We have developed an SI-traceable narrow-band tunable radiance source based on an optical parametric oscillator (OPO) and an integrating sphere for the calibration of spectroradiometers. The source is calibrated with a reference detector over the ultraviolet/visible spectral range with an uncertainty of <1%. As a case study, a CubeSat spectroradiometer has been calibrated for radiance over its operating range from 370 nm to 480 nm. To validate the results, the instrument has also been calibrated with a traditional setup based on a diffuser and an FEL lamp. Both routes show good agreement within the combined measurement uncertainty. The OPO-based approach could be an interesting alternative to the traditional method, not only because of reduced measurement uncertainty, but also because it directly allows for wavelength calibration and characterization of the instrumental spectral response function and stray light effects, which could reduce calibration time and cost.
Reducing the use of pesticides by early visual detection of diseases in precision agriculture is important. Because of the color similarity between potato-plant diseases, narrow band hyper-spectral imaging is required. Payload constraints on unmanned aerial vehicles require reduc- tion of spectral bands. Therefore, we present a methodology for per-patch classification combined with hyper-spectral band selection. In controlled experiments performed on a set of individual leaves, we measure the performance of five classifiers and three dimensionality-reduction methods with three patch sizes. With the best-performing classifier an error rate of 1.5% is achieved for distinguishing two important potato-plant diseases.
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Hybrid Energy Storage System (HESS) have the potential to offer better flexibility to a grid than any single energy storage solution. However, sizing a HESS is challenging, as the required capacity, power and ramp rates for a given application are difficult to derive. This paper proposes a method for splitting a given load profile into several storage technology independent sub-profiles, such that each of the sub-profiles leads to its own requirements. This method can be used to gain preliminary insight into HESS requirements before a choice is made for specific storage technologies. To test the method, a household case is investigated using the derived methodology, and storage requirements are found, which can then be used to derive concrete storage technologies for the HESS of the household. Adding a HESS to the household case reduces the maximum import power from the connected grid by approximately 7000 W and the maximum exported power to the connected grid by approximately 1000 W. It is concluded that the method is particularly suitable for data sets with a high granularity and many data points.
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