquatic environments. It supports eight types of spectra which are commonly measured by instruments on ship: downwelling irradiance above and below the water surface, upwelling radiance above and below the surface, remote sensing reflectance above and below the surface, irradiance reflectance, specular reflectance at the water surface, absorption, attenuation, and bottom reflectance. These spectra can either be simulated (by forward calculation) or analyzed (by inverse modeling) using well-established analytical models. The variability of a spectrum is determined by up to 25 parameters, depending on the spectrum type. All model constants and input spectra can be changed easily for adaptation to a specific region. Effective methods are included for dealing with series of spectra. For some spectrum types, inversion is a critical task and can produce erroneous results, that is when different parameter combinations cause similar spectra. In order to handle this problem, specific inversion techniques are implemented for critical spectrum types, and measures are included which allow fine-tuning of the fit procedure by the user.

Water constituents and water depth retrieval from Sentinel-2A – a first evaluation in an oligotrophic lake

Satellite remote sensing may assist in meeting the needs of lake monitoring. In this study, we aim to evaluate the potential of Sentinel-2 to assess and monitor water constituents and bottom characteristics of lakes at spatio-temporal synoptic scales. In a field campaign at Lake Starnberg, Germany, we collected validation data concurrently to a Sentinel-2A (S2-A) overpass. We compared the results of three different atmospheric corrections, i.e., Sen2Cor, ACOLITE and MIP, with in situ reflectance measurements, whereof MIP performed best (r = 0.987, RMSE = 0.002 sr−1). Using the bio-optical modelling tool WASI-2D, we retrieved absorption by coloured dissolved organic matter (aCDOM(440)), backscattering and concentration of suspended particulate matter (SPM) in optically deep water; water depths, bottom substrates and aCDOM(440) were modelled in optically shallow water. In deep water, SPM and aCDOM(440) showed reasonable spatial patterns. Comparisons with in situ data (mean: 0.43 m−1) showed an underestimation of S2-A derived aCDOM(440) (mean: 0.14 m−1); S2-A backscattering of SPM was slightly higher than backscattering from in situ data (mean: 0.027 m−1 vs. 0.019 m−1). Chlorophyll-a concentrations (~1 mg·m−3) of the lake were too low for a retrieval. In shallow water, retrieved water depths exhibited a high correlation with echo sounding data (r = 0.95, residual standard deviation = 0.12 m) up to 2.5 m (Secchi disk depth: 4.2 m), though water depths were slightly underestimated (RMSE = 0.56 m). In deeper water, Sentinel-2A bands were incapable of allowing a WASI-2D based separation of macrophytes and sediment which led to erroneous water depths. Overall, the results encourage further research on lakes with varying optical properties and trophic states with Sentinel-2A.

A TOOL FOR INVERSE MODELING OF SPECTRAL MEASUREMENTS IN DEEP AND SHALLOW WATERS

A software tool was developed for simulating and inverse modeling of optical spectral measurements in deep and shallow waters above and below the water surface. It supports eight major spectrum types which are commonly measured by instruments on ship: irradiance reflectance, remote sensing reflectance, downwelling irradiance, upwelling radiance, absorption, attenuation, specular reflectance at the surface, and bottom reflectance. Calculation is based on analytical models. For deep water different well-established models are included, for shallow water and surface reflections new models were developed. The program is designed as a user-friendly, sensor-independent spectra generator and spectra analyzer with well documented calculation steps and automatic result visualization. It is suited to generate and analyze large series of spectra. All model constants and input spectra can be changed easily for adaptation to a specific region. This contribution summarizes the models, explains the inversion techniques, and describes how to apply the program.

Analytic model for the direct and diffuse components of downwelling spectral irradiance in water

The direct and diffuse components of downwelling irradiance have in general different path lengths in water, and hence they decrease differently with sensor depth. Furthermore, the ever-changing geometry of a wind-roughened and wave-modulated water surface induces uncorrelated intensity changes to these components. To cope with both effects, an analytic model of the downwelling irradiance in water was developed that calculates the direct and diffuse components separately. By assigning weights f(dd) and f(ds) to the intensities of the two components, measurements performed at arbitrary surface conditions can be analyzed by treating f(dd) and f(ds) as fit parameters. The model was validated against HydroLight and implemented into the public-domain software WASI. It was applied to data from three German lakes to determine the statistics of f(dd) and ff(ds), to derive the sensor depth of each measurement and to estimate the concentrations of water constituents.

