Improving the performance of hyperspectral pushbroom imaging spectrometers for specific science applications

Hyperspectral imaging spectrometers offer the unique chance of recording image data of a broad range of targets in the reflected solar energy spectrum. These instruments are designed upon certain requirements such as signal-to-noise ratio (SNR), spectral resolution and bandwidth or noise equivalent delta radiance. These parameters are determined by investigating one or several typical targets (e.g. vegetation, limnology, soil, atmosphere) that the instrument will sense during its operational life by means of specific instrument models. Depending on the specific application, users can demand hyperspectral image data that might cover a portion or the whole sensor spectral range and, more importantly, may have requirements different from the ones the instrument was designed for originally. Therefore, in order to meet the user requests the spectrometer settings should be modifiable. Many instruments are potentially programmable from the electric point of view, in a way that the sensor setting parameters could be changed, e.g. exposure time, on-chip averaging, the so-called binning, amplifier gains. By tuning these parameters the sensor performances can be modified according to the user needs. The Airborne Prism Experiment (APEX)1, a hyperspectral imaging spectrometer developed by a Swiss-Belgium consortium on behalf of the European Space Agency (ESA) and under the scientific supervision of the Remote Sensing Laboratories (RSL), has been designed upon certain requirements (e.g. radiance levels, SNR) but, nevertheless, the electric settings can be changed by means of a mission control file in order to fulfil user requests that differ from the default scenario. Namely, the APEX instrument allows changes of exposure time, on-chip binning and frame period. We designed and implemented a software utility that optimizes the instrument parameters based on the possible range of hardware settings and the user application requirements. This utility is based on the detector electrical and optical description, which is modelled in terms of signal and noise by using the SNR equation2. In order to develop such a model the instrument optical characteristics, i.e. transmission, must be known. The utility can be regarded as an APEX sensor simulator but it can be easily adapted to any other hyperspectral imaging apparatus. Users (i.e. sensor manufacturers, operators, scientists) can formalize their requirements and feed them into the model. E.g. a scientist is aiming at estimating the amount of leaf chlorophyll content within a vegetation target with a required minimum of detectable differences. Therefore he has to identify the needed values of SNR, spectral resolution and sampling interval as an input for the simulator. The utility evaluates all the possible solutions in terms of exposure time and on-chip binning in order to determine the one that matches the scientist needs the best. A broad variety of error deviations are reported in order to help the users in interpreting the simulation results, estimate the error and accuracy budgets accordingly. Depending on the input requirements the discordance between the users needs and the results can be significant. In such a case the utility performs a further step by analyzing post-processing strategies, as for instance off-chip binning, in a way that the requirements can be someway be met. The presented utility has a twofold advantage: (1) it allows manufacturers and sensor operators to offer an instrument that is adaptable to needs of the end-users community and (2) it lets users, mainly scientists, understand what can be achieved with a given hyperspectral instrument. The weakness of the utility relies on the lack of information about the optical and electrical parameters, which might be caused by the confidential nature of technical details, namely in private companies. We firmly believe that this utility can (a) optimize the programming of hyperspectral imaging spectrometers to gather more accurate image data and (b) let users exploit the broad range of applications that can be investigated with the available large spectral range