WASI-2D: A software tool for regionally optimized analysis of imaging spectrometer data from deep and shallow waters

An image processing software has been developed which allows quantitative analysis of multi- and hyperspectral data from oceanic, coastal and inland waters. It has been implemented into the Water Colour Simulator WASI, which is a tool for the simulation and analysis of optical properties and light field parameters of deep and shallow waters. The new module WASI-2D can import atmospherically corrected images from airborne sensors and satellite instruments in various data formats and units like remote sensing reflectance or radiance. It can be easily adapted by the user to different sensors and to optical properties of the studied area. Data analysis is done by inverse modelling using established analytical models. The bio-optical model of the water column accounts for gelbstoff (coloured dissolved organic matter, CDOM), detritus, and mixtures of up to 6 phytoplankton classes and 2 spectrally different types of suspended matter. The reflectance of the sea floor is treated as sum of up to 6 substrate types. An analytic model of downwelling irradiance allows wavelength dependent modelling of sun glint and sky glint at the water surface. The provided database covers the spectral range from 350 to 1000nm in 1nm intervals. It can be exchanged easily to represent the optical properties of water constituents, bottom types and the atmosphere of the studied area.

Characterisation methods for the hyperspectral sensor HySpex at DLR’s calibration home base

The German Aerospace Center’s (DLR) Remote Sensing Technology Institute (IMF) operates a laboratory for the characterisation of imaging spectrometers. Originally designed as Calibration Home Base (CHB) for the imaging spectrometer APEX, the laboratory can be used to characterise nearly every airborne hyperspectral system. Characterisation methods will be demonstrated exemplarily with HySpex, an airborne imaging spectrometer system from Norsk Elektro Optikks A/S (NEO). Consisting of two separate devices (VNIR-1600 and SWIR-320me) the setup covers the spectral range from 400 nm to 2500 nm. Both airborne sensors have been characterised at NEO. This includes measurement of spectral and spatial resolution and misregistration, polarisation sensitivity, signal to noise ratios and the radiometric response. The same parameters have been examined at the CHB and were used to validate the NEO measurements. Additionally, the line spread functions (LSF) in across and along track direction and the spectral response functions (SRF) for certain detector pixels were measured. The high degree of lab automation allows the determination of the SRFs and LSFs for a large amount of sampling points. Despite this, the measurement of these functions for every detector element would be too time-consuming as typical detectors have 105 elements. But with enough sampling points it is possible to interpolate the attributes of the remaining pixels. The knowledge of these properties for every detector element allows the quantification of spectral and spatial misregistration (smile and keystone) and a better calibration of airborne data. Further laboratory measurements are used to validate the models for the spectral and spatial properties of the imaging spectrometers. Compared to the future German spaceborne hyperspectral Imager EnMAP, the HySpex sensors have the same or higher spectral and spatial resolution. Therefore, airborne data will be used to prepare for and validate the spaceborne system’s data.

Sources of variance of downwelling irradiance in water

The downwelling irradiance in water is highly variable due to the focusing and defocusing of sunlight and skylight by the wave-modulated water surface. While the time scales and intensity variations caused by wave focusing are well studied, little is known about the induced spectral variability. Also, the impact of variations of sensor depth and inclination during the measurement on spectral irradiance has not been studied much. We have developed a model that relates the variance of spectral irradiance to the relevant parameters of the environmental and experimental conditions. A dataset from three German lakes was used to validate the model and to study the importance of each effect as a function of depth for the range of 0 to 5 m.

Estimation of phytoplankton concentration from downwelling irradiance measurements in water

Downwelling irradiance is so far not used directly for the determination of water constituents, mainly due to the large and unpredictable fluctuations of the underwater light field induced by the water surface. The potential of a new analytical model, which can cope with such environmental influences, was analyzed for the estimation of phytoplankton concentration using data from two German lakes. It turned out that the model is able to determine phytoplankton concentration in these lakes above a threshold between 0.4 and 0.9 μg/1, depending on the phytoplankton class, and total pigment concentration (sum of chlorophyll-a and phaeophytin-a) with an uncertainty of 0.7 μg/1. This new in-situ spectroscopy method is particularily of interest for shallow waters, where it is difficult to apply the usual reflectance-based algorithms due to bottom influences.

Supporting Facilities of the Airborne Imaging Spectrometer APEX

The facilities to support the ESAs airborne APEX hyperspectral mission simulator are described. These facilities include calibration tools, such as specific processing in a dedicated Processing and Archiving Facility (PAF), operational calibration and characterization using the Calibration Home Base (CHB), the In-Flight Characterization facility (IFC) and the Calibration Test Master (CTM). Further on, a preview on major applications and the corresponding development efforts to provide scientific data products up to level 2/3 to the user are outlined. Products dedicated for the retrieval of limnology, vegetation, atmospheric parameters, as well as general classification routines and rapid mapping tasks are currently under development and prepared for dissemination by the APEX Science Center (ASC) and the APEX Operations Center (AOC).